[DISCUSS] FLIP-27: Refactor Source Interface

[Becket Qin]

Hi Dawid,

Thanks for the comments. This actually brings another relevant question
about what does a "bounded source" imply. I actually had the same
impression when I look at the Source API. Here is what I understand after
some discussion with Stephan. The bounded source has the following impacts.

1. API validity.
- A bounded source generates a bounded stream so some operations that only
works for bounded records would be performed, e.g. sort.
- To expose these bounded stream only APIs, there are two options:
     a. Add them to the DataStream API and throw exception if a method is
called on an unbounded stream.
     b. Create a BoundedDataStream class which is returned from
env.boundedSource(), while DataStream is returned from env.continousSource().
Note that this cannot be done by having single env.source(theSource) even
the Source has a getBoundedness() method.

2. Scheduling
- A bounded source could be computed stage by stage without bringing up all
the tasks at the same time.

3. Operator behaviors
- A bounded source indicates the records are finite so some operators can
wait until it receives all the records before it starts the processing.

In the above impact, only 1 is relevant to the API design. And the current
proposal in FLIP-27 is following 1.b.

// boundedness depends of source property, imo this should always be
> preferred
>


DataStream<MyType> stream = env.source(theSource);


In your proposal, does DataStream have bounded stream only methods? It
looks it should have, otherwise passing a bounded Source to env.source()
would be confusing. In that case, we will essentially do 1.a if an
unbounded Source is created from env.source(unboundedSource).

If we have the methods only supported for bounded streams in DataStream, it
seems a little weird to have a separate BoundedDataStream interface.

Am I understand it correctly?

Thanks,

Jiangjie (Becket) Qin



On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <[hidden email]>
wrote:

> Hi all,
>
> Really well written proposal and very important one. I must admit I have
> not understood all the intricacies of it yet.
>
> One question I have though is about where does the information about
> boundedness come from. I think in most cases it is a property of the
> source. As you described it might be e.g. end offset, a flag should it
> monitor new splits etc. I think it would be a really nice use case to be
> able to say:
>
> new KafkaSource().readUntil(long timestamp),
>
> which could work as an "end offset". Moreover I think all Bounded sources
> support continuous mode, but no intrinsically continuous source support the
> Bounded mode. If I understood the proposal correctly it suggest the
> boundedness sort of "comes" from the outside of the source, from the
> invokation of either boundedStream or continousSource.
>
> I am wondering if it would make sense to actually change the method
>
> boolean Source#supportsBoundedness(Boundedness)
>
> to
>
> Boundedness Source#getBoundedness().
>
> As for the methods #boundedSource, #continousSource, assuming the
> boundedness is property of the source they do not affect how the enumerator
> works, but mostly how the dag is scheduled, right? I am not against those
> methods, but I think it is a very specific use case to actually override
> the property of the source. In general I would expect users to only call
> env.source(theSource), where the source tells if it is bounded or not. I
> would suggest considering following set of methods:
>
> // boundedness depends of source property, imo this should always be preferred
>
> DataStream<MyType> stream = env.source(theSource);
>
>
> // always continous execution, whether bounded or unbounded source
>
> DataStream<MyType> boundedStream = env.continousSource(theSource);
>
> // imo this would make sense if the BoundedDataStream provides additional features unavailable for continous mode
> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
>
>
> Best,
>
> Dawid
>
>
> On 04/12/2019 11:25, Stephan Ewen wrote:
>
> Thanks, Becket, for updating this.
>
> I agree with moving the aspects you mentioned into separate FLIPs - this
> one way becoming unwieldy in size.
>
> +1 to the FLIP in its current state. Its a very detailed write-up, nicely
> done!
>
> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]> <[hidden email]> wrote:
>
>
> Hi all,
>
> Sorry for the long belated update. I have updated FLIP-27 wiki page with
> the latest proposals. Some noticeable changes include:
> 1. A new generic communication mechanism between SplitEnumerator and
> SourceReader.
> 2. Some detail API method signature changes.
>
> We left a few things out of this FLIP and will address them in separate
> FLIPs. Including:
> 1. Per split event time.
> 2. Event time alignment.
> 3. Fine grained failover for SplitEnumerator failure.
>
> Please let us know if you have any question.
>
> Thanks,
>
> Jiangjie (Becket) Qin
>
> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]> <[hidden email]> wrote:
>
>
> Hi  Łukasz!
>
> Becket and me are working hard on figuring out the last details and
> implementing the first PoC. We would update the FLIP hopefully next week.
>
> There is a fair chance that a first version of this will be in 1.10, but
>
> I
>
> think it will take another release to battle test it and migrate the
> connectors.
>
> Best,
> Stephan
>
>
>
>
> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <[hidden email]> <[hidden email]>
>
> wrote:
>
> Hi,
>
> This proposal looks very promising for us. Do you have any plans in
>
> which
>
> Flink release it is going to be released? We are thinking on using a
>
> Data
>
> Set API for our future use cases but on the other hand Data Set API is
> going to be deprecated so using proposed bounded data streams solution
> could be more viable in the long term.
>
> Thanks,
> Łukasz
>
> On 2019/10/01 15:48:03, Thomas Weise <[hidden email]> <[hidden email]> wrote:
>
> Thanks for putting together this proposal!
>
> I see that the "Per Split Event Time" and "Event Time Alignment"
>
> sections
>
> are still TBD.
>
> It would probably be good to flesh those out a bit before proceeding
>
> too
>
> far
>
> as the event time alignment will probably influence the interaction
>
> with
>
> the split reader, specifically ReaderStatus emitNext(SourceOutput<E>
> output).
>
> We currently have only one implementation for event time alignment in
>
> the
>
> Kinesis consumer. The synchronization in that case takes place as the
>
> last
>
> step before records are emitted downstream (RecordEmitter). With the
> currently proposed interfaces, the equivalent can be implemented in
>
> the
>
> reader loop, although note that in the Kinesis consumer the per shard
> threads push records.
>
> Synchronization has not been implemented for the Kafka consumer yet.
> https://issues.apache.org/jira/browse/FLINK-12675
>
> When I looked at it, I realized that the implementation will look
>
> quite
>
> different
> from Kinesis because it needs to take place in the pull part, where
>
> records
>
> are taken from the Kafka client. Due to the multiplexing it cannot be
>
> done
>
> by blocking the split thread like it currently works for Kinesis.
>
> Reading
>
> from individual Kafka partitions needs to be controlled via
>
> pause/resume
>
> on the Kafka client.
>
> To take on that responsibility the split thread would need to be
>
> aware
>
> of
>
> the
> watermarks or at least whether it should or should not continue to
>
> consume
>
> a given split and this may require a different SourceReader or
>
> SourceOutput
>
> interface.
>
> Thanks,
> Thomas
>
>
> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email]> <[hidden email]> wrote:
>
>
> Hi Stephan,
>
> Thank you for feedback!
> Will take a look at your branch before public discussing.
>
>
> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]> <[hidden email]>
>
> wrote:
>
> Hi Biao!
>
> Thanks for reviving this. I would like to join this discussion,
>
> but
>
> am
>
> quite occupied with the 1.9 release, so can we maybe pause this
>
> discussion
>
> for a week or so?
>
> In the meantime I can share some suggestion based on prior
>
> experiments:
>
> How to do watermarks / timestamp extractors in a simpler and more
>
> flexible
>
> way. I think that part is quite promising should be part of the
>
> new
>
> source
>
> interface.
>
>
>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
>
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
>
> Some experiments on how to build the source reader and its
>
> library
>
> for
>
> common threading/split patterns:
>
>
>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
>
> Best,
> Stephan
>
>
> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]> <[hidden email]>
>
> wrote:
>
> Hi devs,
>
> Since 1.9 is nearly released, I think we could get back to
>
> FLIP-27.
>
> I
>
> believe it should be included in 1.10.
>
> There are so many things mentioned in document of FLIP-27. [1] I
>
> think
>
> we'd better discuss them separately. However the wiki is not a
>
> good
>
> place
>
> to discuss. I wrote google doc about SplitReader API which
>
> misses
>
> some
>
> details in the document. [2]
>
> 1.
>
>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
>
> 2.
>
>
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
>
> CC Stephan, Aljoscha, Piotrek, Becket
>
>
> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email]> <[hidden email]>
>
> wrote:
>
> Hi Steven,
> Thank you for the feedback. Please take a look at the document
>
> FLIP-27
>
> <
>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
>
> which
>
> is updated recently. A lot of details of enumerator were added
>
> in
>
> this
>
> document. I think it would help.
>
> Steven Wu <[hidden email]> <[hidden email]> 于2019年3月28日周四 下午12:52写道：
>
>
> This proposal mentioned that SplitEnumerator might run on the
> JobManager or
> in a single task on a TaskManager.
>
> if enumerator is a single task on a taskmanager, then the job
>
> DAG
>
> can
>
> never
> been embarrassingly parallel anymore. That will nullify the
>
> leverage
>
> of
>
> fine-grained recovery for embarrassingly parallel jobs.
>
> It's not clear to me what's the implication of running
>
> enumerator
>
> on
>
> the
>
> jobmanager. So I will leave that out for now.
>
> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email]> <[hidden email]>
>
> wrote:
>
> Hi Stephan & Piotrek,
>
> Thank you for feedback.
>
> It seems that there are a lot of things to do in community.
>
> I
>
> am
>
> just
>
> afraid that this discussion may be forgotten since there so
>
> many
>
> proposals
>
> recently.
> Anyway, wish to see the split topics soon :)
>
> Piotr Nowojski <[hidden email]> <[hidden email]> 于2019年1月24日周四
>
> 下午8:21写道：
>
> Hi Biao!
>
> This discussion was stalled because of preparations for
>
> the
>
> open
>
> sourcing
>
> & merging Blink. I think before creating the tickets we
>
> should
>
> split this
>
> discussion into topics/areas outlined by Stephan and
>
> create
>
> Flips
>
> for
>
> that.
>
> I think there is no chance for this to be completed in
>
> couple
>
> of
>
> remaining
>
> weeks/1 month before 1.8 feature freeze, however it would
>
> be
>
> good
>
> to aim
>
> with those changes for 1.9.
>
> Piotrek
>
>
> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email]> <[hidden email]>
>
> wrote:
>
> Hi community,
> The summary of Stephan makes a lot sense to me. It is
>
> much
>
> clearer
>
> indeed
>
> after splitting the complex topic into small ones.
> I was wondering is there any detail plan for next step?
>
> If
>
> not,
>
> I
>
> would
>
> like to push this thing forward by creating some JIRA
>
> issues.
>
> Another question is that should version 1.8 include
>
> these
>
> features?
>
> Stephan Ewen <[hidden email]> <[hidden email]> 于2018年12月1日周六 上午4:20写道：
>
>
> Thanks everyone for the lively discussion. Let me try
>
> to
>
> summarize
>
> where I
>
> see convergence in the discussion and open issues.
> I'll try to group this by design aspect of the source.
>
> Please
>
> let me
>
> know
>
> if I got things wrong or missed something crucial here.
>
> For issues 1-3, if the below reflects the state of the
>
> discussion, I
>
> would
>
> try and update the FLIP in the next days.
> For the remaining ones we need more discussion.
>
> I would suggest to fork each of these aspects into a
>
> separate
>
> mail
>
> thread,
>
> or will loose sight of the individual aspects.
>
> *(1) Separation of Split Enumerator and Split Reader*
>
>  - All seem to agree this is a good thing
>  - Split Enumerator could in the end live on JobManager
>
> (and
>
> assign
>
> splits
>
> via RPC) or in a task (and assign splits via data
>
> streams)
>
>  - this discussion is orthogonal and should come later,
>
> when
>
> the
>
> interface
>
> is agreed upon.
>
> *(2) Split Readers for one or more splits*
>
>  - Discussion seems to agree that we need to support
>
> one
>
> reader
>
> that
>
> possibly handles multiple splits concurrently.
>  - The requirement comes from sources where one
>
> poll()-style
>
> call
>
> fetches
>
> data from different splits / partitions
>    --> example sources that require that would be for
>
> example
>
> Kafka,
>
> Pravega, Pulsar
>
>  - Could have one split reader per source, or multiple
>
> split
>
> readers
>
> that
>
> share the "poll()" function
>  - To not make it too complicated, we can start with
>
> thinking
>
> about
>
> one
>
> split reader for all splits initially and see if that
>
> covers
>
> all
>
> requirements
>
> *(3) Threading model of the Split Reader*
>
>  - Most active part of the discussion ;-)
>
>  - A non-blocking way for Flink's task code to interact
>
> with
>
> the
>
> source
>
> is
>
> needed in order to a task runtime code based on a
> single-threaded/actor-style task design
>    --> I personally am a big proponent of that, it will
>
> help
>
> with
>
> well-behaved checkpoints, efficiency, and simpler yet
>
> more
>
> robust
>
> runtime
>
> code
>
>  - Users care about simple abstraction, so as a
>
> subclass
>
> of
>
> SplitReader
>
> (non-blocking / async) we need to have a
>
> BlockingSplitReader
>
> which
>
> will
>
> form the basis of most source implementations.
>
> BlockingSplitReader
>
> lets
>
> users do blocking simple poll() calls.
>  - The BlockingSplitReader would spawn a thread (or
>
> more)
>
> and
>
> the
>
> thread(s) can make blocking calls and hand over data
>
> buffers
>
> via
>
> a
>
> blocking
>
> queue
>  - This should allow us to cover both, a fully async
>
> runtime,
>
> and a
>
> simple
>
> blocking interface for users.
>  - This is actually very similar to how the Kafka
>
> connectors
>
> work.
>
> Kafka
>
> 9+ with one thread, Kafka 8 with multiple threads
>
>  - On the base SplitReader (the async one), the
>
> non-blocking
>
> method
>
> that
>
> gets the next chunk of data would signal data
>
> availability
>
> via
>
> a
>
> CompletableFuture, because that gives the best
>
> flexibility
>
> (can
>
> await
>
> completion or register notification handlers).
>  - The source task would register a "thenHandle()" (or
>
> similar)
>
> on the
>
> future to put a "take next data" task into the
>
> actor-style
>
> mailbox
>
> *(4) Split Enumeration and Assignment*
>
>  - Splits may be generated lazily, both in cases where
>
> there
>
> is a
>
> limited
>
> number of splits (but very many), or splits are
>
> discovered
>
> over
>
> time
>
>  - Assignment should also be lazy, to get better load
>
> balancing
>
>  - Assignment needs support locality preferences
>
>  - Possible design based on discussion so far:
>
>    --> SplitReader has a method "addSplits(SplitT...)"
>
> to
>
> add
>
> one or
>
> more
>
> splits. Some split readers might assume they have only
>
> one
>
> split
>
> ever,
>
> concurrently, others assume multiple splits. (Note:
>
> idea
>
> behind
>
> being
>
> able
>
> to add multiple splits at the same time is to ease
>
> startup
>
> where
>
> multiple
>
> splits may be assigned instantly.)
>    --> SplitReader has a context object on which it can
>
> call
>
> indicate
>
> when
>
> splits are completed. The enumerator gets that
>
> notification and
>
> can
>
> use
>
> to
>
> decide when to assign new splits. This should help both
>
> in
>
> cases
>
> of
>
> sources
>
> that take splits lazily (file readers) and in case the
>
> source
>
> needs to
>
> preserve a partial order between splits (Kinesis,
>
> Pravega,
>
> Pulsar may
>
> need
>
> that).
>    --> SplitEnumerator gets notification when
>
> SplitReaders
>
> start
>
> and
>
> when
>
> they finish splits. They can decide at that moment to
>
> push
>
> more
>
> splits
>
> to
>
> that reader
>    --> The SplitEnumerator should probably be aware of
>
> the
>
> source
>
> parallelism, to build its initial distribution.
>
>  - Open question: Should the source expose something
>
> like
>
> "host
>
> preferences", so that yarn/mesos/k8s can take this into
>
> account
>
> when
>
> selecting a node to start a TM on?
>
> *(5) Watermarks and event time alignment*
>
>  - Watermark generation, as well as idleness, needs to
>
> be
>
> per
>
> split
>
> (like
>
> currently in the Kafka Source, per partition)
>  - It is desirable to support optional
>
> event-time-alignment,
>
> meaning
>
> that
>
> splits that are ahead are back-pressured or temporarily
>
> unsubscribed
>
>  - I think i would be desirable to encapsulate
>
> watermark
>
> generation
>
> logic
>
> in watermark generators, for a separation of concerns.
>
> The
>
> watermark
>
> generators should run per split.
>  - Using watermark generators would also help with
>
> another
>
> problem of
>
> the
>
> suggested interface, namely supporting non-periodic
>
> watermarks
>
> efficiently.
>
>  - Need a way to "dispatch" next record to different
>
> watermark
>
> generators
>
>  - Need a way to tell SplitReader to "suspend" a split
>
> until a
>
> certain
>
> watermark is reached (event time backpressure)
>  - This would in fact be not needed (and thus simpler)
>
> if
>
> we
>
> had
>
> a
>
> SplitReader per split and may be a reason to re-open
>
> that
>
> discussion
>
> *(6) Watermarks across splits and in the Split
>
> Enumerator*
>
>  - The split enumerator may need some watermark
>
> awareness,
>
> which
>
> should
>
> be
>
> purely based on split metadata (like create timestamp
>
> of
>
> file
>
> splits)
>
>  - If there are still more splits with overlapping
>
> event
>
> time
>
> range
>
> for
>
> a
>
> split reader, then that split reader should not advance
>
> the
>
> watermark
>
> within the split beyond the overlap boundary. Otherwise
>
> future
>
> splits
>
> will
>
> produce late data.
>
>  - One way to approach this could be that the split
>
> enumerator
>
> may
>
> send
>
> watermarks to the readers, and the readers cannot emit
>
> watermarks
>
> beyond
>
> that received watermark.
>  - Many split enumerators would simply immediately send
>
> Long.MAX
>
> out
>
> and
>
> leave the progress purely to the split readers.
>
>  - For event-time alignment / split back pressure, this
>
> begs
>
> the
>
> question
>
> how we can avoid deadlocks that may arise when splits
>
> are
>
> suspended
>
> for
>
> event time back pressure,
>
> *(7) Batch and streaming Unification*
>
>  - Functionality wise, the above design should support
>
> both
>
>  - Batch often (mostly) does not care about reading "in
>
> order"
>
> and
>
> generating watermarks
>    --> Might use different enumerator logic that is
>
> more
>
> locality
>
> aware
>
> and ignores event time order
>    --> Does not generate watermarks
>  - Would be great if bounded sources could be
>
> identified
>
> at
>
> compile
>
> time,
>
> so that "env.addBoundedSource(...)" is type safe and
>
> can
>
> return a
>
> "BoundedDataStream".
>  - Possible to defer this discussion until later
>
> *Miscellaneous Comments*
>
>  - Should the source have a TypeInformation for the
>
> produced
>
> type,
>
> instead
>
> of a serializer? We need a type information in the
>
> stream
>
> anyways, and
>
> can
>
> derive the serializer from that. Plus, creating the
>
> serializer
>
> should
>
> respect the ExecutionConfig.
>
>  - The TypeSerializer interface is very powerful but
>
> also
>
> not
>
> easy to
>
> implement. Its purpose is to handle data super
>
> efficiently,
>
> support
>
> flexible ways of evolution, etc.
>  For metadata I would suggest to look at the
>
> SimpleVersionedSerializer
>
> instead, which is used for example for checkpoint
>
> master
>
> hooks,
>
> or for
>
> the
>
> streaming file sink. I think that is is a good match
>
> for
>
> cases
>
> where
>
> we
>
> do
>
> not need more than ser/deser (no copy, etc.) and don't
>
> need to
>
> push
>
> versioning out of the serialization paths for best
>
> performance
>
> (as in
>
> the
>
> TypeSerializer)
>
>
> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <[hidden email]>
> wrote:
>
>
> Hi Biao,
>
> Thanks for the answer!
>
> So given the multi-threaded readers, now we have as
>
> open
>
> questions:
>
> 1) How do we let the checkpoints pass through our
>
> multi-threaded
>
> reader
>
> operator?
>
> 2) Do we have separate reader and source operators or
>
> not? In
>
> the
>
> strategy
>
> that has a separate source, the source operator has a
>
> parallelism of
>
> 1
>
> and
>
> is responsible for split recovery only.
>
> For the first one, given also the constraints
>
> (blocking,
>
> finite
>
> queues,
>
> etc), I do not have an answer yet.
>
> For the 2nd, I think that we should go with separate
>
> operators
>
> for
>
> the
>
> source and the readers, for the following reasons:
>
> 1) This is more aligned with a potential future
>
> improvement
>
> where the
>
> split
>
> discovery becomes a responsibility of the JobManager
>
> and
>
> readers are
>
> pooling more work from the JM.
>
> 2) The source is going to be the "single point of
>
> truth".
>
> It
>
> will
>
> know
>
> what
>
> has been processed and what not. If the source and the
>
> readers
>
> are a
>
> single
>
> operator with parallelism > 1, or in general, if the
>
> split
>
> discovery
>
> is
>
> done by each task individually, then:
>   i) we have to have a deterministic scheme for each
>
> reader to
>
> assign
>
> splits to itself (e.g. mod subtaskId). This is not
>
> necessarily
>
> trivial
>
> for
>
> all sources.
>   ii) each reader would have to keep a copy of all its
>
> processed
>
> slpits
>
>   iii) the state has to be a union state with a
>
> non-trivial
>
> merging
>
> logic
>
> in order to support rescaling.
>
> Two additional points that you raised above:
>
> i) The point that you raised that we need to keep all
>
> splits
>
> (processed
>
> and
>
> not-processed) I think is a bit of a strong
>
> requirement.
>
> This
>
> would
>
> imply
>
> that for infinite sources the state will grow
>
> indefinitely.
>
> This is
>
> problem
>
> is even more pronounced if we do not have a single
>
> source
>
> that
>
> assigns
>
> splits to readers, as each reader will have its own
>
> copy
>
> of
>
> the
>
> state.
>
> ii) it is true that for finite sources we need to
>
> somehow
>
> not
>
> close
>
> the
>
> readers when the source/split discoverer finishes. The
> ContinuousFileReaderOperator has a work-around for
>
> that.
>
> It is
>
> not
>
> elegant,
>
> and checkpoints are not emitted after closing the
>
> source,
>
> but
>
> this, I
>
> believe, is a bigger problem which requires more
>
> changes
>
> than
>
> just
>
> refactoring the source interface.
>
> Cheers,
> Kostas
>
>
>

[dwysakowicz]

Hi Becket,

I am not sure if I understood the last paragraph correctly, but let me clarify my thoughts.

I would not add any bounded/batch specific methods to the DataStream. Imo all the user facing bounded/batch specific methods should be exposed through the new BoundedDataStream interface.

1. Using the source() method would basically mean use the information from Source#getBoundedness in 2(Scheduling) and 3(Operator behaviors). I believe all the unbounded/stream operations can be executed also for a batch stream. In other words the stream/unbounded operations are a subset of the bounded/batch. So I see no problem why it would not be possible to pass a bounded source here if we do not care about bounded specific operations such as e.g. the sort you mentioned.
   
2. Using the continuousSource() method would mean use Boundedness#CONTINUOUS_UNBOUNDED in 2 and 3 independent of what Source#getBoundedness says. <- not sure how useful this method would actually be, imo usually we do want to leverage the boundedness of a source
   
3. Using boundedSource() would:
1. throw and exception if Source#getBoundedness returns Boundedness#CONTINUOUS_UNBOUNDED
2. if Source#getBoundedness returns Boundedness#BOUNDED it is used in 2 and 3 + we expose additional methods in the API as this would return BoundedStream

My main concern was that I think the boundedness should come out of the source rather than from which method on ExecutionEnvironment is used. In general I am also fine with the methods in your original proposal I think though we should have a clear logic what happens if you:

1. pass a bounded source to continuousSource()
2. pass a continuous source to boundedSource()

Plus why should I think about the boundedness twice if I do not care about the additional, bounded-specific methods. Once when instantiating the source (e.g. the example with end timestamp) and second time when creating the DataStream.

Best,

Dawid

On 09/12/2019 13:52, Becket Qin wrote:

Hi Dawid,

Thanks for the comments. This actually brings another relevant question
about what does a "bounded source" imply. I actually had the same
impression when I look at the Source API. Here is what I understand after
some discussion with Stephan. The bounded source has the following impacts.

1. API validity.
- A bounded source generates a bounded stream so some operations that only
works for bounded records would be performed, e.g. sort.
- To expose these bounded stream only APIs, there are two options:
     a. Add them to the DataStream API and throw exception if a method is
called on an unbounded stream.
     b. Create a BoundedDataStream class which is returned from
env.boundedSource(), while DataStream is returned from env.continousSource().
Note that this cannot be done by having single env.source(theSource) even
the Source has a getBoundedness() method.

2. Scheduling
- A bounded source could be computed stage by stage without bringing up all
the tasks at the same time.

3. Operator behaviors
- A bounded source indicates the records are finite so some operators can
wait until it receives all the records before it starts the processing.

In the above impact, only 1 is relevant to the API design. And the current
proposal in FLIP-27 is following 1.b.

// boundedness depends of source property, imo this should always be

preferred

DataStream<MyType> stream = env.source(theSource);


In your proposal, does DataStream have bounded stream only methods? It
looks it should have, otherwise passing a bounded Source to env.source()
would be confusing. In that case, we will essentially do 1.a if an
unbounded Source is created from env.source(unboundedSource).

If we have the methods only supported for bounded streams in DataStream, it
seems a little weird to have a separate BoundedDataStream interface.

Am I understand it correctly?

Thanks,

Jiangjie (Becket) Qin



On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz [hidden email]
wrote:

Hi all,

Really well written proposal and very important one. I must admit I have
not understood all the intricacies of it yet.

One question I have though is about where does the information about
boundedness come from. I think in most cases it is a property of the
source. As you described it might be e.g. end offset, a flag should it
monitor new splits etc. I think it would be a really nice use case to be
able to say:

new KafkaSource().readUntil(long timestamp),

which could work as an "end offset". Moreover I think all Bounded sources
support continuous mode, but no intrinsically continuous source support the
Bounded mode. If I understood the proposal correctly it suggest the
boundedness sort of "comes" from the outside of the source, from the
invokation of either boundedStream or continousSource.

I am wondering if it would make sense to actually change the method

boolean Source#supportsBoundedness(Boundedness)

to

Boundedness Source#getBoundedness().

As for the methods #boundedSource, #continousSource, assuming the
boundedness is property of the source they do not affect how the enumerator
works, but mostly how the dag is scheduled, right? I am not against those
methods, but I think it is a very specific use case to actually override
the property of the source. In general I would expect users to only call
env.source(theSource), where the source tells if it is bounded or not. I
would suggest considering following set of methods:

// boundedness depends of source property, imo this should always be preferred

DataStream<MyType> stream = env.source(theSource);


// always continous execution, whether bounded or unbounded source

DataStream<MyType> boundedStream = env.continousSource(theSource);

// imo this would make sense if the BoundedDataStream provides additional features unavailable for continous mode
BoundedDataStream<MyType> batch = env.boundedSource(theSource);


Best,

Dawid


On 04/12/2019 11:25, Stephan Ewen wrote:

Thanks, Becket, for updating this.

I agree with moving the aspects you mentioned into separate FLIPs - this
one way becoming unwieldy in size.

+1 to the FLIP in its current state. Its a very detailed write-up, nicely
done!

On Wed, Dec 4, 2019 at 7:38 AM Becket Qin [hidden email] [hidden email] wrote:


Hi all,

Sorry for the long belated update. I have updated FLIP-27 wiki page with
the latest proposals. Some noticeable changes include:
1. A new generic communication mechanism between SplitEnumerator and
SourceReader.
2. Some detail API method signature changes.

We left a few things out of this FLIP and will address them in separate
FLIPs. Including:
1. Per split event time.
2. Event time alignment.
3. Fine grained failover for SplitEnumerator failure.

Please let us know if you have any question.

Thanks,

Jiangjie (Becket) Qin

On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen [hidden email] [hidden email] wrote:


Hi  Łukasz!

Becket and me are working hard on figuring out the last details and
implementing the first PoC. We would update the FLIP hopefully next week.

There is a fair chance that a first version of this will be in 1.10, but

I

think it will take another release to battle test it and migrate the
connectors.

Best,
Stephan




On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski [hidden email] [hidden email]

wrote:

Hi,

This proposal looks very promising for us. Do you have any plans in

which

Flink release it is going to be released? We are thinking on using a

Data

Set API for our future use cases but on the other hand Data Set API is
going to be deprecated so using proposed bounded data streams solution
could be more viable in the long term.

Thanks,
Łukasz

On 2019/10/01 15:48:03, Thomas Weise [hidden email] [hidden email] wrote:

Thanks for putting together this proposal!

I see that the "Per Split Event Time" and "Event Time Alignment"

sections

are still TBD.

It would probably be good to flesh those out a bit before proceeding

too

far

as the event time alignment will probably influence the interaction

with

the split reader, specifically ReaderStatus emitNext(SourceOutput<E>
output).

We currently have only one implementation for event time alignment in

the

Kinesis consumer. The synchronization in that case takes place as the

last

step before records are emitted downstream (RecordEmitter). With the
currently proposed interfaces, the equivalent can be implemented in

the

reader loop, although note that in the Kinesis consumer the per shard
threads push records.

Synchronization has not been implemented for the Kafka consumer yet.
https://issues.apache.org/jira/browse/FLINK-12675

When I looked at it, I realized that the implementation will look

quite

different
from Kinesis because it needs to take place in the pull part, where

records

are taken from the Kafka client. Due to the multiplexing it cannot be

done

by blocking the split thread like it currently works for Kinesis.

Reading

from individual Kafka partitions needs to be controlled via

pause/resume

on the Kafka client.

To take on that responsibility the split thread would need to be

aware

of

the
watermarks or at least whether it should or should not continue to

consume

a given split and this may require a different SourceReader or

SourceOutput

interface.

Thanks,
Thomas


On Fri, Jul 26, 2019 at 1:39 AM Biao Liu [hidden email] [hidden email] wrote:


Hi Stephan,

Thank you for feedback!
Will take a look at your branch before public discussing.


On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen [hidden email] [hidden email]

wrote:

Hi Biao!

Thanks for reviving this. I would like to join this discussion,

but

am

quite occupied with the 1.9 release, so can we maybe pause this

discussion

for a week or so?

In the meantime I can share some suggestion based on prior

experiments:

How to do watermarks / timestamp extractors in a simpler and more

flexible

way. I think that part is quite promising should be part of the

new

source

interface.



https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime

https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java

Some experiments on how to build the source reader and its

library

for

common threading/split patterns:



https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src

Best,
Stephan


On Thu, Jul 25, 2019 at 10:03 AM Biao Liu [hidden email] [hidden email]

wrote:

Hi devs,

Since 1.9 is nearly released, I think we could get back to

FLIP-27.

I

believe it should be included in 1.10.

There are so many things mentioned in document of FLIP-27. [1] I

think

we'd better discuss them separately. However the wiki is not a

good

place

to discuss. I wrote google doc about SplitReader API which

misses

some

details in the document. [2]

1.


https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface

2.


https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing

CC Stephan, Aljoscha, Piotrek, Becket


On Thu, Mar 28, 2019 at 4:38 PM Biao Liu [hidden email] [hidden email]

wrote:

Hi Steven,
Thank you for the feedback. Please take a look at the document

FLIP-27

<

https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface

which

is updated recently. A lot of details of enumerator were added

in

this

document. I think it would help.

Steven Wu [hidden email] [hidden email] 于2019年3月28日周四 下午12:52写道：


This proposal mentioned that SplitEnumerator might run on the
JobManager or
in a single task on a TaskManager.

if enumerator is a single task on a taskmanager, then the job

DAG

can

never
been embarrassingly parallel anymore. That will nullify the

leverage

of

fine-grained recovery for embarrassingly parallel jobs.

It's not clear to me what's the implication of running

enumerator

on

the

jobmanager. So I will leave that out for now.

On Mon, Jan 28, 2019 at 3:05 AM Biao Liu [hidden email] [hidden email]

wrote:

Hi Stephan & Piotrek,

Thank you for feedback.

It seems that there are a lot of things to do in community.

I

am

just

afraid that this discussion may be forgotten since there so

many

proposals

recently.
Anyway, wish to see the split topics soon :)

Piotr Nowojski [hidden email] [hidden email] 于2019年1月24日周四

下午8:21写道：

Hi Biao!

This discussion was stalled because of preparations for

the

open

sourcing

& merging Blink. I think before creating the tickets we

should

split this

discussion into topics/areas outlined by Stephan and

create

Flips

for

that.

I think there is no chance for this to be completed in

couple

of

remaining

weeks/1 month before 1.8 feature freeze, however it would

be

good

to aim

with those changes for 1.9.

Piotrek


On 20 Jan 2019, at 16:08, Biao Liu [hidden email] [hidden email]

wrote:

Hi community,
The summary of Stephan makes a lot sense to me. It is

much

clearer

indeed

after splitting the complex topic into small ones.
I was wondering is there any detail plan for next step?

If

not,

I

would

like to push this thing forward by creating some JIRA

issues.

Another question is that should version 1.8 include

these

features?

Stephan Ewen [hidden email] [hidden email] 于2018年12月1日周六 上午4:20写道：


Thanks everyone for the lively discussion. Let me try

to

summarize

where I

see convergence in the discussion and open issues.
I'll try to group this by design aspect of the source.

Please

let me

know

if I got things wrong or missed something crucial here.

For issues 1-3, if the below reflects the state of the

discussion, I

would

try and update the FLIP in the next days.
For the remaining ones we need more discussion.

I would suggest to fork each of these aspects into a

separate

mail

thread,

or will loose sight of the individual aspects.

*(1) Separation of Split Enumerator and Split Reader*

 - All seem to agree this is a good thing
 - Split Enumerator could in the end live on JobManager

(and

assign

splits

via RPC) or in a task (and assign splits via data

streams)

 - this discussion is orthogonal and should come later,

when

the

interface

is agreed upon.

*(2) Split Readers for one or more splits*

 - Discussion seems to agree that we need to support

one

reader

that

possibly handles multiple splits concurrently.
 - The requirement comes from sources where one

poll()-style

call

fetches

data from different splits / partitions
   --> example sources that require that would be for

example

Kafka,

Pravega, Pulsar

 - Could have one split reader per source, or multiple

split

readers

that

share the "poll()" function
 - To not make it too complicated, we can start with

thinking

about

one

split reader for all splits initially and see if that

covers

all

requirements

*(3) Threading model of the Split Reader*

 - Most active part of the discussion ;-)

 - A non-blocking way for Flink's task code to interact

with

the

source

is

needed in order to a task runtime code based on a
single-threaded/actor-style task design
   --> I personally am a big proponent of that, it will

help

with

well-behaved checkpoints, efficiency, and simpler yet

more

robust

runtime

code

 - Users care about simple abstraction, so as a

subclass

of

SplitReader

(non-blocking / async) we need to have a

BlockingSplitReader

which

will

form the basis of most source implementations.

BlockingSplitReader

lets

users do blocking simple poll() calls.
 - The BlockingSplitReader would spawn a thread (or

more)

and

the

thread(s) can make blocking calls and hand over data

buffers

via

a

blocking

queue
 - This should allow us to cover both, a fully async

runtime,

and a

simple

blocking interface for users.
 - This is actually very similar to how the Kafka

connectors

work.

Kafka

9+ with one thread, Kafka 8 with multiple threads

 - On the base SplitReader (the async one), the

non-blocking

method

that

gets the next chunk of data would signal data

availability

via

a

CompletableFuture, because that gives the best

flexibility

(can

await

completion or register notification handlers).
 - The source task would register a "thenHandle()" (or

similar)

on the

future to put a "take next data" task into the

actor-style

mailbox

*(4) Split Enumeration and Assignment*

 - Splits may be generated lazily, both in cases where

there

is a

limited

number of splits (but very many), or splits are

discovered

over

time

 - Assignment should also be lazy, to get better load

balancing

 - Assignment needs support locality preferences

 - Possible design based on discussion so far:

   --> SplitReader has a method "addSplits(SplitT...)"

to

add

one or

more

splits. Some split readers might assume they have only

one

split

ever,

concurrently, others assume multiple splits. (Note:

idea

behind

being

able

to add multiple splits at the same time is to ease

startup

where

multiple

splits may be assigned instantly.)
   --> SplitReader has a context object on which it can

call

indicate

when

splits are completed. The enumerator gets that

notification and

can

use

to

decide when to assign new splits. This should help both

in

cases

of

sources

that take splits lazily (file readers) and in case the

source

needs to

preserve a partial order between splits (Kinesis,

Pravega,

Pulsar may

need

that).
   --> SplitEnumerator gets notification when

SplitReaders

start

and

when

they finish splits. They can decide at that moment to

push

more

splits

to

that reader
   --> The SplitEnumerator should probably be aware of

the

source

parallelism, to build its initial distribution.

 - Open question: Should the source expose something

like

"host

preferences", so that yarn/mesos/k8s can take this into

account

when

selecting a node to start a TM on?

*(5) Watermarks and event time alignment*

 - Watermark generation, as well as idleness, needs to

be

per

split

(like

currently in the Kafka Source, per partition)
 - It is desirable to support optional

event-time-alignment,

meaning

that

splits that are ahead are back-pressured or temporarily

unsubscribed

 - I think i would be desirable to encapsulate

watermark

generation

logic

in watermark generators, for a separation of concerns.

The

watermark

generators should run per split.
 - Using watermark generators would also help with

another

problem of

the

suggested interface, namely supporting non-periodic

watermarks

efficiently.

 - Need a way to "dispatch" next record to different

watermark

generators

 - Need a way to tell SplitReader to "suspend" a split

until a

certain

watermark is reached (event time backpressure)
 - This would in fact be not needed (and thus simpler)

if

we

had

a

SplitReader per split and may be a reason to re-open

that

discussion

*(6) Watermarks across splits and in the Split

Enumerator*

 - The split enumerator may need some watermark

awareness,

which

should

be

purely based on split metadata (like create timestamp

of

file

splits)

 - If there are still more splits with overlapping

event

time

range

for

a

split reader, then that split reader should not advance

the

watermark

within the split beyond the overlap boundary. Otherwise

future

splits

will

produce late data.

 - One way to approach this could be that the split

enumerator

may

send

watermarks to the readers, and the readers cannot emit

watermarks

beyond

that received watermark.
 - Many split enumerators would simply immediately send

Long.MAX

out

and

leave the progress purely to the split readers.

 - For event-time alignment / split back pressure, this

begs

the

question

how we can avoid deadlocks that may arise when splits

are

suspended

for

event time back pressure,

*(7) Batch and streaming Unification*

 - Functionality wise, the above design should support

both

 - Batch often (mostly) does not care about reading "in

order"

and

generating watermarks
   --> Might use different enumerator logic that is

more

locality

aware

and ignores event time order
   --> Does not generate watermarks
 - Would be great if bounded sources could be

identified

at

compile

time,

so that "env.addBoundedSource(...)" is type safe and

can

return a

"BoundedDataStream".
 - Possible to defer this discussion until later

*Miscellaneous Comments*

 - Should the source have a TypeInformation for the

produced

type,

instead

of a serializer? We need a type information in the

stream

anyways, and

can

derive the serializer from that. Plus, creating the

serializer

should

respect the ExecutionConfig.

 - The TypeSerializer interface is very powerful but

also

not

easy to

implement. Its purpose is to handle data super

efficiently,

support

flexible ways of evolution, etc.
 For metadata I would suggest to look at the

SimpleVersionedSerializer

instead, which is used for example for checkpoint

master

hooks,

or for

the

streaming file sink. I think that is is a good match

for

cases

where

we

do

not need more than ser/deser (no copy, etc.) and don't

need to

push

versioning out of the serialization paths for best

performance

(as in

the

TypeSerializer)


On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas [hidden email]
wrote:


Hi Biao,

Thanks for the answer!

So given the multi-threaded readers, now we have as

open

questions:

1) How do we let the checkpoints pass through our

multi-threaded

reader

operator?

2) Do we have separate reader and source operators or

not? In

the

strategy

that has a separate source, the source operator has a

parallelism of

1

and

is responsible for split recovery only.

For the first one, given also the constraints

(blocking,

finite

queues,

etc), I do not have an answer yet.

For the 2nd, I think that we should go with separate

operators

for

the

source and the readers, for the following reasons:

1) This is more aligned with a potential future

improvement

where the

split

discovery becomes a responsibility of the JobManager

and

readers are

pooling more work from the JM.

2) The source is going to be the "single point of

truth".

It

will

know

what

has been processed and what not. If the source and the

readers

are a

single

operator with parallelism > 1, or in general, if the

split

discovery

is

done by each task individually, then:
  i) we have to have a deterministic scheme for each

reader to

assign

splits to itself (e.g. mod subtaskId). This is not

necessarily

trivial

for

all sources.
  ii) each reader would have to keep a copy of all its

processed

slpits

  iii) the state has to be a union state with a

non-trivial

merging

logic

in order to support rescaling.

Two additional points that you raised above:

i) The point that you raised that we need to keep all

splits

(processed

and

not-processed) I think is a bit of a strong

requirement.

This

would

imply

that for infinite sources the state will grow

indefinitely.

This is

problem

is even more pronounced if we do not have a single

source

that

assigns

splits to readers, as each reader will have its own

copy

of

the

state.

ii) it is true that for finite sources we need to

somehow

not

close

the

readers when the source/split discoverer finishes. The
ContinuousFileReaderOperator has a work-around for

that.

It is

not

elegant,

and checkpoints are not emitted after closing the

source,

but

this, I

believe, is a bigger problem which requires more

changes

than

just

refactoring the source interface.

Cheers,
Kostas

[dwysakowicz]

One more thing. In the current proposal, with the
supportsBoundedness(Boundedness) method and the boundedness coming from
either continuousSource or boundedSource I could not find how this
information is fed back to the SplitEnumerator.

Best,

Dawid

On 09/12/2019 13:52, Becket Qin wrote:

> Hi Dawid,
>
> Thanks for the comments. This actually brings another relevant question
> about what does a "bounded source" imply. I actually had the same
> impression when I look at the Source API. Here is what I understand after
> some discussion with Stephan. The bounded source has the following impacts.
>
> 1. API validity.
> - A bounded source generates a bounded stream so some operations that only
> works for bounded records would be performed, e.g. sort.
> - To expose these bounded stream only APIs, there are two options:
>      a. Add them to the DataStream API and throw exception if a method is
> called on an unbounded stream.
>      b. Create a BoundedDataStream class which is returned from
> env.boundedSource(), while DataStream is returned from env.continousSource().
> Note that this cannot be done by having single env.source(theSource) even
> the Source has a getBoundedness() method.
>
> 2. Scheduling
> - A bounded source could be computed stage by stage without bringing up all
> the tasks at the same time.
>
> 3. Operator behaviors
> - A bounded source indicates the records are finite so some operators can
> wait until it receives all the records before it starts the processing.
>
> In the above impact, only 1 is relevant to the API design. And the current
> proposal in FLIP-27 is following 1.b.
>
> // boundedness depends of source property, imo this should always be
>> preferred
>>
>
> DataStream<MyType> stream = env.source(theSource);
>
>
> In your proposal, does DataStream have bounded stream only methods? It
> looks it should have, otherwise passing a bounded Source to env.source()
> would be confusing. In that case, we will essentially do 1.a if an
> unbounded Source is created from env.source(unboundedSource).
>
> If we have the methods only supported for bounded streams in DataStream, it
> seems a little weird to have a separate BoundedDataStream interface.
>
> Am I understand it correctly?
>
> Thanks,
>
> Jiangjie (Becket) Qin
>
>
>
> On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <[hidden email]>
> wrote:
>
>> Hi all,
>>
>> Really well written proposal and very important one. I must admit I have
>> not understood all the intricacies of it yet.
>>
>> One question I have though is about where does the information about
>> boundedness come from. I think in most cases it is a property of the
>> source. As you described it might be e.g. end offset, a flag should it
>> monitor new splits etc. I think it would be a really nice use case to be
>> able to say:
>>
>> new KafkaSource().readUntil(long timestamp),
>>
>> which could work as an "end offset". Moreover I think all Bounded sources
>> support continuous mode, but no intrinsically continuous source support the
>> Bounded mode. If I understood the proposal correctly it suggest the
>> boundedness sort of "comes" from the outside of the source, from the
>> invokation of either boundedStream or continousSource.
>>
>> I am wondering if it would make sense to actually change the method
>>
>> boolean Source#supportsBoundedness(Boundedness)
>>
>> to
>>
>> Boundedness Source#getBoundedness().
>>
>> As for the methods #boundedSource, #continousSource, assuming the
>> boundedness is property of the source they do not affect how the enumerator
>> works, but mostly how the dag is scheduled, right? I am not against those
>> methods, but I think it is a very specific use case to actually override
>> the property of the source. In general I would expect users to only call
>> env.source(theSource), where the source tells if it is bounded or not. I
>> would suggest considering following set of methods:
>>
>> // boundedness depends of source property, imo this should always be preferred
>>
>> DataStream<MyType> stream = env.source(theSource);
>>
>>
>> // always continous execution, whether bounded or unbounded source
>>
>> DataStream<MyType> boundedStream = env.continousSource(theSource);
>>
>> // imo this would make sense if the BoundedDataStream provides additional features unavailable for continous mode
>> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
>>
>>
>> Best,
>>
>> Dawid
>>
>>
>> On 04/12/2019 11:25, Stephan Ewen wrote:
>>
>> Thanks, Becket, for updating this.
>>
>> I agree with moving the aspects you mentioned into separate FLIPs - this
>> one way becoming unwieldy in size.
>>
>> +1 to the FLIP in its current state. Its a very detailed write-up, nicely
>> done!
>>
>> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]> <[hidden email]> wrote:
>>
>>
>> Hi all,
>>
>> Sorry for the long belated update. I have updated FLIP-27 wiki page with
>> the latest proposals. Some noticeable changes include:
>> 1. A new generic communication mechanism between SplitEnumerator and
>> SourceReader.
>> 2. Some detail API method signature changes.
>>
>> We left a few things out of this FLIP and will address them in separate
>> FLIPs. Including:
>> 1. Per split event time.
>> 2. Event time alignment.
>> 3. Fine grained failover for SplitEnumerator failure.
>>
>> Please let us know if you have any question.
>>
>> Thanks,
>>
>> Jiangjie (Becket) Qin
>>
>> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]> <[hidden email]> wrote:
>>
>>
>> Hi  Łukasz!
>>
>> Becket and me are working hard on figuring out the last details and
>> implementing the first PoC. We would update the FLIP hopefully next week.
>>
>> There is a fair chance that a first version of this will be in 1.10, but
>>
>> I
>>
>> think it will take another release to battle test it and migrate the
>> connectors.
>>
>> Best,
>> Stephan
>>
>>
>>
>>
>> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <[hidden email]> <[hidden email]>
>>
>> wrote:
>>
>> Hi,
>>
>> This proposal looks very promising for us. Do you have any plans in
>>
>> which
>>
>> Flink release it is going to be released? We are thinking on using a
>>
>> Data
>>
>> Set API for our future use cases but on the other hand Data Set API is
>> going to be deprecated so using proposed bounded data streams solution
>> could be more viable in the long term.
>>
>> Thanks,
>> Łukasz
>>
>> On 2019/10/01 15:48:03, Thomas Weise <[hidden email]> <[hidden email]> wrote:
>>
>> Thanks for putting together this proposal!
>>
>> I see that the "Per Split Event Time" and "Event Time Alignment"
>>
>> sections
>>
>> are still TBD.
>>
>> It would probably be good to flesh those out a bit before proceeding
>>
>> too
>>
>> far
>>
>> as the event time alignment will probably influence the interaction
>>
>> with
>>
>> the split reader, specifically ReaderStatus emitNext(SourceOutput<E>
>> output).
>>
>> We currently have only one implementation for event time alignment in
>>
>> the
>>
>> Kinesis consumer. The synchronization in that case takes place as the
>>
>> last
>>
>> step before records are emitted downstream (RecordEmitter). With the
>> currently proposed interfaces, the equivalent can be implemented in
>>
>> the
>>
>> reader loop, although note that in the Kinesis consumer the per shard
>> threads push records.
>>
>> Synchronization has not been implemented for the Kafka consumer yet.
>> https://issues.apache.org/jira/browse/FLINK-12675
>>
>> When I looked at it, I realized that the implementation will look
>>
>> quite
>>
>> different
>> from Kinesis because it needs to take place in the pull part, where
>>
>> records
>>
>> are taken from the Kafka client. Due to the multiplexing it cannot be
>>
>> done
>>
>> by blocking the split thread like it currently works for Kinesis.
>>
>> Reading
>>
>> from individual Kafka partitions needs to be controlled via
>>
>> pause/resume
>>
>> on the Kafka client.
>>
>> To take on that responsibility the split thread would need to be
>>
>> aware
>>
>> of
>>
>> the
>> watermarks or at least whether it should or should not continue to
>>
>> consume
>>
>> a given split and this may require a different SourceReader or
>>
>> SourceOutput
>>
>> interface.
>>
>> Thanks,
>> Thomas
>>
>>
>> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email]> <[hidden email]> wrote:
>>
>>
>> Hi Stephan,
>>
>> Thank you for feedback!
>> Will take a look at your branch before public discussing.
>>
>>
>> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]> <[hidden email]>
>>
>> wrote:
>>
>> Hi Biao!
>>
>> Thanks for reviving this. I would like to join this discussion,
>>
>> but
>>
>> am
>>
>> quite occupied with the 1.9 release, so can we maybe pause this
>>
>> discussion
>>
>> for a week or so?
>>
>> In the meantime I can share some suggestion based on prior
>>
>> experiments:
>>
>> How to do watermarks / timestamp extractors in a simpler and more
>>
>> flexible
>>
>> way. I think that part is quite promising should be part of the
>>
>> new
>>
>> source
>>
>> interface.
>>
>>
>>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
>>
>> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
>>
>> Some experiments on how to build the source reader and its
>>
>> library
>>
>> for
>>
>> common threading/split patterns:
>>
>>
>>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
>>
>> Best,
>> Stephan
>>
>>
>> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]> <[hidden email]>
>>
>> wrote:
>>
>> Hi devs,
>>
>> Since 1.9 is nearly released, I think we could get back to
>>
>> FLIP-27.
>>
>> I
>>
>> believe it should be included in 1.10.
>>
>> There are so many things mentioned in document of FLIP-27. [1] I
>>
>> think
>>
>> we'd better discuss them separately. However the wiki is not a
>>
>> good
>>
>> place
>>
>> to discuss. I wrote google doc about SplitReader API which
>>
>> misses
>>
>> some
>>
>> details in the document. [2]
>>
>> 1.
>>
>>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
>>
>> 2.
>>
>>
>> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
>>
>> CC Stephan, Aljoscha, Piotrek, Becket
>>
>>
>> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email]> <[hidden email]>
>>
>> wrote:
>>
>> Hi Steven,
>> Thank you for the feedback. Please take a look at the document
>>
>> FLIP-27
>>
>> <
>>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
>>
>> which
>>
>> is updated recently. A lot of details of enumerator were added
>>
>> in
>>
>> this
>>
>> document. I think it would help.
>>
>> Steven Wu <[hidden email]> <[hidden email]> 于2019年3月28日周四 下午12:52写道：
>>
>>
>> This proposal mentioned that SplitEnumerator might run on the
>> JobManager or
>> in a single task on a TaskManager.
>>
>> if enumerator is a single task on a taskmanager, then the job
>>
>> DAG
>>
>> can
>>
>> never
>> been embarrassingly parallel anymore. That will nullify the
>>
>> leverage
>>
>> of
>>
>> fine-grained recovery for embarrassingly parallel jobs.
>>
>> It's not clear to me what's the implication of running
>>
>> enumerator
>>
>> on
>>
>> the
>>
>> jobmanager. So I will leave that out for now.
>>
>> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email]> <[hidden email]>
>>
>> wrote:
>>
>> Hi Stephan & Piotrek,
>>
>> Thank you for feedback.
>>
>> It seems that there are a lot of things to do in community.
>>
>> I
>>
>> am
>>
>> just
>>
>> afraid that this discussion may be forgotten since there so
>>
>> many
>>
>> proposals
>>
>> recently.
>> Anyway, wish to see the split topics soon :)
>>
>> Piotr Nowojski <[hidden email]> <[hidden email]> 于2019年1月24日周四
>>
>> 下午8:21写道：
>>
>> Hi Biao!
>>
>> This discussion was stalled because of preparations for
>>
>> the
>>
>> open
>>
>> sourcing
>>
>> & merging Blink. I think before creating the tickets we
>>
>> should
>>
>> split this
>>
>> discussion into topics/areas outlined by Stephan and
>>
>> create
>>
>> Flips
>>
>> for
>>
>> that.
>>
>> I think there is no chance for this to be completed in
>>
>> couple
>>
>> of
>>
>> remaining
>>
>> weeks/1 month before 1.8 feature freeze, however it would
>>
>> be
>>
>> good
>>
>> to aim
>>
>> with those changes for 1.9.
>>
>> Piotrek
>>
>>
>> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email]> <[hidden email]>
>>
>> wrote:
>>
>> Hi community,
>> The summary of Stephan makes a lot sense to me. It is
>>
>> much
>>
>> clearer
>>
>> indeed
>>
>> after splitting the complex topic into small ones.
>> I was wondering is there any detail plan for next step?
>>
>> If
>>
>> not,
>>
>> I
>>
>> would
>>
>> like to push this thing forward by creating some JIRA
>>
>> issues.
>>
>> Another question is that should version 1.8 include
>>
>> these
>>
>> features?
>>
>> Stephan Ewen <[hidden email]> <[hidden email]> 于2018年12月1日周六 上午4:20写道：
>>
>>
>> Thanks everyone for the lively discussion. Let me try
>>
>> to
>>
>> summarize
>>
>> where I
>>
>> see convergence in the discussion and open issues.
>> I'll try to group this by design aspect of the source.
>>
>> Please
>>
>> let me
>>
>> know
>>
>> if I got things wrong or missed something crucial here.
>>
>> For issues 1-3, if the below reflects the state of the
>>
>> discussion, I
>>
>> would
>>
>> try and update the FLIP in the next days.
>> For the remaining ones we need more discussion.
>>
>> I would suggest to fork each of these aspects into a
>>
>> separate
>>
>> mail
>>
>> thread,
>>
>> or will loose sight of the individual aspects.
>>
>> *(1) Separation of Split Enumerator and Split Reader*
>>
>>  - All seem to agree this is a good thing
>>  - Split Enumerator could in the end live on JobManager
>>
>> (and
>>
>> assign
>>
>> splits
>>
>> via RPC) or in a task (and assign splits via data
>>
>> streams)
>>
>>  - this discussion is orthogonal and should come later,
>>
>> when
>>
>> the
>>
>> interface
>>
>> is agreed upon.
>>
>> *(2) Split Readers for one or more splits*
>>
>>  - Discussion seems to agree that we need to support
>>
>> one
>>
>> reader
>>
>> that
>>
>> possibly handles multiple splits concurrently.
>>  - The requirement comes from sources where one
>>
>> poll()-style
>>
>> call
>>
>> fetches
>>
>> data from different splits / partitions
>>    --> example sources that require that would be for
>>
>> example
>>
>> Kafka,
>>
>> Pravega, Pulsar
>>
>>  - Could have one split reader per source, or multiple
>>
>> split
>>
>> readers
>>
>> that
>>
>> share the "poll()" function
>>  - To not make it too complicated, we can start with
>>
>> thinking
>>
>> about
>>
>> one
>>
>> split reader for all splits initially and see if that
>>
>> covers
>>
>> all
>>
>> requirements
>>
>> *(3) Threading model of the Split Reader*
>>
>>  - Most active part of the discussion ;-)
>>
>>  - A non-blocking way for Flink's task code to interact
>>
>> with
>>
>> the
>>
>> source
>>
>> is
>>
>> needed in order to a task runtime code based on a
>> single-threaded/actor-style task design
>>    --> I personally am a big proponent of that, it will
>>
>> help
>>
>> with
>>
>> well-behaved checkpoints, efficiency, and simpler yet
>>
>> more
>>
>> robust
>>
>> runtime
>>
>> code
>>
>>  - Users care about simple abstraction, so as a
>>
>> subclass
>>
>> of
>>
>> SplitReader
>>
>> (non-blocking / async) we need to have a
>>
>> BlockingSplitReader
>>
>> which
>>
>> will
>>
>> form the basis of most source implementations.
>>
>> BlockingSplitReader
>>
>> lets
>>
>> users do blocking simple poll() calls.
>>  - The BlockingSplitReader would spawn a thread (or
>>
>> more)
>>
>> and
>>
>> the
>>
>> thread(s) can make blocking calls and hand over data
>>
>> buffers
>>
>> via
>>
>> a
>>
>> blocking
>>
>> queue
>>  - This should allow us to cover both, a fully async
>>
>> runtime,
>>
>> and a
>>
>> simple
>>
>> blocking interface for users.
>>  - This is actually very similar to how the Kafka
>>
>> connectors
>>
>> work.
>>
>> Kafka
>>
>> 9+ with one thread, Kafka 8 with multiple threads
>>
>>  - On the base SplitReader (the async one), the
>>
>> non-blocking
>>
>> method
>>
>> that
>>
>> gets the next chunk of data would signal data
>>
>> availability
>>
>> via
>>
>> a
>>
>> CompletableFuture, because that gives the best
>>
>> flexibility
>>
>> (can
>>
>> await
>>
>> completion or register notification handlers).
>>  - The source task would register a "thenHandle()" (or
>>
>> similar)
>>
>> on the
>>
>> future to put a "take next data" task into the
>>
>> actor-style
>>
>> mailbox
>>
>> *(4) Split Enumeration and Assignment*
>>
>>  - Splits may be generated lazily, both in cases where
>>
>> there
>>
>> is a
>>
>> limited
>>
>> number of splits (but very many), or splits are
>>
>> discovered
>>
>> over
>>
>> time
>>
>>  - Assignment should also be lazy, to get better load
>>
>> balancing
>>
>>  - Assignment needs support locality preferences
>>
>>  - Possible design based on discussion so far:
>>
>>    --> SplitReader has a method "addSplits(SplitT...)"
>>
>> to
>>
>> add
>>
>> one or
>>
>> more
>>
>> splits. Some split readers might assume they have only
>>
>> one
>>
>> split
>>
>> ever,
>>
>> concurrently, others assume multiple splits. (Note:
>>
>> idea
>>
>> behind
>>
>> being
>>
>> able
>>
>> to add multiple splits at the same time is to ease
>>
>> startup
>>
>> where
>>
>> multiple
>>
>> splits may be assigned instantly.)
>>    --> SplitReader has a context object on which it can
>>
>> call
>>
>> indicate
>>
>> when
>>
>> splits are completed. The enumerator gets that
>>
>> notification and
>>
>> can
>>
>> use
>>
>> to
>>
>> decide when to assign new splits. This should help both
>>
>> in
>>
>> cases
>>
>> of
>>
>> sources
>>
>> that take splits lazily (file readers) and in case the
>>
>> source
>>
>> needs to
>>
>> preserve a partial order between splits (Kinesis,
>>
>> Pravega,
>>
>> Pulsar may
>>
>> need
>>
>> that).
>>    --> SplitEnumerator gets notification when
>>
>> SplitReaders
>>
>> start
>>
>> and
>>
>> when
>>
>> they finish splits. They can decide at that moment to
>>
>> push
>>
>> more
>>
>> splits
>>
>> to
>>
>> that reader
>>    --> The SplitEnumerator should probably be aware of
>>
>> the
>>
>> source
>>
>> parallelism, to build its initial distribution.
>>
>>  - Open question: Should the source expose something
>>
>> like
>>
>> "host
>>
>> preferences", so that yarn/mesos/k8s can take this into
>>
>> account
>>
>> when
>>
>> selecting a node to start a TM on?
>>
>> *(5) Watermarks and event time alignment*
>>
>>  - Watermark generation, as well as idleness, needs to
>>
>> be
>>
>> per
>>
>> split
>>
>> (like
>>
>> currently in the Kafka Source, per partition)
>>  - It is desirable to support optional
>>
>> event-time-alignment,
>>
>> meaning
>>
>> that
>>
>> splits that are ahead are back-pressured or temporarily
>>
>> unsubscribed
>>
>>  - I think i would be desirable to encapsulate
>>
>> watermark
>>
>> generation
>>
>> logic
>>
>> in watermark generators, for a separation of concerns.
>>
>> The
>>
>> watermark
>>
>> generators should run per split.
>>  - Using watermark generators would also help with
>>
>> another
>>
>> problem of
>>
>> the
>>
>> suggested interface, namely supporting non-periodic
>>
>> watermarks
>>
>> efficiently.
>>
>>  - Need a way to "dispatch" next record to different
>>
>> watermark
>>
>> generators
>>
>>  - Need a way to tell SplitReader to "suspend" a split
>>
>> until a
>>
>> certain
>>
>> watermark is reached (event time backpressure)
>>  - This would in fact be not needed (and thus simpler)
>>
>> if
>>
>> we
>>
>> had
>>
>> a
>>
>> SplitReader per split and may be a reason to re-open
>>
>> that
>>
>> discussion
>>
>> *(6) Watermarks across splits and in the Split
>>
>> Enumerator*
>>
>>  - The split enumerator may need some watermark
>>
>> awareness,
>>
>> which
>>
>> should
>>
>> be
>>
>> purely based on split metadata (like create timestamp
>>
>> of
>>
>> file
>>
>> splits)
>>
>>  - If there are still more splits with overlapping
>>
>> event
>>
>> time
>>
>> range
>>
>> for
>>
>> a
>>
>> split reader, then that split reader should not advance
>>
>> the
>>
>> watermark
>>
>> within the split beyond the overlap boundary. Otherwise
>>
>> future
>>
>> splits
>>
>> will
>>
>> produce late data.
>>
>>  - One way to approach this could be that the split
>>
>> enumerator
>>
>> may
>>
>> send
>>
>> watermarks to the readers, and the readers cannot emit
>>
>> watermarks
>>
>> beyond
>>
>> that received watermark.
>>  - Many split enumerators would simply immediately send
>>
>> Long.MAX
>>
>> out
>>
>> and
>>
>> leave the progress purely to the split readers.
>>
>>  - For event-time alignment / split back pressure, this
>>
>> begs
>>
>> the
>>
>> question
>>
>> how we can avoid deadlocks that may arise when splits
>>
>> are
>>
>> suspended
>>
>> for
>>
>> event time back pressure,
>>
>> *(7) Batch and streaming Unification*
>>
>>  - Functionality wise, the above design should support
>>
>> both
>>
>>  - Batch often (mostly) does not care about reading "in
>>
>> order"
>>
>> and
>>
>> generating watermarks
>>    --> Might use different enumerator logic that is
>>
>> more
>>
>> locality
>>
>> aware
>>
>> and ignores event time order
>>    --> Does not generate watermarks
>>  - Would be great if bounded sources could be
>>
>> identified
>>
>> at
>>
>> compile
>>
>> time,
>>
>> so that "env.addBoundedSource(...)" is type safe and
>>
>> can
>>
>> return a
>>
>> "BoundedDataStream".
>>  - Possible to defer this discussion until later
>>
>> *Miscellaneous Comments*
>>
>>  - Should the source have a TypeInformation for the
>>
>> produced
>>
>> type,
>>
>> instead
>>
>> of a serializer? We need a type information in the
>>
>> stream
>>
>> anyways, and
>>
>> can
>>
>> derive the serializer from that. Plus, creating the
>>
>> serializer
>>
>> should
>>
>> respect the ExecutionConfig.
>>
>>  - The TypeSerializer interface is very powerful but
>>
>> also
>>
>> not
>>
>> easy to
>>
>> implement. Its purpose is to handle data super
>>
>> efficiently,
>>
>> support
>>
>> flexible ways of evolution, etc.
>>  For metadata I would suggest to look at the
>>
>> SimpleVersionedSerializer
>>
>> instead, which is used for example for checkpoint
>>
>> master
>>
>> hooks,
>>
>> or for
>>
>> the
>>
>> streaming file sink. I think that is is a good match
>>
>> for
>>
>> cases
>>
>> where
>>
>> we
>>
>> do
>>
>> not need more than ser/deser (no copy, etc.) and don't
>>
>> need to
>>
>> push
>>
>> versioning out of the serialization paths for best
>>
>> performance
>>
>> (as in
>>
>> the
>>
>> TypeSerializer)
>>
>>
>> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <[hidden email]>
>> wrote:
>>
>>
>> Hi Biao,
>>
>> Thanks for the answer!
>>
>> So given the multi-threaded readers, now we have as
>>
>> open
>>
>> questions:
>>
>> 1) How do we let the checkpoints pass through our
>>
>> multi-threaded
>>
>> reader
>>
>> operator?
>>
>> 2) Do we have separate reader and source operators or
>>
>> not? In
>>
>> the
>>
>> strategy
>>
>> that has a separate source, the source operator has a
>>
>> parallelism of
>>
>> 1
>>
>> and
>>
>> is responsible for split recovery only.
>>
>> For the first one, given also the constraints
>>
>> (blocking,
>>
>> finite
>>
>> queues,
>>
>> etc), I do not have an answer yet.
>>
>> For the 2nd, I think that we should go with separate
>>
>> operators
>>
>> for
>>
>> the
>>
>> source and the readers, for the following reasons:
>>
>> 1) This is more aligned with a potential future
>>
>> improvement
>>
>> where the
>>
>> split
>>
>> discovery becomes a responsibility of the JobManager
>>
>> and
>>
>> readers are
>>
>> pooling more work from the JM.
>>
>> 2) The source is going to be the "single point of
>>
>> truth".
>>
>> It
>>
>> will
>>
>> know
>>
>> what
>>
>> has been processed and what not. If the source and the
>>
>> readers
>>
>> are a
>>
>> single
>>
>> operator with parallelism > 1, or in general, if the
>>
>> split
>>
>> discovery
>>
>> is
>>
>> done by each task individually, then:
>>   i) we have to have a deterministic scheme for each
>>
>> reader to
>>
>> assign
>>
>> splits to itself (e.g. mod subtaskId). This is not
>>
>> necessarily
>>
>> trivial
>>
>> for
>>
>> all sources.
>>   ii) each reader would have to keep a copy of all its
>>
>> processed
>>
>> slpits
>>
>>   iii) the state has to be a union state with a
>>
>> non-trivial
>>
>> merging
>>
>> logic
>>
>> in order to support rescaling.
>>
>> Two additional points that you raised above:
>>
>> i) The point that you raised that we need to keep all
>>
>> splits
>>
>> (processed
>>
>> and
>>
>> not-processed) I think is a bit of a strong
>>
>> requirement.
>>
>> This
>>
>> would
>>
>> imply
>>
>> that for infinite sources the state will grow
>>
>> indefinitely.
>>
>> This is
>>
>> problem
>>
>> is even more pronounced if we do not have a single
>>
>> source
>>
>> that
>>
>> assigns
>>
>> splits to readers, as each reader will have its own
>>
>> copy
>>
>> of
>>
>> the
>>
>> state.
>>
>> ii) it is true that for finite sources we need to
>>
>> somehow
>>
>> not
>>
>> close
>>
>> the
>>
>> readers when the source/split discoverer finishes. The
>> ContinuousFileReaderOperator has a work-around for
>>
>> that.
>>
>> It is
>>
>> not
>>
>> elegant,
>>
>> and checkpoints are not emitted after closing the
>>
>> source,
>>
>> but
>>
>> this, I
>>
>> believe, is a bigger problem which requires more
>>
>> changes
>>
>> than
>>
>> just
>>
>> refactoring the source interface.
>>
>> Cheers,
>> Kostas
>>
>>
>>

[Jark Wu-2]

I agree with Dawid's point that the boundedness information should come
from the source itself (e.g. the end timestamp), not through
env.boundedSouce()/continuousSource().
I think if we want to support something like `env.source()` that derive the
execution mode from source, `supportsBoundedness(Boundedness)`
method is not enough, because we don't know whether it is bounded or not.

Best,
Jark


On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <[hidden email]>
wrote:

> One more thing. In the current proposal, with the
> supportsBoundedness(Boundedness) method and the boundedness coming from
> either continuousSource or boundedSource I could not find how this
> information is fed back to the SplitEnumerator.
>
> Best,
>
> Dawid
>
> On 09/12/2019 13:52, Becket Qin wrote:
> > Hi Dawid,
> >
> > Thanks for the comments. This actually brings another relevant question
> > about what does a "bounded source" imply. I actually had the same
> > impression when I look at the Source API. Here is what I understand after
> > some discussion with Stephan. The bounded source has the following
> impacts.
> >
> > 1. API validity.
> > - A bounded source generates a bounded stream so some operations that
> only
> > works for bounded records would be performed, e.g. sort.
> > - To expose these bounded stream only APIs, there are two options:
> >      a. Add them to the DataStream API and throw exception if a method is
> > called on an unbounded stream.
> >      b. Create a BoundedDataStream class which is returned from
> > env.boundedSource(), while DataStream is returned from
> env.continousSource().
> > Note that this cannot be done by having single env.source(theSource) even
> > the Source has a getBoundedness() method.
> >
> > 2. Scheduling
> > - A bounded source could be computed stage by stage without bringing up
> all
> > the tasks at the same time.
> >
> > 3. Operator behaviors
> > - A bounded source indicates the records are finite so some operators can
> > wait until it receives all the records before it starts the processing.
> >
> > In the above impact, only 1 is relevant to the API design. And the
> current
> > proposal in FLIP-27 is following 1.b.
> >
> > // boundedness depends of source property, imo this should always be
> >> preferred
> >>
> >
> > DataStream<MyType> stream = env.source(theSource);
> >
> >
> > In your proposal, does DataStream have bounded stream only methods? It
> > looks it should have, otherwise passing a bounded Source to env.source()
> > would be confusing. In that case, we will essentially do 1.a if an
> > unbounded Source is created from env.source(unboundedSource).
> >
> > If we have the methods only supported for bounded streams in DataStream,
> it
> > seems a little weird to have a separate BoundedDataStream interface.
> >
> > Am I understand it correctly?
> >
> > Thanks,
> >
> > Jiangjie (Becket) Qin
> >
> >
> >
> > On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <[hidden email]>
> > wrote:
> >
> >> Hi all,
> >>
> >> Really well written proposal and very important one. I must admit I have
> >> not understood all the intricacies of it yet.
> >>
> >> One question I have though is about where does the information about
> >> boundedness come from. I think in most cases it is a property of the
> >> source. As you described it might be e.g. end offset, a flag should it
> >> monitor new splits etc. I think it would be a really nice use case to be
> >> able to say:
> >>
> >> new KafkaSource().readUntil(long timestamp),
> >>
> >> which could work as an "end offset". Moreover I think all Bounded
> sources
> >> support continuous mode, but no intrinsically continuous source support
> the
> >> Bounded mode. If I understood the proposal correctly it suggest the
> >> boundedness sort of "comes" from the outside of the source, from the
> >> invokation of either boundedStream or continousSource.
> >>
> >> I am wondering if it would make sense to actually change the method
> >>
> >> boolean Source#supportsBoundedness(Boundedness)
> >>
> >> to
> >>
> >> Boundedness Source#getBoundedness().
> >>
> >> As for the methods #boundedSource, #continousSource, assuming the
> >> boundedness is property of the source they do not affect how the
> enumerator
> >> works, but mostly how the dag is scheduled, right? I am not against
> those
> >> methods, but I think it is a very specific use case to actually override
> >> the property of the source. In general I would expect users to only call
> >> env.source(theSource), where the source tells if it is bounded or not. I
> >> would suggest considering following set of methods:
> >>
> >> // boundedness depends of source property, imo this should always be
> preferred
> >>
> >> DataStream<MyType> stream = env.source(theSource);
> >>
> >>
> >> // always continous execution, whether bounded or unbounded source
> >>
> >> DataStream<MyType> boundedStream = env.continousSource(theSource);
> >>
> >> // imo this would make sense if the BoundedDataStream provides
> additional features unavailable for continous mode
> >> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
> >>
> >>
> >> Best,
> >>
> >> Dawid
> >>
> >>
> >> On 04/12/2019 11:25, Stephan Ewen wrote:
> >>
> >> Thanks, Becket, for updating this.
> >>
> >> I agree with moving the aspects you mentioned into separate FLIPs - this
> >> one way becoming unwieldy in size.
> >>
> >> +1 to the FLIP in its current state. Its a very detailed write-up,
> nicely
> >> done!
> >>
> >> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]> <
> [hidden email]> wrote:
> >>
> >>
> >> Hi all,
> >>
> >> Sorry for the long belated update. I have updated FLIP-27 wiki page with
> >> the latest proposals. Some noticeable changes include:
> >> 1. A new generic communication mechanism between SplitEnumerator and
> >> SourceReader.
> >> 2. Some detail API method signature changes.
> >>
> >> We left a few things out of this FLIP and will address them in separate
> >> FLIPs. Including:
> >> 1. Per split event time.
> >> 2. Event time alignment.
> >> 3. Fine grained failover for SplitEnumerator failure.
> >>
> >> Please let us know if you have any question.
> >>
> >> Thanks,
> >>
> >> Jiangjie (Becket) Qin
> >>
> >> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]> <
> [hidden email]> wrote:
> >>
> >>
> >> Hi  Łukasz!
> >>
> >> Becket and me are working hard on figuring out the last details and
> >> implementing the first PoC. We would update the FLIP hopefully next
> week.
> >>
> >> There is a fair chance that a first version of this will be in 1.10, but
> >>
> >> I
> >>
> >> think it will take another release to battle test it and migrate the
> >> connectors.
> >>
> >> Best,
> >> Stephan
> >>
> >>
> >>
> >>
> >> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <[hidden email]> <
> [hidden email]>
> >>
> >> wrote:
> >>
> >> Hi,
> >>
> >> This proposal looks very promising for us. Do you have any plans in
> >>
> >> which
> >>
> >> Flink release it is going to be released? We are thinking on using a
> >>
> >> Data
> >>
> >> Set API for our future use cases but on the other hand Data Set API is
> >> going to be deprecated so using proposed bounded data streams solution
> >> could be more viable in the long term.
> >>
> >> Thanks,
> >> Łukasz
> >>
> >> On 2019/10/01 15:48:03, Thomas Weise <[hidden email]> <
> [hidden email]> wrote:
> >>
> >> Thanks for putting together this proposal!
> >>
> >> I see that the "Per Split Event Time" and "Event Time Alignment"
> >>
> >> sections
> >>
> >> are still TBD.
> >>
> >> It would probably be good to flesh those out a bit before proceeding
> >>
> >> too
> >>
> >> far
> >>
> >> as the event time alignment will probably influence the interaction
> >>
> >> with
> >>
> >> the split reader, specifically ReaderStatus emitNext(SourceOutput<E>
> >> output).
> >>
> >> We currently have only one implementation for event time alignment in
> >>
> >> the
> >>
> >> Kinesis consumer. The synchronization in that case takes place as the
> >>
> >> last
> >>
> >> step before records are emitted downstream (RecordEmitter). With the
> >> currently proposed interfaces, the equivalent can be implemented in
> >>
> >> the
> >>
> >> reader loop, although note that in the Kinesis consumer the per shard
> >> threads push records.
> >>
> >> Synchronization has not been implemented for the Kafka consumer yet.
> >> https://issues.apache.org/jira/browse/FLINK-12675
> >>
> >> When I looked at it, I realized that the implementation will look
> >>
> >> quite
> >>
> >> different
> >> from Kinesis because it needs to take place in the pull part, where
> >>
> >> records
> >>
> >> are taken from the Kafka client. Due to the multiplexing it cannot be
> >>
> >> done
> >>
> >> by blocking the split thread like it currently works for Kinesis.
> >>
> >> Reading
> >>
> >> from individual Kafka partitions needs to be controlled via
> >>
> >> pause/resume
> >>
> >> on the Kafka client.
> >>
> >> To take on that responsibility the split thread would need to be
> >>
> >> aware
> >>
> >> of
> >>
> >> the
> >> watermarks or at least whether it should or should not continue to
> >>
> >> consume
> >>
> >> a given split and this may require a different SourceReader or
> >>
> >> SourceOutput
> >>
> >> interface.
> >>
> >> Thanks,
> >> Thomas
> >>
> >>
> >> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email]> <
> [hidden email]> wrote:
> >>
> >>
> >> Hi Stephan,
> >>
> >> Thank you for feedback!
> >> Will take a look at your branch before public discussing.
> >>
> >>
> >> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]> <
> [hidden email]>
> >>
> >> wrote:
> >>
> >> Hi Biao!
> >>
> >> Thanks for reviving this. I would like to join this discussion,
> >>
> >> but
> >>
> >> am
> >>
> >> quite occupied with the 1.9 release, so can we maybe pause this
> >>
> >> discussion
> >>
> >> for a week or so?
> >>
> >> In the meantime I can share some suggestion based on prior
> >>
> >> experiments:
> >>
> >> How to do watermarks / timestamp extractors in a simpler and more
> >>
> >> flexible
> >>
> >> way. I think that part is quite promising should be part of the
> >>
> >> new
> >>
> >> source
> >>
> >> interface.
> >>
> >>
> >>
> >>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> >>
> >>
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> >>
> >> Some experiments on how to build the source reader and its
> >>
> >> library
> >>
> >> for
> >>
> >> common threading/split patterns:
> >>
> >>
> >>
> >>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> >>
> >> Best,
> >> Stephan
> >>
> >>
> >> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]> <
> [hidden email]>
> >>
> >> wrote:
> >>
> >> Hi devs,
> >>
> >> Since 1.9 is nearly released, I think we could get back to
> >>
> >> FLIP-27.
> >>
> >> I
> >>
> >> believe it should be included in 1.10.
> >>
> >> There are so many things mentioned in document of FLIP-27. [1] I
> >>
> >> think
> >>
> >> we'd better discuss them separately. However the wiki is not a
> >>
> >> good
> >>
> >> place
> >>
> >> to discuss. I wrote google doc about SplitReader API which
> >>
> >> misses
> >>
> >> some
> >>
> >> details in the document. [2]
> >>
> >> 1.
> >>
> >>
> >>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> >>
> >> 2.
> >>
> >>
> >>
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> >>
> >> CC Stephan, Aljoscha, Piotrek, Becket
> >>
> >>
> >> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email]> <
> [hidden email]>
> >>
> >> wrote:
> >>
> >> Hi Steven,
> >> Thank you for the feedback. Please take a look at the document
> >>
> >> FLIP-27
> >>
> >> <
> >>
> >>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> >>
> >> which
> >>
> >> is updated recently. A lot of details of enumerator were added
> >>
> >> in
> >>
> >> this
> >>
> >> document. I think it would help.
> >>
> >> Steven Wu <[hidden email]> <[hidden email]> 于2019年3月28日周四
> 下午12:52写道：
> >>
> >>
> >> This proposal mentioned that SplitEnumerator might run on the
> >> JobManager or
> >> in a single task on a TaskManager.
> >>
> >> if enumerator is a single task on a taskmanager, then the job
> >>
> >> DAG
> >>
> >> can
> >>
> >> never
> >> been embarrassingly parallel anymore. That will nullify the
> >>
> >> leverage
> >>
> >> of
> >>
> >> fine-grained recovery for embarrassingly parallel jobs.
> >>
> >> It's not clear to me what's the implication of running
> >>
> >> enumerator
> >>
> >> on
> >>
> >> the
> >>
> >> jobmanager. So I will leave that out for now.
> >>
> >> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email]> <
> [hidden email]>
> >>
> >> wrote:
> >>
> >> Hi Stephan & Piotrek,
> >>
> >> Thank you for feedback.
> >>
> >> It seems that there are a lot of things to do in community.
> >>
> >> I
> >>
> >> am
> >>
> >> just
> >>
> >> afraid that this discussion may be forgotten since there so
> >>
> >> many
> >>
> >> proposals
> >>
> >> recently.
> >> Anyway, wish to see the split topics soon :)
> >>
> >> Piotr Nowojski <[hidden email]> <[hidden email]>
> 于2019年1月24日周四
> >>
> >> 下午8:21写道：
> >>
> >> Hi Biao!
> >>
> >> This discussion was stalled because of preparations for
> >>
> >> the
> >>
> >> open
> >>
> >> sourcing
> >>
> >> & merging Blink. I think before creating the tickets we
> >>
> >> should
> >>
> >> split this
> >>
> >> discussion into topics/areas outlined by Stephan and
> >>
> >> create
> >>
> >> Flips
> >>
> >> for
> >>
> >> that.
> >>
> >> I think there is no chance for this to be completed in
> >>
> >> couple
> >>
> >> of
> >>
> >> remaining
> >>
> >> weeks/1 month before 1.8 feature freeze, however it would
> >>
> >> be
> >>
> >> good
> >>
> >> to aim
> >>
> >> with those changes for 1.9.
> >>
> >> Piotrek
> >>
> >>
> >> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email]> <
> [hidden email]>
> >>
> >> wrote:
> >>
> >> Hi community,
> >> The summary of Stephan makes a lot sense to me. It is
> >>
> >> much
> >>
> >> clearer
> >>
> >> indeed
> >>
> >> after splitting the complex topic into small ones.
> >> I was wondering is there any detail plan for next step?
> >>
> >> If
> >>
> >> not,
> >>
> >> I
> >>
> >> would
> >>
> >> like to push this thing forward by creating some JIRA
> >>
> >> issues.
> >>
> >> Another question is that should version 1.8 include
> >>
> >> these
> >>
> >> features?
> >>
> >> Stephan Ewen <[hidden email]> <[hidden email]> 于2018年12月1日周六
> 上午4:20写道：
> >>
> >>
> >> Thanks everyone for the lively discussion. Let me try
> >>
> >> to
> >>
> >> summarize
> >>
> >> where I
> >>
> >> see convergence in the discussion and open issues.
> >> I'll try to group this by design aspect of the source.
> >>
> >> Please
> >>
> >> let me
> >>
> >> know
> >>
> >> if I got things wrong or missed something crucial here.
> >>
> >> For issues 1-3, if the below reflects the state of the
> >>
> >> discussion, I
> >>
> >> would
> >>
> >> try and update the FLIP in the next days.
> >> For the remaining ones we need more discussion.
> >>
> >> I would suggest to fork each of these aspects into a
> >>
> >> separate
> >>
> >> mail
> >>
> >> thread,
> >>
> >> or will loose sight of the individual aspects.
> >>
> >> *(1) Separation of Split Enumerator and Split Reader*
> >>
> >>  - All seem to agree this is a good thing
> >>  - Split Enumerator could in the end live on JobManager
> >>
> >> (and
> >>
> >> assign
> >>
> >> splits
> >>
> >> via RPC) or in a task (and assign splits via data
> >>
> >> streams)
> >>
> >>  - this discussion is orthogonal and should come later,
> >>
> >> when
> >>
> >> the
> >>
> >> interface
> >>
> >> is agreed upon.
> >>
> >> *(2) Split Readers for one or more splits*
> >>
> >>  - Discussion seems to agree that we need to support
> >>
> >> one
> >>
> >> reader
> >>
> >> that
> >>
> >> possibly handles multiple splits concurrently.
> >>  - The requirement comes from sources where one
> >>
> >> poll()-style
> >>
> >> call
> >>
> >> fetches
> >>
> >> data from different splits / partitions
> >>    --> example sources that require that would be for
> >>
> >> example
> >>
> >> Kafka,
> >>
> >> Pravega, Pulsar
> >>
> >>  - Could have one split reader per source, or multiple
> >>
> >> split
> >>
> >> readers
> >>
> >> that
> >>
> >> share the "poll()" function
> >>  - To not make it too complicated, we can start with
> >>
> >> thinking
> >>
> >> about
> >>
> >> one
> >>
> >> split reader for all splits initially and see if that
> >>
> >> covers
> >>
> >> all
> >>
> >> requirements
> >>
> >> *(3) Threading model of the Split Reader*
> >>
> >>  - Most active part of the discussion ;-)
> >>
> >>  - A non-blocking way for Flink's task code to interact
> >>
> >> with
> >>
> >> the
> >>
> >> source
> >>
> >> is
> >>
> >> needed in order to a task runtime code based on a
> >> single-threaded/actor-style task design
> >>    --> I personally am a big proponent of that, it will
> >>
> >> help
> >>
> >> with
> >>
> >> well-behaved checkpoints, efficiency, and simpler yet
> >>
> >> more
> >>
> >> robust
> >>
> >> runtime
> >>
> >> code
> >>
> >>  - Users care about simple abstraction, so as a
> >>
> >> subclass
> >>
> >> of
> >>
> >> SplitReader
> >>
> >> (non-blocking / async) we need to have a
> >>
> >> BlockingSplitReader
> >>
> >> which
> >>
> >> will
> >>
> >> form the basis of most source implementations.
> >>
> >> BlockingSplitReader
> >>
> >> lets
> >>
> >> users do blocking simple poll() calls.
> >>  - The BlockingSplitReader would spawn a thread (or
> >>
> >> more)
> >>
> >> and
> >>
> >> the
> >>
> >> thread(s) can make blocking calls and hand over data
> >>
> >> buffers
> >>
> >> via
> >>
> >> a
> >>
> >> blocking
> >>
> >> queue
> >>  - This should allow us to cover both, a fully async
> >>
> >> runtime,
> >>
> >> and a
> >>
> >> simple
> >>
> >> blocking interface for users.
> >>  - This is actually very similar to how the Kafka
> >>
> >> connectors
> >>
> >> work.
> >>
> >> Kafka
> >>
> >> 9+ with one thread, Kafka 8 with multiple threads
> >>
> >>  - On the base SplitReader (the async one), the
> >>
> >> non-blocking
> >>
> >> method
> >>
> >> that
> >>
> >> gets the next chunk of data would signal data
> >>
> >> availability
> >>
> >> via
> >>
> >> a
> >>
> >> CompletableFuture, because that gives the best
> >>
> >> flexibility
> >>
> >> (can
> >>
> >> await
> >>
> >> completion or register notification handlers).
> >>  - The source task would register a "thenHandle()" (or
> >>
> >> similar)
> >>
> >> on the
> >>
> >> future to put a "take next data" task into the
> >>
> >> actor-style
> >>
> >> mailbox
> >>
> >> *(4) Split Enumeration and Assignment*
> >>
> >>  - Splits may be generated lazily, both in cases where
> >>
> >> there
> >>
> >> is a
> >>
> >> limited
> >>
> >> number of splits (but very many), or splits are
> >>
> >> discovered
> >>
> >> over
> >>
> >> time
> >>
> >>  - Assignment should also be lazy, to get better load
> >>
> >> balancing
> >>
> >>  - Assignment needs support locality preferences
> >>
> >>  - Possible design based on discussion so far:
> >>
> >>    --> SplitReader has a method "addSplits(SplitT...)"
> >>
> >> to
> >>
> >> add
> >>
> >> one or
> >>
> >> more
> >>
> >> splits. Some split readers might assume they have only
> >>
> >> one
> >>
> >> split
> >>
> >> ever,
> >>
> >> concurrently, others assume multiple splits. (Note:
> >>
> >> idea
> >>
> >> behind
> >>
> >> being
> >>
> >> able
> >>
> >> to add multiple splits at the same time is to ease
> >>
> >> startup
> >>
> >> where
> >>
> >> multiple
> >>
> >> splits may be assigned instantly.)
> >>    --> SplitReader has a context object on which it can
> >>
> >> call
> >>
> >> indicate
> >>
> >> when
> >>
> >> splits are completed. The enumerator gets that
> >>
> >> notification and
> >>
> >> can
> >>
> >> use
> >>
> >> to
> >>
> >> decide when to assign new splits. This should help both
> >>
> >> in
> >>
> >> cases
> >>
> >> of
> >>
> >> sources
> >>
> >> that take splits lazily (file readers) and in case the
> >>
> >> source
> >>
> >> needs to
> >>
> >> preserve a partial order between splits (Kinesis,
> >>
> >> Pravega,
> >>
> >> Pulsar may
> >>
> >> need
> >>
> >> that).
> >>    --> SplitEnumerator gets notification when
> >>
> >> SplitReaders
> >>
> >> start
> >>
> >> and
> >>
> >> when
> >>
> >> they finish splits. They can decide at that moment to
> >>
> >> push
> >>
> >> more
> >>
> >> splits
> >>
> >> to
> >>
> >> that reader
> >>    --> The SplitEnumerator should probably be aware of
> >>
> >> the
> >>
> >> source
> >>
> >> parallelism, to build its initial distribution.
> >>
> >>  - Open question: Should the source expose something
> >>
> >> like
> >>
> >> "host
> >>
> >> preferences", so that yarn/mesos/k8s can take this into
> >>
> >> account
> >>
> >> when
> >>
> >> selecting a node to start a TM on?
> >>
> >> *(5) Watermarks and event time alignment*
> >>
> >>  - Watermark generation, as well as idleness, needs to
> >>
> >> be
> >>
> >> per
> >>
> >> split
> >>
> >> (like
> >>
> >> currently in the Kafka Source, per partition)
> >>  - It is desirable to support optional
> >>
> >> event-time-alignment,
> >>
> >> meaning
> >>
> >> that
> >>
> >> splits that are ahead are back-pressured or temporarily
> >>
> >> unsubscribed
> >>
> >>  - I think i would be desirable to encapsulate
> >>
> >> watermark
> >>
> >> generation
> >>
> >> logic
> >>
> >> in watermark generators, for a separation of concerns.
> >>
> >> The
> >>
> >> watermark
> >>
> >> generators should run per split.
> >>  - Using watermark generators would also help with
> >>
> >> another
> >>
> >> problem of
> >>
> >> the
> >>
> >> suggested interface, namely supporting non-periodic
> >>
> >> watermarks
> >>
> >> efficiently.
> >>
> >>  - Need a way to "dispatch" next record to different
> >>
> >> watermark
> >>
> >> generators
> >>
> >>  - Need a way to tell SplitReader to "suspend" a split
> >>
> >> until a
> >>
> >> certain
> >>
> >> watermark is reached (event time backpressure)
> >>  - This would in fact be not needed (and thus simpler)
> >>
> >> if
> >>
> >> we
> >>
> >> had
> >>
> >> a
> >>
> >> SplitReader per split and may be a reason to re-open
> >>
> >> that
> >>
> >> discussion
> >>
> >> *(6) Watermarks across splits and in the Split
> >>
> >> Enumerator*
> >>
> >>  - The split enumerator may need some watermark
> >>
> >> awareness,
> >>
> >> which
> >>
> >> should
> >>
> >> be
> >>
> >> purely based on split metadata (like create timestamp
> >>
> >> of
> >>
> >> file
> >>
> >> splits)
> >>
> >>  - If there are still more splits with overlapping
> >>
> >> event
> >>
> >> time
> >>
> >> range
> >>
> >> for
> >>
> >> a
> >>
> >> split reader, then that split reader should not advance
> >>
> >> the
> >>
> >> watermark
> >>
> >> within the split beyond the overlap boundary. Otherwise
> >>
> >> future
> >>
> >> splits
> >>
> >> will
> >>
> >> produce late data.
> >>
> >>  - One way to approach this could be that the split
> >>
> >> enumerator
> >>
> >> may
> >>
> >> send
> >>
> >> watermarks to the readers, and the readers cannot emit
> >>
> >> watermarks
> >>
> >> beyond
> >>
> >> that received watermark.
> >>  - Many split enumerators would simply immediately send
> >>
> >> Long.MAX
> >>
> >> out
> >>
> >> and
> >>
> >> leave the progress purely to the split readers.
> >>
> >>  - For event-time alignment / split back pressure, this
> >>
> >> begs
> >>
> >> the
> >>
> >> question
> >>
> >> how we can avoid deadlocks that may arise when splits
> >>
> >> are
> >>
> >> suspended
> >>
> >> for
> >>
> >> event time back pressure,
> >>
> >> *(7) Batch and streaming Unification*
> >>
> >>  - Functionality wise, the above design should support
> >>
> >> both
> >>
> >>  - Batch often (mostly) does not care about reading "in
> >>
> >> order"
> >>
> >> and
> >>
> >> generating watermarks
> >>    --> Might use different enumerator logic that is
> >>
> >> more
> >>
> >> locality
> >>
> >> aware
> >>
> >> and ignores event time order
> >>    --> Does not generate watermarks
> >>  - Would be great if bounded sources could be
> >>
> >> identified
> >>
> >> at
> >>
> >> compile
> >>
> >> time,
> >>
> >> so that "env.addBoundedSource(...)" is type safe and
> >>
> >> can
> >>
> >> return a
> >>
> >> "BoundedDataStream".
> >>  - Possible to defer this discussion until later
> >>
> >> *Miscellaneous Comments*
> >>
> >>  - Should the source have a TypeInformation for the
> >>
> >> produced
> >>
> >> type,
> >>
> >> instead
> >>
> >> of a serializer? We need a type information in the
> >>
> >> stream
> >>
> >> anyways, and
> >>
> >> can
> >>
> >> derive the serializer from that. Plus, creating the
> >>
> >> serializer
> >>
> >> should
> >>
> >> respect the ExecutionConfig.
> >>
> >>  - The TypeSerializer interface is very powerful but
> >>
> >> also
> >>
> >> not
> >>
> >> easy to
> >>
> >> implement. Its purpose is to handle data super
> >>
> >> efficiently,
> >>
> >> support
> >>
> >> flexible ways of evolution, etc.
> >>  For metadata I would suggest to look at the
> >>
> >> SimpleVersionedSerializer
> >>
> >> instead, which is used for example for checkpoint
> >>
> >> master
> >>
> >> hooks,
> >>
> >> or for
> >>
> >> the
> >>
> >> streaming file sink. I think that is is a good match
> >>
> >> for
> >>
> >> cases
> >>
> >> where
> >>
> >> we
> >>
> >> do
> >>
> >> not need more than ser/deser (no copy, etc.) and don't
> >>
> >> need to
> >>
> >> push
> >>
> >> versioning out of the serialization paths for best
> >>
> >> performance
> >>
> >> (as in
> >>
> >> the
> >>
> >> TypeSerializer)
> >>
> >>
> >> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
> [hidden email]>
> >> wrote:
> >>
> >>
> >> Hi Biao,
> >>
> >> Thanks for the answer!
> >>
> >> So given the multi-threaded readers, now we have as
> >>
> >> open
> >>
> >> questions:
> >>
> >> 1) How do we let the checkpoints pass through our
> >>
> >> multi-threaded
> >>
> >> reader
> >>
> >> operator?
> >>
> >> 2) Do we have separate reader and source operators or
> >>
> >> not? In
> >>
> >> the
> >>
> >> strategy
> >>
> >> that has a separate source, the source operator has a
> >>
> >> parallelism of
> >>
> >> 1
> >>
> >> and
> >>
> >> is responsible for split recovery only.
> >>
> >> For the first one, given also the constraints
> >>
> >> (blocking,
> >>
> >> finite
> >>
> >> queues,
> >>
> >> etc), I do not have an answer yet.
> >>
> >> For the 2nd, I think that we should go with separate
> >>
> >> operators
> >>
> >> for
> >>
> >> the
> >>
> >> source and the readers, for the following reasons:
> >>
> >> 1) This is more aligned with a potential future
> >>
> >> improvement
> >>
> >> where the
> >>
> >> split
> >>
> >> discovery becomes a responsibility of the JobManager
> >>
> >> and
> >>
> >> readers are
> >>
> >> pooling more work from the JM.
> >>
> >> 2) The source is going to be the "single point of
> >>
> >> truth".
> >>
> >> It
> >>
> >> will
> >>
> >> know
> >>
> >> what
> >>
> >> has been processed and what not. If the source and the
> >>
> >> readers
> >>
> >> are a
> >>
> >> single
> >>
> >> operator with parallelism > 1, or in general, if the
> >>
> >> split
> >>
> >> discovery
> >>
> >> is
> >>
> >> done by each task individually, then:
> >>   i) we have to have a deterministic scheme for each
> >>
> >> reader to
> >>
> >> assign
> >>
> >> splits to itself (e.g. mod subtaskId). This is not
> >>
> >> necessarily
> >>
> >> trivial
> >>
> >> for
> >>
> >> all sources.
> >>   ii) each reader would have to keep a copy of all its
> >>
> >> processed
> >>
> >> slpits
> >>
> >>   iii) the state has to be a union state with a
> >>
> >> non-trivial
> >>
> >> merging
> >>
> >> logic
> >>
> >> in order to support rescaling.
> >>
> >> Two additional points that you raised above:
> >>
> >> i) The point that you raised that we need to keep all
> >>
> >> splits
> >>
> >> (processed
> >>
> >> and
> >>
> >> not-processed) I think is a bit of a strong
> >>
> >> requirement.
> >>
> >> This
> >>
> >> would
> >>
> >> imply
> >>
> >> that for infinite sources the state will grow
> >>
> >> indefinitely.
> >>
> >> This is
> >>
> >> problem
> >>
> >> is even more pronounced if we do not have a single
> >>
> >> source
> >>
> >> that
> >>
> >> assigns
> >>
> >> splits to readers, as each reader will have its own
> >>
> >> copy
> >>
> >> of
> >>
> >> the
> >>
> >> state.
> >>
> >> ii) it is true that for finite sources we need to
> >>
> >> somehow
> >>
> >> not
> >>
> >> close
> >>
> >> the
> >>
> >> readers when the source/split discoverer finishes. The
> >> ContinuousFileReaderOperator has a work-around for
> >>
> >> that.
> >>
> >> It is
> >>
> >> not
> >>
> >> elegant,
> >>
> >> and checkpoints are not emitted after closing the
> >>
> >> source,
> >>
> >> but
> >>
> >> this, I
> >>
> >> believe, is a bigger problem which requires more
> >>
> >> changes
> >>
> >> than
> >>
> >> just
> >>
> >> refactoring the source interface.
> >>
> >> Cheers,
> >> Kostas
> >>
> >>
> >>
>
>

[Jingsong Li]

Hi all,

I think current design is good.

My understanding is:

For execution mode: bounded mode and continuous mode, It's totally
different. I don't think we have the ability to integrate the two models at
present. It's about scheduling, memory, algorithms, States, etc. we
shouldn't confuse them.

For source capabilities: only bounded, only continuous, both bounded and
continuous.
I think Kafka is a source that can be ran both bounded
and continuous execution mode.
And Kafka with end offset should be ran both bounded
and continuous execution mode.  Using apache Beam with Flink runner, I used
to run a "bounded" Kafka in streaming mode. For our previous DataStream, it
is not necessarily required that the source cannot be bounded.

So it is my thought for Dawid's question:
1.pass a bounded source to continuousSource() +1
2.pass a continuous source to boundedSource() -1, should throw exception.

In StreamExecutionEnvironment, continuousSource and boundedSource define
the execution mode. It defines a clear boundary of execution mode.

Best,
Jingsong Lee

On Tue, Dec 10, 2019 at 10:37 AM Jark Wu <[hidden email]> wrote:

> I agree with Dawid's point that the boundedness information should come
> from the source itself (e.g. the end timestamp), not through
> env.boundedSouce()/continuousSource().
> I think if we want to support something like `env.source()` that derive the
> execution mode from source, `supportsBoundedness(Boundedness)`
> method is not enough, because we don't know whether it is bounded or not.
>
> Best,
> Jark
>
>
> On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <[hidden email]>
> wrote:
>
> > One more thing. In the current proposal, with the
> > supportsBoundedness(Boundedness) method and the boundedness coming from
> > either continuousSource or boundedSource I could not find how this
> > information is fed back to the SplitEnumerator.
> >
> > Best,
> >
> > Dawid
> >
> > On 09/12/2019 13:52, Becket Qin wrote:
> > > Hi Dawid,
> > >
> > > Thanks for the comments. This actually brings another relevant question
> > > about what does a "bounded source" imply. I actually had the same
> > > impression when I look at the Source API. Here is what I understand
> after
> > > some discussion with Stephan. The bounded source has the following
> > impacts.
> > >
> > > 1. API validity.
> > > - A bounded source generates a bounded stream so some operations that
> > only
> > > works for bounded records would be performed, e.g. sort.
> > > - To expose these bounded stream only APIs, there are two options:
> > >      a. Add them to the DataStream API and throw exception if a method
> is
> > > called on an unbounded stream.
> > >      b. Create a BoundedDataStream class which is returned from
> > > env.boundedSource(), while DataStream is returned from
> > env.continousSource().
> > > Note that this cannot be done by having single env.source(theSource)
> even
> > > the Source has a getBoundedness() method.
> > >
> > > 2. Scheduling
> > > - A bounded source could be computed stage by stage without bringing up
> > all
> > > the tasks at the same time.
> > >
> > > 3. Operator behaviors
> > > - A bounded source indicates the records are finite so some operators
> can
> > > wait until it receives all the records before it starts the processing.
> > >
> > > In the above impact, only 1 is relevant to the API design. And the
> > current
> > > proposal in FLIP-27 is following 1.b.
> > >
> > > // boundedness depends of source property, imo this should always be
> > >> preferred
> > >>
> > >
> > > DataStream<MyType> stream = env.source(theSource);
> > >
> > >
> > > In your proposal, does DataStream have bounded stream only methods? It
> > > looks it should have, otherwise passing a bounded Source to
> env.source()
> > > would be confusing. In that case, we will essentially do 1.a if an
> > > unbounded Source is created from env.source(unboundedSource).
> > >
> > > If we have the methods only supported for bounded streams in
> DataStream,
> > it
> > > seems a little weird to have a separate BoundedDataStream interface.
> > >
> > > Am I understand it correctly?
> > >
> > > Thanks,
> > >
> > > Jiangjie (Becket) Qin
> > >
> > >
> > >
> > > On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <
> [hidden email]>
> > > wrote:
> > >
> > >> Hi all,
> > >>
> > >> Really well written proposal and very important one. I must admit I
> have
> > >> not understood all the intricacies of it yet.
> > >>
> > >> One question I have though is about where does the information about
> > >> boundedness come from. I think in most cases it is a property of the
> > >> source. As you described it might be e.g. end offset, a flag should it
> > >> monitor new splits etc. I think it would be a really nice use case to
> be
> > >> able to say:
> > >>
> > >> new KafkaSource().readUntil(long timestamp),
> > >>
> > >> which could work as an "end offset". Moreover I think all Bounded
> > sources
> > >> support continuous mode, but no intrinsically continuous source
> support
> > the
> > >> Bounded mode. If I understood the proposal correctly it suggest the
> > >> boundedness sort of "comes" from the outside of the source, from the
> > >> invokation of either boundedStream or continousSource.
> > >>
> > >> I am wondering if it would make sense to actually change the method
> > >>
> > >> boolean Source#supportsBoundedness(Boundedness)
> > >>
> > >> to
> > >>
> > >> Boundedness Source#getBoundedness().
> > >>
> > >> As for the methods #boundedSource, #continousSource, assuming the
> > >> boundedness is property of the source they do not affect how the
> > enumerator
> > >> works, but mostly how the dag is scheduled, right? I am not against
> > those
> > >> methods, but I think it is a very specific use case to actually
> override
> > >> the property of the source. In general I would expect users to only
> call
> > >> env.source(theSource), where the source tells if it is bounded or
> not. I
> > >> would suggest considering following set of methods:
> > >>
> > >> // boundedness depends of source property, imo this should always be
> > preferred
> > >>
> > >> DataStream<MyType> stream = env.source(theSource);
> > >>
> > >>
> > >> // always continous execution, whether bounded or unbounded source
> > >>
> > >> DataStream<MyType> boundedStream = env.continousSource(theSource);
> > >>
> > >> // imo this would make sense if the BoundedDataStream provides
> > additional features unavailable for continous mode
> > >> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
> > >>
> > >>
> > >> Best,
> > >>
> > >> Dawid
> > >>
> > >>
> > >> On 04/12/2019 11:25, Stephan Ewen wrote:
> > >>
> > >> Thanks, Becket, for updating this.
> > >>
> > >> I agree with moving the aspects you mentioned into separate FLIPs -
> this
> > >> one way becoming unwieldy in size.
> > >>
> > >> +1 to the FLIP in its current state. Its a very detailed write-up,
> > nicely
> > >> done!
> > >>
> > >> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]> <
> > [hidden email]> wrote:
> > >>
> > >>
> > >> Hi all,
> > >>
> > >> Sorry for the long belated update. I have updated FLIP-27 wiki page
> with
> > >> the latest proposals. Some noticeable changes include:
> > >> 1. A new generic communication mechanism between SplitEnumerator and
> > >> SourceReader.
> > >> 2. Some detail API method signature changes.
> > >>
> > >> We left a few things out of this FLIP and will address them in
> separate
> > >> FLIPs. Including:
> > >> 1. Per split event time.
> > >> 2. Event time alignment.
> > >> 3. Fine grained failover for SplitEnumerator failure.
> > >>
> > >> Please let us know if you have any question.
> > >>
> > >> Thanks,
> > >>
> > >> Jiangjie (Becket) Qin
> > >>
> > >> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]> <
> > [hidden email]> wrote:
> > >>
> > >>
> > >> Hi  Łukasz!
> > >>
> > >> Becket and me are working hard on figuring out the last details and
> > >> implementing the first PoC. We would update the FLIP hopefully next
> > week.
> > >>
> > >> There is a fair chance that a first version of this will be in 1.10,
> but
> > >>
> > >> I
> > >>
> > >> think it will take another release to battle test it and migrate the
> > >> connectors.
> > >>
> > >> Best,
> > >> Stephan
> > >>
> > >>
> > >>
> > >>
> > >> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <[hidden email]> <
> > [hidden email]>
> > >>
> > >> wrote:
> > >>
> > >> Hi,
> > >>
> > >> This proposal looks very promising for us. Do you have any plans in
> > >>
> > >> which
> > >>
> > >> Flink release it is going to be released? We are thinking on using a
> > >>
> > >> Data
> > >>
> > >> Set API for our future use cases but on the other hand Data Set API is
> > >> going to be deprecated so using proposed bounded data streams solution
> > >> could be more viable in the long term.
> > >>
> > >> Thanks,
> > >> Łukasz
> > >>
> > >> On 2019/10/01 15:48:03, Thomas Weise <[hidden email]> <
> > [hidden email]> wrote:
> > >>
> > >> Thanks for putting together this proposal!
> > >>
> > >> I see that the "Per Split Event Time" and "Event Time Alignment"
> > >>
> > >> sections
> > >>
> > >> are still TBD.
> > >>
> > >> It would probably be good to flesh those out a bit before proceeding
> > >>
> > >> too
> > >>
> > >> far
> > >>
> > >> as the event time alignment will probably influence the interaction
> > >>
> > >> with
> > >>
> > >> the split reader, specifically ReaderStatus emitNext(SourceOutput<E>
> > >> output).
> > >>
> > >> We currently have only one implementation for event time alignment in
> > >>
> > >> the
> > >>
> > >> Kinesis consumer. The synchronization in that case takes place as the
> > >>
> > >> last
> > >>
> > >> step before records are emitted downstream (RecordEmitter). With the
> > >> currently proposed interfaces, the equivalent can be implemented in
> > >>
> > >> the
> > >>
> > >> reader loop, although note that in the Kinesis consumer the per shard
> > >> threads push records.
> > >>
> > >> Synchronization has not been implemented for the Kafka consumer yet.
> > >> https://issues.apache.org/jira/browse/FLINK-12675
> > >>
> > >> When I looked at it, I realized that the implementation will look
> > >>
> > >> quite
> > >>
> > >> different
> > >> from Kinesis because it needs to take place in the pull part, where
> > >>
> > >> records
> > >>
> > >> are taken from the Kafka client. Due to the multiplexing it cannot be
> > >>
> > >> done
> > >>
> > >> by blocking the split thread like it currently works for Kinesis.
> > >>
> > >> Reading
> > >>
> > >> from individual Kafka partitions needs to be controlled via
> > >>
> > >> pause/resume
> > >>
> > >> on the Kafka client.
> > >>
> > >> To take on that responsibility the split thread would need to be
> > >>
> > >> aware
> > >>
> > >> of
> > >>
> > >> the
> > >> watermarks or at least whether it should or should not continue to
> > >>
> > >> consume
> > >>
> > >> a given split and this may require a different SourceReader or
> > >>
> > >> SourceOutput
> > >>
> > >> interface.
> > >>
> > >> Thanks,
> > >> Thomas
> > >>
> > >>
> > >> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email]> <
> > [hidden email]> wrote:
> > >>
> > >>
> > >> Hi Stephan,
> > >>
> > >> Thank you for feedback!
> > >> Will take a look at your branch before public discussing.
> > >>
> > >>
> > >> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]> <
> > [hidden email]>
> > >>
> > >> wrote:
> > >>
> > >> Hi Biao!
> > >>
> > >> Thanks for reviving this. I would like to join this discussion,
> > >>
> > >> but
> > >>
> > >> am
> > >>
> > >> quite occupied with the 1.9 release, so can we maybe pause this
> > >>
> > >> discussion
> > >>
> > >> for a week or so?
> > >>
> > >> In the meantime I can share some suggestion based on prior
> > >>
> > >> experiments:
> > >>
> > >> How to do watermarks / timestamp extractors in a simpler and more
> > >>
> > >> flexible
> > >>
> > >> way. I think that part is quite promising should be part of the
> > >>
> > >> new
> > >>
> > >> source
> > >>
> > >> interface.
> > >>
> > >>
> > >>
> > >>
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> > >>
> > >>
> >
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> > >>
> > >> Some experiments on how to build the source reader and its
> > >>
> > >> library
> > >>
> > >> for
> > >>
> > >> common threading/split patterns:
> > >>
> > >>
> > >>
> > >>
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> > >>
> > >> Best,
> > >> Stephan
> > >>
> > >>
> > >> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]> <
> > [hidden email]>
> > >>
> > >> wrote:
> > >>
> > >> Hi devs,
> > >>
> > >> Since 1.9 is nearly released, I think we could get back to
> > >>
> > >> FLIP-27.
> > >>
> > >> I
> > >>
> > >> believe it should be included in 1.10.
> > >>
> > >> There are so many things mentioned in document of FLIP-27. [1] I
> > >>
> > >> think
> > >>
> > >> we'd better discuss them separately. However the wiki is not a
> > >>
> > >> good
> > >>
> > >> place
> > >>
> > >> to discuss. I wrote google doc about SplitReader API which
> > >>
> > >> misses
> > >>
> > >> some
> > >>
> > >> details in the document. [2]
> > >>
> > >> 1.
> > >>
> > >>
> > >>
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> > >>
> > >> 2.
> > >>
> > >>
> > >>
> >
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> > >>
> > >> CC Stephan, Aljoscha, Piotrek, Becket
> > >>
> > >>
> > >> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email]> <
> > [hidden email]>
> > >>
> > >> wrote:
> > >>
> > >> Hi Steven,
> > >> Thank you for the feedback. Please take a look at the document
> > >>
> > >> FLIP-27
> > >>
> > >> <
> > >>
> > >>
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> > >>
> > >> which
> > >>
> > >> is updated recently. A lot of details of enumerator were added
> > >>
> > >> in
> > >>
> > >> this
> > >>
> > >> document. I think it would help.
> > >>
> > >> Steven Wu <[hidden email]> <[hidden email]> 于2019年3月28日周四
> > 下午12:52写道：
> > >>
> > >>
> > >> This proposal mentioned that SplitEnumerator might run on the
> > >> JobManager or
> > >> in a single task on a TaskManager.
> > >>
> > >> if enumerator is a single task on a taskmanager, then the job
> > >>
> > >> DAG
> > >>
> > >> can
> > >>
> > >> never
> > >> been embarrassingly parallel anymore. That will nullify the
> > >>
> > >> leverage
> > >>
> > >> of
> > >>
> > >> fine-grained recovery for embarrassingly parallel jobs.
> > >>
> > >> It's not clear to me what's the implication of running
> > >>
> > >> enumerator
> > >>
> > >> on
> > >>
> > >> the
> > >>
> > >> jobmanager. So I will leave that out for now.
> > >>
> > >> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email]> <
> > [hidden email]>
> > >>
> > >> wrote:
> > >>
> > >> Hi Stephan & Piotrek,
> > >>
> > >> Thank you for feedback.
> > >>
> > >> It seems that there are a lot of things to do in community.
> > >>
> > >> I
> > >>
> > >> am
> > >>
> > >> just
> > >>
> > >> afraid that this discussion may be forgotten since there so
> > >>
> > >> many
> > >>
> > >> proposals
> > >>
> > >> recently.
> > >> Anyway, wish to see the split topics soon :)
> > >>
> > >> Piotr Nowojski <[hidden email]> <[hidden email]>
> > 于2019年1月24日周四
> > >>
> > >> 下午8:21写道：
> > >>
> > >> Hi Biao!
> > >>
> > >> This discussion was stalled because of preparations for
> > >>
> > >> the
> > >>
> > >> open
> > >>
> > >> sourcing
> > >>
> > >> & merging Blink. I think before creating the tickets we
> > >>
> > >> should
> > >>
> > >> split this
> > >>
> > >> discussion into topics/areas outlined by Stephan and
> > >>
> > >> create
> > >>
> > >> Flips
> > >>
> > >> for
> > >>
> > >> that.
> > >>
> > >> I think there is no chance for this to be completed in
> > >>
> > >> couple
> > >>
> > >> of
> > >>
> > >> remaining
> > >>
> > >> weeks/1 month before 1.8 feature freeze, however it would
> > >>
> > >> be
> > >>
> > >> good
> > >>
> > >> to aim
> > >>
> > >> with those changes for 1.9.
> > >>
> > >> Piotrek
> > >>
> > >>
> > >> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email]> <
> > [hidden email]>
> > >>
> > >> wrote:
> > >>
> > >> Hi community,
> > >> The summary of Stephan makes a lot sense to me. It is
> > >>
> > >> much
> > >>
> > >> clearer
> > >>
> > >> indeed
> > >>
> > >> after splitting the complex topic into small ones.
> > >> I was wondering is there any detail plan for next step?
> > >>
> > >> If
> > >>
> > >> not,
> > >>
> > >> I
> > >>
> > >> would
> > >>
> > >> like to push this thing forward by creating some JIRA
> > >>
> > >> issues.
> > >>
> > >> Another question is that should version 1.8 include
> > >>
> > >> these
> > >>
> > >> features?
> > >>
> > >> Stephan Ewen <[hidden email]> <[hidden email]> 于2018年12月1日周六
> > 上午4:20写道：
> > >>
> > >>
> > >> Thanks everyone for the lively discussion. Let me try
> > >>
> > >> to
> > >>
> > >> summarize
> > >>
> > >> where I
> > >>
> > >> see convergence in the discussion and open issues.
> > >> I'll try to group this by design aspect of the source.
> > >>
> > >> Please
> > >>
> > >> let me
> > >>
> > >> know
> > >>
> > >> if I got things wrong or missed something crucial here.
> > >>
> > >> For issues 1-3, if the below reflects the state of the
> > >>
> > >> discussion, I
> > >>
> > >> would
> > >>
> > >> try and update the FLIP in the next days.
> > >> For the remaining ones we need more discussion.
> > >>
> > >> I would suggest to fork each of these aspects into a
> > >>
> > >> separate
> > >>
> > >> mail
> > >>
> > >> thread,
> > >>
> > >> or will loose sight of the individual aspects.
> > >>
> > >> *(1) Separation of Split Enumerator and Split Reader*
> > >>
> > >>  - All seem to agree this is a good thing
> > >>  - Split Enumerator could in the end live on JobManager
> > >>
> > >> (and
> > >>
> > >> assign
> > >>
> > >> splits
> > >>
> > >> via RPC) or in a task (and assign splits via data
> > >>
> > >> streams)
> > >>
> > >>  - this discussion is orthogonal and should come later,
> > >>
> > >> when
> > >>
> > >> the
> > >>
> > >> interface
> > >>
> > >> is agreed upon.
> > >>
> > >> *(2) Split Readers for one or more splits*
> > >>
> > >>  - Discussion seems to agree that we need to support
> > >>
> > >> one
> > >>
> > >> reader
> > >>
> > >> that
> > >>
> > >> possibly handles multiple splits concurrently.
> > >>  - The requirement comes from sources where one
> > >>
> > >> poll()-style
> > >>
> > >> call
> > >>
> > >> fetches
> > >>
> > >> data from different splits / partitions
> > >>    --> example sources that require that would be for
> > >>
> > >> example
> > >>
> > >> Kafka,
> > >>
> > >> Pravega, Pulsar
> > >>
> > >>  - Could have one split reader per source, or multiple
> > >>
> > >> split
> > >>
> > >> readers
> > >>
> > >> that
> > >>
> > >> share the "poll()" function
> > >>  - To not make it too complicated, we can start with
> > >>
> > >> thinking
> > >>
> > >> about
> > >>
> > >> one
> > >>
> > >> split reader for all splits initially and see if that
> > >>
> > >> covers
> > >>
> > >> all
> > >>
> > >> requirements
> > >>
> > >> *(3) Threading model of the Split Reader*
> > >>
> > >>  - Most active part of the discussion ;-)
> > >>
> > >>  - A non-blocking way for Flink's task code to interact
> > >>
> > >> with
> > >>
> > >> the
> > >>
> > >> source
> > >>
> > >> is
> > >>
> > >> needed in order to a task runtime code based on a
> > >> single-threaded/actor-style task design
> > >>    --> I personally am a big proponent of that, it will
> > >>
> > >> help
> > >>
> > >> with
> > >>
> > >> well-behaved checkpoints, efficiency, and simpler yet
> > >>
> > >> more
> > >>
> > >> robust
> > >>
> > >> runtime
> > >>
> > >> code
> > >>
> > >>  - Users care about simple abstraction, so as a
> > >>
> > >> subclass
> > >>
> > >> of
> > >>
> > >> SplitReader
> > >>
> > >> (non-blocking / async) we need to have a
> > >>
> > >> BlockingSplitReader
> > >>
> > >> which
> > >>
> > >> will
> > >>
> > >> form the basis of most source implementations.
> > >>
> > >> BlockingSplitReader
> > >>
> > >> lets
> > >>
> > >> users do blocking simple poll() calls.
> > >>  - The BlockingSplitReader would spawn a thread (or
> > >>
> > >> more)
> > >>
> > >> and
> > >>
> > >> the
> > >>
> > >> thread(s) can make blocking calls and hand over data
> > >>
> > >> buffers
> > >>
> > >> via
> > >>
> > >> a
> > >>
> > >> blocking
> > >>
> > >> queue
> > >>  - This should allow us to cover both, a fully async
> > >>
> > >> runtime,
> > >>
> > >> and a
> > >>
> > >> simple
> > >>
> > >> blocking interface for users.
> > >>  - This is actually very similar to how the Kafka
> > >>
> > >> connectors
> > >>
> > >> work.
> > >>
> > >> Kafka
> > >>
> > >> 9+ with one thread, Kafka 8 with multiple threads
> > >>
> > >>  - On the base SplitReader (the async one), the
> > >>
> > >> non-blocking
> > >>
> > >> method
> > >>
> > >> that
> > >>
> > >> gets the next chunk of data would signal data
> > >>
> > >> availability
> > >>
> > >> via
> > >>
> > >> a
> > >>
> > >> CompletableFuture, because that gives the best
> > >>
> > >> flexibility
> > >>
> > >> (can
> > >>
> > >> await
> > >>
> > >> completion or register notification handlers).
> > >>  - The source task would register a "thenHandle()" (or
> > >>
> > >> similar)
> > >>
> > >> on the
> > >>
> > >> future to put a "take next data" task into the
> > >>
> > >> actor-style
> > >>
> > >> mailbox
> > >>
> > >> *(4) Split Enumeration and Assignment*
> > >>
> > >>  - Splits may be generated lazily, both in cases where
> > >>
> > >> there
> > >>
> > >> is a
> > >>
> > >> limited
> > >>
> > >> number of splits (but very many), or splits are
> > >>
> > >> discovered
> > >>
> > >> over
> > >>
> > >> time
> > >>
> > >>  - Assignment should also be lazy, to get better load
> > >>
> > >> balancing
> > >>
> > >>  - Assignment needs support locality preferences
> > >>
> > >>  - Possible design based on discussion so far:
> > >>
> > >>    --> SplitReader has a method "addSplits(SplitT...)"
> > >>
> > >> to
> > >>
> > >> add
> > >>
> > >> one or
> > >>
> > >> more
> > >>
> > >> splits. Some split readers might assume they have only
> > >>
> > >> one
> > >>
> > >> split
> > >>
> > >> ever,
> > >>
> > >> concurrently, others assume multiple splits. (Note:
> > >>
> > >> idea
> > >>
> > >> behind
> > >>
> > >> being
> > >>
> > >> able
> > >>
> > >> to add multiple splits at the same time is to ease
> > >>
> > >> startup
> > >>
> > >> where
> > >>
> > >> multiple
> > >>
> > >> splits may be assigned instantly.)
> > >>    --> SplitReader has a context object on which it can
> > >>
> > >> call
> > >>
> > >> indicate
> > >>
> > >> when
> > >>
> > >> splits are completed. The enumerator gets that
> > >>
> > >> notification and
> > >>
> > >> can
> > >>
> > >> use
> > >>
> > >> to
> > >>
> > >> decide when to assign new splits. This should help both
> > >>
> > >> in
> > >>
> > >> cases
> > >>
> > >> of
> > >>
> > >> sources
> > >>
> > >> that take splits lazily (file readers) and in case the
> > >>
> > >> source
> > >>
> > >> needs to
> > >>
> > >> preserve a partial order between splits (Kinesis,
> > >>
> > >> Pravega,
> > >>
> > >> Pulsar may
> > >>
> > >> need
> > >>
> > >> that).
> > >>    --> SplitEnumerator gets notification when
> > >>
> > >> SplitReaders
> > >>
> > >> start
> > >>
> > >> and
> > >>
> > >> when
> > >>
> > >> they finish splits. They can decide at that moment to
> > >>
> > >> push
> > >>
> > >> more
> > >>
> > >> splits
> > >>
> > >> to
> > >>
> > >> that reader
> > >>    --> The SplitEnumerator should probably be aware of
> > >>
> > >> the
> > >>
> > >> source
> > >>
> > >> parallelism, to build its initial distribution.
> > >>
> > >>  - Open question: Should the source expose something
> > >>
> > >> like
> > >>
> > >> "host
> > >>
> > >> preferences", so that yarn/mesos/k8s can take this into
> > >>
> > >> account
> > >>
> > >> when
> > >>
> > >> selecting a node to start a TM on?
> > >>
> > >> *(5) Watermarks and event time alignment*
> > >>
> > >>  - Watermark generation, as well as idleness, needs to
> > >>
> > >> be
> > >>
> > >> per
> > >>
> > >> split
> > >>
> > >> (like
> > >>
> > >> currently in the Kafka Source, per partition)
> > >>  - It is desirable to support optional
> > >>
> > >> event-time-alignment,
> > >>
> > >> meaning
> > >>
> > >> that
> > >>
> > >> splits that are ahead are back-pressured or temporarily
> > >>
> > >> unsubscribed
> > >>
> > >>  - I think i would be desirable to encapsulate
> > >>
> > >> watermark
> > >>
> > >> generation
> > >>
> > >> logic
> > >>
> > >> in watermark generators, for a separation of concerns.
> > >>
> > >> The
> > >>
> > >> watermark
> > >>
> > >> generators should run per split.
> > >>  - Using watermark generators would also help with
> > >>
> > >> another
> > >>
> > >> problem of
> > >>
> > >> the
> > >>
> > >> suggested interface, namely supporting non-periodic
> > >>
> > >> watermarks
> > >>
> > >> efficiently.
> > >>
> > >>  - Need a way to "dispatch" next record to different
> > >>
> > >> watermark
> > >>
> > >> generators
> > >>
> > >>  - Need a way to tell SplitReader to "suspend" a split
> > >>
> > >> until a
> > >>
> > >> certain
> > >>
> > >> watermark is reached (event time backpressure)
> > >>  - This would in fact be not needed (and thus simpler)
> > >>
> > >> if
> > >>
> > >> we
> > >>
> > >> had
> > >>
> > >> a
> > >>
> > >> SplitReader per split and may be a reason to re-open
> > >>
> > >> that
> > >>
> > >> discussion
> > >>
> > >> *(6) Watermarks across splits and in the Split
> > >>
> > >> Enumerator*
> > >>
> > >>  - The split enumerator may need some watermark
> > >>
> > >> awareness,
> > >>
> > >> which
> > >>
> > >> should
> > >>
> > >> be
> > >>
> > >> purely based on split metadata (like create timestamp
> > >>
> > >> of
> > >>
> > >> file
> > >>
> > >> splits)
> > >>
> > >>  - If there are still more splits with overlapping
> > >>
> > >> event
> > >>
> > >> time
> > >>
> > >> range
> > >>
> > >> for
> > >>
> > >> a
> > >>
> > >> split reader, then that split reader should not advance
> > >>
> > >> the
> > >>
> > >> watermark
> > >>
> > >> within the split beyond the overlap boundary. Otherwise
> > >>
> > >> future
> > >>
> > >> splits
> > >>
> > >> will
> > >>
> > >> produce late data.
> > >>
> > >>  - One way to approach this could be that the split
> > >>
> > >> enumerator
> > >>
> > >> may
> > >>
> > >> send
> > >>
> > >> watermarks to the readers, and the readers cannot emit
> > >>
> > >> watermarks
> > >>
> > >> beyond
> > >>
> > >> that received watermark.
> > >>  - Many split enumerators would simply immediately send
> > >>
> > >> Long.MAX
> > >>
> > >> out
> > >>
> > >> and
> > >>
> > >> leave the progress purely to the split readers.
> > >>
> > >>  - For event-time alignment / split back pressure, this
> > >>
> > >> begs
> > >>
> > >> the
> > >>
> > >> question
> > >>
> > >> how we can avoid deadlocks that may arise when splits
> > >>
> > >> are
> > >>
> > >> suspended
> > >>
> > >> for
> > >>
> > >> event time back pressure,
> > >>
> > >> *(7) Batch and streaming Unification*
> > >>
> > >>  - Functionality wise, the above design should support
> > >>
> > >> both
> > >>
> > >>  - Batch often (mostly) does not care about reading "in
> > >>
> > >> order"
> > >>
> > >> and
> > >>
> > >> generating watermarks
> > >>    --> Might use different enumerator logic that is
> > >>
> > >> more
> > >>
> > >> locality
> > >>
> > >> aware
> > >>
> > >> and ignores event time order
> > >>    --> Does not generate watermarks
> > >>  - Would be great if bounded sources could be
> > >>
> > >> identified
> > >>
> > >> at
> > >>
> > >> compile
> > >>
> > >> time,
> > >>
> > >> so that "env.addBoundedSource(...)" is type safe and
> > >>
> > >> can
> > >>
> > >> return a
> > >>
> > >> "BoundedDataStream".
> > >>  - Possible to defer this discussion until later
> > >>
> > >> *Miscellaneous Comments*
> > >>
> > >>  - Should the source have a TypeInformation for the
> > >>
> > >> produced
> > >>
> > >> type,
> > >>
> > >> instead
> > >>
> > >> of a serializer? We need a type information in the
> > >>
> > >> stream
> > >>
> > >> anyways, and
> > >>
> > >> can
> > >>
> > >> derive the serializer from that. Plus, creating the
> > >>
> > >> serializer
> > >>
> > >> should
> > >>
> > >> respect the ExecutionConfig.
> > >>
> > >>  - The TypeSerializer interface is very powerful but
> > >>
> > >> also
> > >>
> > >> not
> > >>
> > >> easy to
> > >>
> > >> implement. Its purpose is to handle data super
> > >>
> > >> efficiently,
> > >>
> > >> support
> > >>
> > >> flexible ways of evolution, etc.
> > >>  For metadata I would suggest to look at the
> > >>
> > >> SimpleVersionedSerializer
> > >>
> > >> instead, which is used for example for checkpoint
> > >>
> > >> master
> > >>
> > >> hooks,
> > >>
> > >> or for
> > >>
> > >> the
> > >>
> > >> streaming file sink. I think that is is a good match
> > >>
> > >> for
> > >>
> > >> cases
> > >>
> > >> where
> > >>
> > >> we
> > >>
> > >> do
> > >>
> > >> not need more than ser/deser (no copy, etc.) and don't
> > >>
> > >> need to
> > >>
> > >> push
> > >>
> > >> versioning out of the serialization paths for best
> > >>
> > >> performance
> > >>
> > >> (as in
> > >>
> > >> the
> > >>
> > >> TypeSerializer)
> > >>
> > >>
> > >> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
> > [hidden email]>
> > >> wrote:
> > >>
> > >>
> > >> Hi Biao,
> > >>
> > >> Thanks for the answer!
> > >>
> > >> So given the multi-threaded readers, now we have as
> > >>
> > >> open
> > >>
> > >> questions:
> > >>
> > >> 1) How do we let the checkpoints pass through our
> > >>
> > >> multi-threaded
> > >>
> > >> reader
> > >>
> > >> operator?
> > >>
> > >> 2) Do we have separate reader and source operators or
> > >>
> > >> not? In
> > >>
> > >> the
> > >>
> > >> strategy
> > >>
> > >> that has a separate source, the source operator has a
> > >>
> > >> parallelism of
> > >>
> > >> 1
> > >>
> > >> and
> > >>
> > >> is responsible for split recovery only.
> > >>
> > >> For the first one, given also the constraints
> > >>
> > >> (blocking,
> > >>
> > >> finite
> > >>
> > >> queues,
> > >>
> > >> etc), I do not have an answer yet.
> > >>
> > >> For the 2nd, I think that we should go with separate
> > >>
> > >> operators
> > >>
> > >> for
> > >>
> > >> the
> > >>
> > >> source and the readers, for the following reasons:
> > >>
> > >> 1) This is more aligned with a potential future
> > >>
> > >> improvement
> > >>
> > >> where the
> > >>
> > >> split
> > >>
> > >> discovery becomes a responsibility of the JobManager
> > >>
> > >> and
> > >>
> > >> readers are
> > >>
> > >> pooling more work from the JM.
> > >>
> > >> 2) The source is going to be the "single point of
> > >>
> > >> truth".
> > >>
> > >> It
> > >>
> > >> will
> > >>
> > >> know
> > >>
> > >> what
> > >>
> > >> has been processed and what not. If the source and the
> > >>
> > >> readers
> > >>
> > >> are a
> > >>
> > >> single
> > >>
> > >> operator with parallelism > 1, or in general, if the
> > >>
> > >> split
> > >>
> > >> discovery
> > >>
> > >> is
> > >>
> > >> done by each task individually, then:
> > >>   i) we have to have a deterministic scheme for each
> > >>
> > >> reader to
> > >>
> > >> assign
> > >>
> > >> splits to itself (e.g. mod subtaskId). This is not
> > >>
> > >> necessarily
> > >>
> > >> trivial
> > >>
> > >> for
> > >>
> > >> all sources.
> > >>   ii) each reader would have to keep a copy of all its
> > >>
> > >> processed
> > >>
> > >> slpits
> > >>
> > >>   iii) the state has to be a union state with a
> > >>
> > >> non-trivial
> > >>
> > >> merging
> > >>
> > >> logic
> > >>
> > >> in order to support rescaling.
> > >>
> > >> Two additional points that you raised above:
> > >>
> > >> i) The point that you raised that we need to keep all
> > >>
> > >> splits
> > >>
> > >> (processed
> > >>
> > >> and
> > >>
> > >> not-processed) I think is a bit of a strong
> > >>
> > >> requirement.
> > >>
> > >> This
> > >>
> > >> would
> > >>
> > >> imply
> > >>
> > >> that for infinite sources the state will grow
> > >>
> > >> indefinitely.
> > >>
> > >> This is
> > >>
> > >> problem
> > >>
> > >> is even more pronounced if we do not have a single
> > >>
> > >> source
> > >>
> > >> that
> > >>
> > >> assigns
> > >>
> > >> splits to readers, as each reader will have its own
> > >>
> > >> copy
> > >>
> > >> of
> > >>
> > >> the
> > >>
> > >> state.
> > >>
> > >> ii) it is true that for finite sources we need to
> > >>
> > >> somehow
> > >>
> > >> not
> > >>
> > >> close
> > >>
> > >> the
> > >>
> > >> readers when the source/split discoverer finishes. The
> > >> ContinuousFileReaderOperator has a work-around for
> > >>
> > >> that.
> > >>
> > >> It is
> > >>
> > >> not
> > >>
> > >> elegant,
> > >>
> > >> and checkpoints are not emitted after closing the
> > >>
> > >> source,
> > >>
> > >> but
> > >>
> > >> this, I
> > >>
> > >> believe, is a bigger problem which requires more
> > >>
> > >> changes
> > >>
> > >> than
> > >>
> > >> just
> > >>
> > >> refactoring the source interface.
> > >>
> > >> Cheers,
> > >> Kostas
> > >>
> > >>
> > >>
> >
> >
>

--
Best, Jingsong Lee

[Till Rohrmann]

Hi everyone,

thanks for drafting this FLIP. It reads very well.

Concerning Dawid's proposal, I tend to agree. The boundedness could come
from the source and tell the system how to treat the operator (scheduling
wise). From a user's perspective it should be fine to get back a DataStream
when calling env.source(boundedSource) if he does not need special
operations defined on a BoundedDataStream. If he needs this, then one could
use the method BoundedDataStream env.boundedSource(boundedSource).

If possible, we could enforce the proper usage of env.boundedSource() by
introducing a BoundedSource type so that one cannot pass an
unbounded source to it. That way users would not be able to shoot
themselves in the foot.

Maybe this has already been asked before but I was wondering why the
SourceReader interface has the method pollNext which hands the
responsibility of outputting elements to the SourceReader implementation?
Has this been done for backwards compatibility reasons with the old source
interface? If not, then one could define a Collection<E> getNextRecords()
method which returns the currently retrieved records and then the caller
emits them outside of the SourceReader. That way the interface would not
allow to implement an outputting loop where we never hand back control to
the caller. At the moment, this contract can be easily broken and is only
mentioned loosely in the JavaDocs.

Cheers,
Till

On Tue, Dec 10, 2019 at 7:49 AM Jingsong Li <[hidden email]> wrote:

> Hi all,
>
> I think current design is good.
>
> My understanding is:
>
> For execution mode: bounded mode and continuous mode, It's totally
> different. I don't think we have the ability to integrate the two models at
> present. It's about scheduling, memory, algorithms, States, etc. we
> shouldn't confuse them.
>
> For source capabilities: only bounded, only continuous, both bounded and
> continuous.
> I think Kafka is a source that can be ran both bounded
> and continuous execution mode.
> And Kafka with end offset should be ran both bounded
> and continuous execution mode.  Using apache Beam with Flink runner, I used
> to run a "bounded" Kafka in streaming mode. For our previous DataStream, it
> is not necessarily required that the source cannot be bounded.
>
> So it is my thought for Dawid's question:
> 1.pass a bounded source to continuousSource() +1
> 2.pass a continuous source to boundedSource() -1, should throw exception.
>
> In StreamExecutionEnvironment, continuousSource and boundedSource define
> the execution mode. It defines a clear boundary of execution mode.
>
> Best,
> Jingsong Lee
>
> On Tue, Dec 10, 2019 at 10:37 AM Jark Wu <[hidden email]> wrote:
>
> > I agree with Dawid's point that the boundedness information should come
> > from the source itself (e.g. the end timestamp), not through
> > env.boundedSouce()/continuousSource().
> > I think if we want to support something like `env.source()` that derive
> the
> > execution mode from source, `supportsBoundedness(Boundedness)`
> > method is not enough, because we don't know whether it is bounded or not.
> >
> > Best,
> > Jark
> >
> >
> > On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <[hidden email]>
> > wrote:
> >
> > > One more thing. In the current proposal, with the
> > > supportsBoundedness(Boundedness) method and the boundedness coming from
> > > either continuousSource or boundedSource I could not find how this
> > > information is fed back to the SplitEnumerator.
> > >
> > > Best,
> > >
> > > Dawid
> > >
> > > On 09/12/2019 13:52, Becket Qin wrote:
> > > > Hi Dawid,
> > > >
> > > > Thanks for the comments. This actually brings another relevant
> question
> > > > about what does a "bounded source" imply. I actually had the same
> > > > impression when I look at the Source API. Here is what I understand
> > after
> > > > some discussion with Stephan. The bounded source has the following
> > > impacts.
> > > >
> > > > 1. API validity.
> > > > - A bounded source generates a bounded stream so some operations that
> > > only
> > > > works for bounded records would be performed, e.g. sort.
> > > > - To expose these bounded stream only APIs, there are two options:
> > > >      a. Add them to the DataStream API and throw exception if a
> method
> > is
> > > > called on an unbounded stream.
> > > >      b. Create a BoundedDataStream class which is returned from
> > > > env.boundedSource(), while DataStream is returned from
> > > env.continousSource().
> > > > Note that this cannot be done by having single env.source(theSource)
> > even
> > > > the Source has a getBoundedness() method.
> > > >
> > > > 2. Scheduling
> > > > - A bounded source could be computed stage by stage without bringing
> up
> > > all
> > > > the tasks at the same time.
> > > >
> > > > 3. Operator behaviors
> > > > - A bounded source indicates the records are finite so some operators
> > can
> > > > wait until it receives all the records before it starts the
> processing.
> > > >
> > > > In the above impact, only 1 is relevant to the API design. And the
> > > current
> > > > proposal in FLIP-27 is following 1.b.
> > > >
> > > > // boundedness depends of source property, imo this should always be
> > > >> preferred
> > > >>
> > > >
> > > > DataStream<MyType> stream = env.source(theSource);
> > > >
> > > >
> > > > In your proposal, does DataStream have bounded stream only methods?
> It
> > > > looks it should have, otherwise passing a bounded Source to
> > env.source()
> > > > would be confusing. In that case, we will essentially do 1.a if an
> > > > unbounded Source is created from env.source(unboundedSource).
> > > >
> > > > If we have the methods only supported for bounded streams in
> > DataStream,
> > > it
> > > > seems a little weird to have a separate BoundedDataStream interface.
> > > >
> > > > Am I understand it correctly?
> > > >
> > > > Thanks,
> > > >
> > > > Jiangjie (Becket) Qin
> > > >
> > > >
> > > >
> > > > On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <
> > [hidden email]>
> > > > wrote:
> > > >
> > > >> Hi all,
> > > >>
> > > >> Really well written proposal and very important one. I must admit I
> > have
> > > >> not understood all the intricacies of it yet.
> > > >>
> > > >> One question I have though is about where does the information about
> > > >> boundedness come from. I think in most cases it is a property of the
> > > >> source. As you described it might be e.g. end offset, a flag should
> it
> > > >> monitor new splits etc. I think it would be a really nice use case
> to
> > be
> > > >> able to say:
> > > >>
> > > >> new KafkaSource().readUntil(long timestamp),
> > > >>
> > > >> which could work as an "end offset". Moreover I think all Bounded
> > > sources
> > > >> support continuous mode, but no intrinsically continuous source
> > support
> > > the
> > > >> Bounded mode. If I understood the proposal correctly it suggest the
> > > >> boundedness sort of "comes" from the outside of the source, from the
> > > >> invokation of either boundedStream or continousSource.
> > > >>
> > > >> I am wondering if it would make sense to actually change the method
> > > >>
> > > >> boolean Source#supportsBoundedness(Boundedness)
> > > >>
> > > >> to
> > > >>
> > > >> Boundedness Source#getBoundedness().
> > > >>
> > > >> As for the methods #boundedSource, #continousSource, assuming the
> > > >> boundedness is property of the source they do not affect how the
> > > enumerator
> > > >> works, but mostly how the dag is scheduled, right? I am not against
> > > those
> > > >> methods, but I think it is a very specific use case to actually
> > override
> > > >> the property of the source. In general I would expect users to only
> > call
> > > >> env.source(theSource), where the source tells if it is bounded or
> > not. I
> > > >> would suggest considering following set of methods:
> > > >>
> > > >> // boundedness depends of source property, imo this should always be
> > > preferred
> > > >>
> > > >> DataStream<MyType> stream = env.source(theSource);
> > > >>
> > > >>
> > > >> // always continous execution, whether bounded or unbounded source
> > > >>
> > > >> DataStream<MyType> boundedStream = env.continousSource(theSource);
> > > >>
> > > >> // imo this would make sense if the BoundedDataStream provides
> > > additional features unavailable for continous mode
> > > >> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
> > > >>
> > > >>
> > > >> Best,
> > > >>
> > > >> Dawid
> > > >>
> > > >>
> > > >> On 04/12/2019 11:25, Stephan Ewen wrote:
> > > >>
> > > >> Thanks, Becket, for updating this.
> > > >>
> > > >> I agree with moving the aspects you mentioned into separate FLIPs -
> > this
> > > >> one way becoming unwieldy in size.
> > > >>
> > > >> +1 to the FLIP in its current state. Its a very detailed write-up,
> > > nicely
> > > >> done!
> > > >>
> > > >> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]> <
> > > [hidden email]> wrote:
> > > >>
> > > >>
> > > >> Hi all,
> > > >>
> > > >> Sorry for the long belated update. I have updated FLIP-27 wiki page
> > with
> > > >> the latest proposals. Some noticeable changes include:
> > > >> 1. A new generic communication mechanism between SplitEnumerator and
> > > >> SourceReader.
> > > >> 2. Some detail API method signature changes.
> > > >>
> > > >> We left a few things out of this FLIP and will address them in
> > separate
> > > >> FLIPs. Including:
> > > >> 1. Per split event time.
> > > >> 2. Event time alignment.
> > > >> 3. Fine grained failover for SplitEnumerator failure.
> > > >>
> > > >> Please let us know if you have any question.
> > > >>
> > > >> Thanks,
> > > >>
> > > >> Jiangjie (Becket) Qin
> > > >>
> > > >> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]> <
> > > [hidden email]> wrote:
> > > >>
> > > >>
> > > >> Hi  Łukasz!
> > > >>
> > > >> Becket and me are working hard on figuring out the last details and
> > > >> implementing the first PoC. We would update the FLIP hopefully next
> > > week.
> > > >>
> > > >> There is a fair chance that a first version of this will be in 1.10,
> > but
> > > >>
> > > >> I
> > > >>
> > > >> think it will take another release to battle test it and migrate the
> > > >> connectors.
> > > >>
> > > >> Best,
> > > >> Stephan
> > > >>
> > > >>
> > > >>
> > > >>
> > > >> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <[hidden email]>
> <
> > > [hidden email]>
> > > >>
> > > >> wrote:
> > > >>
> > > >> Hi,
> > > >>
> > > >> This proposal looks very promising for us. Do you have any plans in
> > > >>
> > > >> which
> > > >>
> > > >> Flink release it is going to be released? We are thinking on using a
> > > >>
> > > >> Data
> > > >>
> > > >> Set API for our future use cases but on the other hand Data Set API
> is
> > > >> going to be deprecated so using proposed bounded data streams
> solution
> > > >> could be more viable in the long term.
> > > >>
> > > >> Thanks,
> > > >> Łukasz
> > > >>
> > > >> On 2019/10/01 15:48:03, Thomas Weise <[hidden email]> <
> > > [hidden email]> wrote:
> > > >>
> > > >> Thanks for putting together this proposal!
> > > >>
> > > >> I see that the "Per Split Event Time" and "Event Time Alignment"
> > > >>
> > > >> sections
> > > >>
> > > >> are still TBD.
> > > >>
> > > >> It would probably be good to flesh those out a bit before proceeding
> > > >>
> > > >> too
> > > >>
> > > >> far
> > > >>
> > > >> as the event time alignment will probably influence the interaction
> > > >>
> > > >> with
> > > >>
> > > >> the split reader, specifically ReaderStatus emitNext(SourceOutput<E>
> > > >> output).
> > > >>
> > > >> We currently have only one implementation for event time alignment
> in
> > > >>
> > > >> the
> > > >>
> > > >> Kinesis consumer. The synchronization in that case takes place as
> the
> > > >>
> > > >> last
> > > >>
> > > >> step before records are emitted downstream (RecordEmitter). With the
> > > >> currently proposed interfaces, the equivalent can be implemented in
> > > >>
> > > >> the
> > > >>
> > > >> reader loop, although note that in the Kinesis consumer the per
> shard
> > > >> threads push records.
> > > >>
> > > >> Synchronization has not been implemented for the Kafka consumer yet.
> > > >> https://issues.apache.org/jira/browse/FLINK-12675
> > > >>
> > > >> When I looked at it, I realized that the implementation will look
> > > >>
> > > >> quite
> > > >>
> > > >> different
> > > >> from Kinesis because it needs to take place in the pull part, where
> > > >>
> > > >> records
> > > >>
> > > >> are taken from the Kafka client. Due to the multiplexing it cannot
> be
> > > >>
> > > >> done
> > > >>
> > > >> by blocking the split thread like it currently works for Kinesis.
> > > >>
> > > >> Reading
> > > >>
> > > >> from individual Kafka partitions needs to be controlled via
> > > >>
> > > >> pause/resume
> > > >>
> > > >> on the Kafka client.
> > > >>
> > > >> To take on that responsibility the split thread would need to be
> > > >>
> > > >> aware
> > > >>
> > > >> of
> > > >>
> > > >> the
> > > >> watermarks or at least whether it should or should not continue to
> > > >>
> > > >> consume
> > > >>
> > > >> a given split and this may require a different SourceReader or
> > > >>
> > > >> SourceOutput
> > > >>
> > > >> interface.
> > > >>
> > > >> Thanks,
> > > >> Thomas
> > > >>
> > > >>
> > > >> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email]> <
> > > [hidden email]> wrote:
> > > >>
> > > >>
> > > >> Hi Stephan,
> > > >>
> > > >> Thank you for feedback!
> > > >> Will take a look at your branch before public discussing.
> > > >>
> > > >>
> > > >> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]> <
> > > [hidden email]>
> > > >>
> > > >> wrote:
> > > >>
> > > >> Hi Biao!
> > > >>
> > > >> Thanks for reviving this. I would like to join this discussion,
> > > >>
> > > >> but
> > > >>
> > > >> am
> > > >>
> > > >> quite occupied with the 1.9 release, so can we maybe pause this
> > > >>
> > > >> discussion
> > > >>
> > > >> for a week or so?
> > > >>
> > > >> In the meantime I can share some suggestion based on prior
> > > >>
> > > >> experiments:
> > > >>
> > > >> How to do watermarks / timestamp extractors in a simpler and more
> > > >>
> > > >> flexible
> > > >>
> > > >> way. I think that part is quite promising should be part of the
> > > >>
> > > >> new
> > > >>
> > > >> source
> > > >>
> > > >> interface.
> > > >>
> > > >>
> > > >>
> > > >>
> > >
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> > > >>
> > > >>
> > >
> >
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> > > >>
> > > >> Some experiments on how to build the source reader and its
> > > >>
> > > >> library
> > > >>
> > > >> for
> > > >>
> > > >> common threading/split patterns:
> > > >>
> > > >>
> > > >>
> > > >>
> > >
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> > > >>
> > > >> Best,
> > > >> Stephan
> > > >>
> > > >>
> > > >> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]> <
> > > [hidden email]>
> > > >>
> > > >> wrote:
> > > >>
> > > >> Hi devs,
> > > >>
> > > >> Since 1.9 is nearly released, I think we could get back to
> > > >>
> > > >> FLIP-27.
> > > >>
> > > >> I
> > > >>
> > > >> believe it should be included in 1.10.
> > > >>
> > > >> There are so many things mentioned in document of FLIP-27. [1] I
> > > >>
> > > >> think
> > > >>
> > > >> we'd better discuss them separately. However the wiki is not a
> > > >>
> > > >> good
> > > >>
> > > >> place
> > > >>
> > > >> to discuss. I wrote google doc about SplitReader API which
> > > >>
> > > >> misses
> > > >>
> > > >> some
> > > >>
> > > >> details in the document. [2]
> > > >>
> > > >> 1.
> > > >>
> > > >>
> > > >>
> > >
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> > > >>
> > > >> 2.
> > > >>
> > > >>
> > > >>
> > >
> >
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> > > >>
> > > >> CC Stephan, Aljoscha, Piotrek, Becket
> > > >>
> > > >>
> > > >> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email]> <
> > > [hidden email]>
> > > >>
> > > >> wrote:
> > > >>
> > > >> Hi Steven,
> > > >> Thank you for the feedback. Please take a look at the document
> > > >>
> > > >> FLIP-27
> > > >>
> > > >> <
> > > >>
> > > >>
> > >
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> > > >>
> > > >> which
> > > >>
> > > >> is updated recently. A lot of details of enumerator were added
> > > >>
> > > >> in
> > > >>
> > > >> this
> > > >>
> > > >> document. I think it would help.
> > > >>
> > > >> Steven Wu <[hidden email]> <[hidden email]>
> 于2019年3月28日周四
> > > 下午12:52写道：
> > > >>
> > > >>
> > > >> This proposal mentioned that SplitEnumerator might run on the
> > > >> JobManager or
> > > >> in a single task on a TaskManager.
> > > >>
> > > >> if enumerator is a single task on a taskmanager, then the job
> > > >>
> > > >> DAG
> > > >>
> > > >> can
> > > >>
> > > >> never
> > > >> been embarrassingly parallel anymore. That will nullify the
> > > >>
> > > >> leverage
> > > >>
> > > >> of
> > > >>
> > > >> fine-grained recovery for embarrassingly parallel jobs.
> > > >>
> > > >> It's not clear to me what's the implication of running
> > > >>
> > > >> enumerator
> > > >>
> > > >> on
> > > >>
> > > >> the
> > > >>
> > > >> jobmanager. So I will leave that out for now.
> > > >>
> > > >> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email]> <
> > > [hidden email]>
> > > >>
> > > >> wrote:
> > > >>
> > > >> Hi Stephan & Piotrek,
> > > >>
> > > >> Thank you for feedback.
> > > >>
> > > >> It seems that there are a lot of things to do in community.
> > > >>
> > > >> I
> > > >>
> > > >> am
> > > >>
> > > >> just
> > > >>
> > > >> afraid that this discussion may be forgotten since there so
> > > >>
> > > >> many
> > > >>
> > > >> proposals
> > > >>
> > > >> recently.
> > > >> Anyway, wish to see the split topics soon :)
> > > >>
> > > >> Piotr Nowojski <[hidden email]> <[hidden email]>
> > > 于2019年1月24日周四
> > > >>
> > > >> 下午8:21写道：
> > > >>
> > > >> Hi Biao!
> > > >>
> > > >> This discussion was stalled because of preparations for
> > > >>
> > > >> the
> > > >>
> > > >> open
> > > >>
> > > >> sourcing
> > > >>
> > > >> & merging Blink. I think before creating the tickets we
> > > >>
> > > >> should
> > > >>
> > > >> split this
> > > >>
> > > >> discussion into topics/areas outlined by Stephan and
> > > >>
> > > >> create
> > > >>
> > > >> Flips
> > > >>
> > > >> for
> > > >>
> > > >> that.
> > > >>
> > > >> I think there is no chance for this to be completed in
> > > >>
> > > >> couple
> > > >>
> > > >> of
> > > >>
> > > >> remaining
> > > >>
> > > >> weeks/1 month before 1.8 feature freeze, however it would
> > > >>
> > > >> be
> > > >>
> > > >> good
> > > >>
> > > >> to aim
> > > >>
> > > >> with those changes for 1.9.
> > > >>
> > > >> Piotrek
> > > >>
> > > >>
> > > >> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email]> <
> > > [hidden email]>
> > > >>
> > > >> wrote:
> > > >>
> > > >> Hi community,
> > > >> The summary of Stephan makes a lot sense to me. It is
> > > >>
> > > >> much
> > > >>
> > > >> clearer
> > > >>
> > > >> indeed
> > > >>
> > > >> after splitting the complex topic into small ones.
> > > >> I was wondering is there any detail plan for next step?
> > > >>
> > > >> If
> > > >>
> > > >> not,
> > > >>
> > > >> I
> > > >>
> > > >> would
> > > >>
> > > >> like to push this thing forward by creating some JIRA
> > > >>
> > > >> issues.
> > > >>
> > > >> Another question is that should version 1.8 include
> > > >>
> > > >> these
> > > >>
> > > >> features?
> > > >>
> > > >> Stephan Ewen <[hidden email]> <[hidden email]> 于2018年12月1日周六
> > > 上午4:20写道：
> > > >>
> > > >>
> > > >> Thanks everyone for the lively discussion. Let me try
> > > >>
> > > >> to
> > > >>
> > > >> summarize
> > > >>
> > > >> where I
> > > >>
> > > >> see convergence in the discussion and open issues.
> > > >> I'll try to group this by design aspect of the source.
> > > >>
> > > >> Please
> > > >>
> > > >> let me
> > > >>
> > > >> know
> > > >>
> > > >> if I got things wrong or missed something crucial here.
> > > >>
> > > >> For issues 1-3, if the below reflects the state of the
> > > >>
> > > >> discussion, I
> > > >>
> > > >> would
> > > >>
> > > >> try and update the FLIP in the next days.
> > > >> For the remaining ones we need more discussion.
> > > >>
> > > >> I would suggest to fork each of these aspects into a
> > > >>
> > > >> separate
> > > >>
> > > >> mail
> > > >>
> > > >> thread,
> > > >>
> > > >> or will loose sight of the individual aspects.
> > > >>
> > > >> *(1) Separation of Split Enumerator and Split Reader*
> > > >>
> > > >>  - All seem to agree this is a good thing
> > > >>  - Split Enumerator could in the end live on JobManager
> > > >>
> > > >> (and
> > > >>
> > > >> assign
> > > >>
> > > >> splits
> > > >>
> > > >> via RPC) or in a task (and assign splits via data
> > > >>
> > > >> streams)
> > > >>
> > > >>  - this discussion is orthogonal and should come later,
> > > >>
> > > >> when
> > > >>
> > > >> the
> > > >>
> > > >> interface
> > > >>
> > > >> is agreed upon.
> > > >>
> > > >> *(2) Split Readers for one or more splits*
> > > >>
> > > >>  - Discussion seems to agree that we need to support
> > > >>
> > > >> one
> > > >>
> > > >> reader
> > > >>
> > > >> that
> > > >>
> > > >> possibly handles multiple splits concurrently.
> > > >>  - The requirement comes from sources where one
> > > >>
> > > >> poll()-style
> > > >>
> > > >> call
> > > >>
> > > >> fetches
> > > >>
> > > >> data from different splits / partitions
> > > >>    --> example sources that require that would be for
> > > >>
> > > >> example
> > > >>
> > > >> Kafka,
> > > >>
> > > >> Pravega, Pulsar
> > > >>
> > > >>  - Could have one split reader per source, or multiple
> > > >>
> > > >> split
> > > >>
> > > >> readers
> > > >>
> > > >> that
> > > >>
> > > >> share the "poll()" function
> > > >>  - To not make it too complicated, we can start with
> > > >>
> > > >> thinking
> > > >>
> > > >> about
> > > >>
> > > >> one
> > > >>
> > > >> split reader for all splits initially and see if that
> > > >>
> > > >> covers
> > > >>
> > > >> all
> > > >>
> > > >> requirements
> > > >>
> > > >> *(3) Threading model of the Split Reader*
> > > >>
> > > >>  - Most active part of the discussion ;-)
> > > >>
> > > >>  - A non-blocking way for Flink's task code to interact
> > > >>
> > > >> with
> > > >>
> > > >> the
> > > >>
> > > >> source
> > > >>
> > > >> is
> > > >>
> > > >> needed in order to a task runtime code based on a
> > > >> single-threaded/actor-style task design
> > > >>    --> I personally am a big proponent of that, it will
> > > >>
> > > >> help
> > > >>
> > > >> with
> > > >>
> > > >> well-behaved checkpoints, efficiency, and simpler yet
> > > >>
> > > >> more
> > > >>
> > > >> robust
> > > >>
> > > >> runtime
> > > >>
> > > >> code
> > > >>
> > > >>  - Users care about simple abstraction, so as a
> > > >>
> > > >> subclass
> > > >>
> > > >> of
> > > >>
> > > >> SplitReader
> > > >>
> > > >> (non-blocking / async) we need to have a
> > > >>
> > > >> BlockingSplitReader
> > > >>
> > > >> which
> > > >>
> > > >> will
> > > >>
> > > >> form the basis of most source implementations.
> > > >>
> > > >> BlockingSplitReader
> > > >>
> > > >> lets
> > > >>
> > > >> users do blocking simple poll() calls.
> > > >>  - The BlockingSplitReader would spawn a thread (or
> > > >>
> > > >> more)
> > > >>
> > > >> and
> > > >>
> > > >> the
> > > >>
> > > >> thread(s) can make blocking calls and hand over data
> > > >>
> > > >> buffers
> > > >>
> > > >> via
> > > >>
> > > >> a
> > > >>
> > > >> blocking
> > > >>
> > > >> queue
> > > >>  - This should allow us to cover both, a fully async
> > > >>
> > > >> runtime,
> > > >>
> > > >> and a
> > > >>
> > > >> simple
> > > >>
> > > >> blocking interface for users.
> > > >>  - This is actually very similar to how the Kafka
> > > >>
> > > >> connectors
> > > >>
> > > >> work.
> > > >>
> > > >> Kafka
> > > >>
> > > >> 9+ with one thread, Kafka 8 with multiple threads
> > > >>
> > > >>  - On the base SplitReader (the async one), the
> > > >>
> > > >> non-blocking
> > > >>
> > > >> method
> > > >>
> > > >> that
> > > >>
> > > >> gets the next chunk of data would signal data
> > > >>
> > > >> availability
> > > >>
> > > >> via
> > > >>
> > > >> a
> > > >>
> > > >> CompletableFuture, because that gives the best
> > > >>
> > > >> flexibility
> > > >>
> > > >> (can
> > > >>
> > > >> await
> > > >>
> > > >> completion or register notification handlers).
> > > >>  - The source task would register a "thenHandle()" (or
> > > >>
> > > >> similar)
> > > >>
> > > >> on the
> > > >>
> > > >> future to put a "take next data" task into the
> > > >>
> > > >> actor-style
> > > >>
> > > >> mailbox
> > > >>
> > > >> *(4) Split Enumeration and Assignment*
> > > >>
> > > >>  - Splits may be generated lazily, both in cases where
> > > >>
> > > >> there
> > > >>
> > > >> is a
> > > >>
> > > >> limited
> > > >>
> > > >> number of splits (but very many), or splits are
> > > >>
> > > >> discovered
> > > >>
> > > >> over
> > > >>
> > > >> time
> > > >>
> > > >>  - Assignment should also be lazy, to get better load
> > > >>
> > > >> balancing
> > > >>
> > > >>  - Assignment needs support locality preferences
> > > >>
> > > >>  - Possible design based on discussion so far:
> > > >>
> > > >>    --> SplitReader has a method "addSplits(SplitT...)"
> > > >>
> > > >> to
> > > >>
> > > >> add
> > > >>
> > > >> one or
> > > >>
> > > >> more
> > > >>
> > > >> splits. Some split readers might assume they have only
> > > >>
> > > >> one
> > > >>
> > > >> split
> > > >>
> > > >> ever,
> > > >>
> > > >> concurrently, others assume multiple splits. (Note:
> > > >>
> > > >> idea
> > > >>
> > > >> behind
> > > >>
> > > >> being
> > > >>
> > > >> able
> > > >>
> > > >> to add multiple splits at the same time is to ease
> > > >>
> > > >> startup
> > > >>
> > > >> where
> > > >>
> > > >> multiple
> > > >>
> > > >> splits may be assigned instantly.)
> > > >>    --> SplitReader has a context object on which it can
> > > >>
> > > >> call
> > > >>
> > > >> indicate
> > > >>
> > > >> when
> > > >>
> > > >> splits are completed. The enumerator gets that
> > > >>
> > > >> notification and
> > > >>
> > > >> can
> > > >>
> > > >> use
> > > >>
> > > >> to
> > > >>
> > > >> decide when to assign new splits. This should help both
> > > >>
> > > >> in
> > > >>
> > > >> cases
> > > >>
> > > >> of
> > > >>
> > > >> sources
> > > >>
> > > >> that take splits lazily (file readers) and in case the
> > > >>
> > > >> source
> > > >>
> > > >> needs to
> > > >>
> > > >> preserve a partial order between splits (Kinesis,
> > > >>
> > > >> Pravega,
> > > >>
> > > >> Pulsar may
> > > >>
> > > >> need
> > > >>
> > > >> that).
> > > >>    --> SplitEnumerator gets notification when
> > > >>
> > > >> SplitReaders
> > > >>
> > > >> start
> > > >>
> > > >> and
> > > >>
> > > >> when
> > > >>
> > > >> they finish splits. They can decide at that moment to
> > > >>
> > > >> push
> > > >>
> > > >> more
> > > >>
> > > >> splits
> > > >>
> > > >> to
> > > >>
> > > >> that reader
> > > >>    --> The SplitEnumerator should probably be aware of
> > > >>
> > > >> the
> > > >>
> > > >> source
> > > >>
> > > >> parallelism, to build its initial distribution.
> > > >>
> > > >>  - Open question: Should the source expose something
> > > >>
> > > >> like
> > > >>
> > > >> "host
> > > >>
> > > >> preferences", so that yarn/mesos/k8s can take this into
> > > >>
> > > >> account
> > > >>
> > > >> when
> > > >>
> > > >> selecting a node to start a TM on?
> > > >>
> > > >> *(5) Watermarks and event time alignment*
> > > >>
> > > >>  - Watermark generation, as well as idleness, needs to
> > > >>
> > > >> be
> > > >>
> > > >> per
> > > >>
> > > >> split
> > > >>
> > > >> (like
> > > >>
> > > >> currently in the Kafka Source, per partition)
> > > >>  - It is desirable to support optional
> > > >>
> > > >> event-time-alignment,
> > > >>
> > > >> meaning
> > > >>
> > > >> that
> > > >>
> > > >> splits that are ahead are back-pressured or temporarily
> > > >>
> > > >> unsubscribed
> > > >>
> > > >>  - I think i would be desirable to encapsulate
> > > >>
> > > >> watermark
> > > >>
> > > >> generation
> > > >>
> > > >> logic
> > > >>
> > > >> in watermark generators, for a separation of concerns.
> > > >>
> > > >> The
> > > >>
> > > >> watermark
> > > >>
> > > >> generators should run per split.
> > > >>  - Using watermark generators would also help with
> > > >>
> > > >> another
> > > >>
> > > >> problem of
> > > >>
> > > >> the
> > > >>
> > > >> suggested interface, namely supporting non-periodic
> > > >>
> > > >> watermarks
> > > >>
> > > >> efficiently.
> > > >>
> > > >>  - Need a way to "dispatch" next record to different
> > > >>
> > > >> watermark
> > > >>
> > > >> generators
> > > >>
> > > >>  - Need a way to tell SplitReader to "suspend" a split
> > > >>
> > > >> until a
> > > >>
> > > >> certain
> > > >>
> > > >> watermark is reached (event time backpressure)
> > > >>  - This would in fact be not needed (and thus simpler)
> > > >>
> > > >> if
> > > >>
> > > >> we
> > > >>
> > > >> had
> > > >>
> > > >> a
> > > >>
> > > >> SplitReader per split and may be a reason to re-open
> > > >>
> > > >> that
> > > >>
> > > >> discussion
> > > >>
> > > >> *(6) Watermarks across splits and in the Split
> > > >>
> > > >> Enumerator*
> > > >>
> > > >>  - The split enumerator may need some watermark
> > > >>
> > > >> awareness,
> > > >>
> > > >> which
> > > >>
> > > >> should
> > > >>
> > > >> be
> > > >>
> > > >> purely based on split metadata (like create timestamp
> > > >>
> > > >> of
> > > >>
> > > >> file
> > > >>
> > > >> splits)
> > > >>
> > > >>  - If there are still more splits with overlapping
> > > >>
> > > >> event
> > > >>
> > > >> time
> > > >>
> > > >> range
> > > >>
> > > >> for
> > > >>
> > > >> a
> > > >>
> > > >> split reader, then that split reader should not advance
> > > >>
> > > >> the
> > > >>
> > > >> watermark
> > > >>
> > > >> within the split beyond the overlap boundary. Otherwise
> > > >>
> > > >> future
> > > >>
> > > >> splits
> > > >>
> > > >> will
> > > >>
> > > >> produce late data.
> > > >>
> > > >>  - One way to approach this could be that the split
> > > >>
> > > >> enumerator
> > > >>
> > > >> may
> > > >>
> > > >> send
> > > >>
> > > >> watermarks to the readers, and the readers cannot emit
> > > >>
> > > >> watermarks
> > > >>
> > > >> beyond
> > > >>
> > > >> that received watermark.
> > > >>  - Many split enumerators would simply immediately send
> > > >>
> > > >> Long.MAX
> > > >>
> > > >> out
> > > >>
> > > >> and
> > > >>
> > > >> leave the progress purely to the split readers.
> > > >>
> > > >>  - For event-time alignment / split back pressure, this
> > > >>
> > > >> begs
> > > >>
> > > >> the
> > > >>
> > > >> question
> > > >>
> > > >> how we can avoid deadlocks that may arise when splits
> > > >>
> > > >> are
> > > >>
> > > >> suspended
> > > >>
> > > >> for
> > > >>
> > > >> event time back pressure,
> > > >>
> > > >> *(7) Batch and streaming Unification*
> > > >>
> > > >>  - Functionality wise, the above design should support
> > > >>
> > > >> both
> > > >>
> > > >>  - Batch often (mostly) does not care about reading "in
> > > >>
> > > >> order"
> > > >>
> > > >> and
> > > >>
> > > >> generating watermarks
> > > >>    --> Might use different enumerator logic that is
> > > >>
> > > >> more
> > > >>
> > > >> locality
> > > >>
> > > >> aware
> > > >>
> > > >> and ignores event time order
> > > >>    --> Does not generate watermarks
> > > >>  - Would be great if bounded sources could be
> > > >>
> > > >> identified
> > > >>
> > > >> at
> > > >>
> > > >> compile
> > > >>
> > > >> time,
> > > >>
> > > >> so that "env.addBoundedSource(...)" is type safe and
> > > >>
> > > >> can
> > > >>
> > > >> return a
> > > >>
> > > >> "BoundedDataStream".
> > > >>  - Possible to defer this discussion until later
> > > >>
> > > >> *Miscellaneous Comments*
> > > >>
> > > >>  - Should the source have a TypeInformation for the
> > > >>
> > > >> produced
> > > >>
> > > >> type,
> > > >>
> > > >> instead
> > > >>
> > > >> of a serializer? We need a type information in the
> > > >>
> > > >> stream
> > > >>
> > > >> anyways, and
> > > >>
> > > >> can
> > > >>
> > > >> derive the serializer from that. Plus, creating the
> > > >>
> > > >> serializer
> > > >>
> > > >> should
> > > >>
> > > >> respect the ExecutionConfig.
> > > >>
> > > >>  - The TypeSerializer interface is very powerful but
> > > >>
> > > >> also
> > > >>
> > > >> not
> > > >>
> > > >> easy to
> > > >>
> > > >> implement. Its purpose is to handle data super
> > > >>
> > > >> efficiently,
> > > >>
> > > >> support
> > > >>
> > > >> flexible ways of evolution, etc.
> > > >>  For metadata I would suggest to look at the
> > > >>
> > > >> SimpleVersionedSerializer
> > > >>
> > > >> instead, which is used for example for checkpoint
> > > >>
> > > >> master
> > > >>
> > > >> hooks,
> > > >>
> > > >> or for
> > > >>
> > > >> the
> > > >>
> > > >> streaming file sink. I think that is is a good match
> > > >>
> > > >> for
> > > >>
> > > >> cases
> > > >>
> > > >> where
> > > >>
> > > >> we
> > > >>
> > > >> do
> > > >>
> > > >> not need more than ser/deser (no copy, etc.) and don't
> > > >>
> > > >> need to
> > > >>
> > > >> push
> > > >>
> > > >> versioning out of the serialization paths for best
> > > >>
> > > >> performance
> > > >>
> > > >> (as in
> > > >>
> > > >> the
> > > >>
> > > >> TypeSerializer)
> > > >>
> > > >>
> > > >> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
> > > [hidden email]>
> > > >> wrote:
> > > >>
> > > >>
> > > >> Hi Biao,
> > > >>
> > > >> Thanks for the answer!
> > > >>
> > > >> So given the multi-threaded readers, now we have as
> > > >>
> > > >> open
> > > >>
> > > >> questions:
> > > >>
> > > >> 1) How do we let the checkpoints pass through our
> > > >>
> > > >> multi-threaded
> > > >>
> > > >> reader
> > > >>
> > > >> operator?
> > > >>
> > > >> 2) Do we have separate reader and source operators or
> > > >>
> > > >> not? In
> > > >>
> > > >> the
> > > >>
> > > >> strategy
> > > >>
> > > >> that has a separate source, the source operator has a
> > > >>
> > > >> parallelism of
> > > >>
> > > >> 1
> > > >>
> > > >> and
> > > >>
> > > >> is responsible for split recovery only.
> > > >>
> > > >> For the first one, given also the constraints
> > > >>
> > > >> (blocking,
> > > >>
> > > >> finite
> > > >>
> > > >> queues,
> > > >>
> > > >> etc), I do not have an answer yet.
> > > >>
> > > >> For the 2nd, I think that we should go with separate
> > > >>
> > > >> operators
> > > >>
> > > >> for
> > > >>
> > > >> the
> > > >>
> > > >> source and the readers, for the following reasons:
> > > >>
> > > >> 1) This is more aligned with a potential future
> > > >>
> > > >> improvement
> > > >>
> > > >> where the
> > > >>
> > > >> split
> > > >>
> > > >> discovery becomes a responsibility of the JobManager
> > > >>
> > > >> and
> > > >>
> > > >> readers are
> > > >>
> > > >> pooling more work from the JM.
> > > >>
> > > >> 2) The source is going to be the "single point of
> > > >>
> > > >> truth".
> > > >>
> > > >> It
> > > >>
> > > >> will
> > > >>
> > > >> know
> > > >>
> > > >> what
> > > >>
> > > >> has been processed and what not. If the source and the
> > > >>
> > > >> readers
> > > >>
> > > >> are a
> > > >>
> > > >> single
> > > >>
> > > >> operator with parallelism > 1, or in general, if the
> > > >>
> > > >> split
> > > >>
> > > >> discovery
> > > >>
> > > >> is
> > > >>
> > > >> done by each task individually, then:
> > > >>   i) we have to have a deterministic scheme for each
> > > >>
> > > >> reader to
> > > >>
> > > >> assign
> > > >>
> > > >> splits to itself (e.g. mod subtaskId). This is not
> > > >>
> > > >> necessarily
> > > >>
> > > >> trivial
> > > >>
> > > >> for
> > > >>
> > > >> all sources.
> > > >>   ii) each reader would have to keep a copy of all its
> > > >>
> > > >> processed
> > > >>
> > > >> slpits
> > > >>
> > > >>   iii) the state has to be a union state with a
> > > >>
> > > >> non-trivial
> > > >>
> > > >> merging
> > > >>
> > > >> logic
> > > >>
> > > >> in order to support rescaling.
> > > >>
> > > >> Two additional points that you raised above:
> > > >>
> > > >> i) The point that you raised that we need to keep all
> > > >>
> > > >> splits
> > > >>
> > > >> (processed
> > > >>
> > > >> and
> > > >>
> > > >> not-processed) I think is a bit of a strong
> > > >>
> > > >> requirement.
> > > >>
> > > >> This
> > > >>
> > > >> would
> > > >>
> > > >> imply
> > > >>
> > > >> that for infinite sources the state will grow
> > > >>
> > > >> indefinitely.
> > > >>
> > > >> This is
> > > >>
> > > >> problem
> > > >>
> > > >> is even more pronounced if we do not have a single
> > > >>
> > > >> source
> > > >>
> > > >> that
> > > >>
> > > >> assigns
> > > >>
> > > >> splits to readers, as each reader will have its own
> > > >>
> > > >> copy
> > > >>
> > > >> of
> > > >>
> > > >> the
> > > >>
> > > >> state.
> > > >>
> > > >> ii) it is true that for finite sources we need to
> > > >>
> > > >> somehow
> > > >>
> > > >> not
> > > >>
> > > >> close
> > > >>
> > > >> the
> > > >>
> > > >> readers when the source/split discoverer finishes. The
> > > >> ContinuousFileReaderOperator has a work-around for
> > > >>
> > > >> that.
> > > >>
> > > >> It is
> > > >>
> > > >> not
> > > >>
> > > >> elegant,
> > > >>
> > > >> and checkpoints are not emitted after closing the
> > > >>
> > > >> source,
> > > >>
> > > >> but
> > > >>
> > > >> this, I
> > > >>
> > > >> believe, is a bigger problem which requires more
> > > >>
> > > >> changes
> > > >>
> > > >> than
> > > >>
> > > >> just
> > > >>
> > > >> refactoring the source interface.
> > > >>
> > > >> Cheers,
> > > >> Kostas
> > > >>
> > > >>
> > > >>
> > >
> > >
> >
>
>
> --
> Best, Jingsong Lee
>

[Becket Qin]

Hi folks,

Thanks for the discussion, great feedback. Also thanks Dawid for the
explanation, it is much clearer now.

One thing that is indeed missing from the FLIP is how the boundedness is
passed to the Source implementation. So the API should be
Source#createEnumerator(Boundedness boundedness, SplitEnumeratorContext
context)
And we can probably remove the Source#supportBoundedness(Boundedness
boundedness) method.

Assuming we have that, we are essentially choosing from one of the
following two options:

Option 1:
// The source is continuous source, and only unbounded operations can be
performed.
DataStream<Type> datastream = env.continuousSource(someSource);

// The source is bounded source, both bounded and unbounded operations can
be performed.
BoundedDataStream<Type> boundedDataStream = env.boundedSource(someSource);

  - Pros:
       a) explicit boundary between bounded / unbounded streams, it is
quite simple and clear to the users.
  - Cons:
       a) For applications that do not involve bounded operations, they
still have to call different API to distinguish bounded / unbounded streams.
       b) No support for bounded stream to run in a streaming runtime
setting, i.e. scheduling and operators behaviors.


Option 2:
// The source is either bounded or unbounded, but only unbounded operations
could be performed on the returned DataStream.
DataStream<Type> dataStream = env.source(someSource);

// The source must be a bounded source, otherwise exception is thrown.
BoundedDataStream<Type> boundedDataStream =
env.boundedSource(boundedSource);

The pros and cons are exactly the opposite of option 1.
  - Pros:
       a) For applications that do not involve bounded operations, they
still have to call different API to distinguish bounded / unbounded streams.
       b) Support for bounded stream to run in a streaming runtime setting,
i.e. scheduling and operators behaviors.
  - Cons:
       a) Bounded / unbounded streams are kind of mixed, i.e. given a
DataStream, it is not clear whether it is bounded or not, unless you have
the access to its source.


If we only think from the Source API perspective, option 2 seems a better
choice because functionality wise it is a superset of option 1, at the cost
of some seemingly acceptable ambiguity in the DataStream API.
But if we look at the DataStream API as a whole, option 1 seems a clearer
choice. For example, some times a library may have to know whether a
certain task will finish or not. And it would be difficult to tell if the
input is a DataStream, unless additional information is provided all the
way from the Source. One possible solution is to have a *modified option 2*
which adds a method to the DataStream API to indicate boundedness, such as
getBoundedness(). It would solve the problem with a potential confusion of
what is difference between a DataStream with getBoundedness()=true and a
BoundedDataStream. But that seems not super difficult to explain.

So from API's perspective, I don't have a strong opinion between *option 1*
and *modified option 2. *I like the cleanness of option 1, but modified
option 2 would be more attractive if we have concrete use case for the
"Bounded stream with unbounded streaming runtime settings".

Re: Till

> Maybe this has already been asked before but I was wondering why the
> SourceReader interface has the method pollNext which hands the
> responsibility of outputting elements to the SourceReader implementation?
> Has this been done for backwards compatibility reasons with the old source
> interface? If not, then one could define a Collection<E> getNextRecords()
> method which returns the currently retrieved records and then the caller
> emits them outside of the SourceReader. That way the interface would not
> allow to implement an outputting loop where we never hand back control to
> the caller. At the moment, this contract can be easily broken and is only
> mentioned loosely in the JavaDocs.
>

The primary reason we handover the SourceOutput to the SourceReader is
because sometimes it is difficult for a SourceReader to emit one record at
a time. One example is some batched messaging systems which only have an
offset for the entire batch instead of individual messages in the batch. In
that case, returning one record at a time would leave the SourceReader in
an uncheckpointable state because they can only checkpoint at the batch
boundaries.

Thanks,

Jiangjie (Becket) Qin

On Tue, Dec 10, 2019 at 5:33 PM Till Rohrmann <[hidden email]> wrote:

> Hi everyone,
>
> thanks for drafting this FLIP. It reads very well.
>
> Concerning Dawid's proposal, I tend to agree. The boundedness could come
> from the source and tell the system how to treat the operator (scheduling
> wise). From a user's perspective it should be fine to get back a DataStream
> when calling env.source(boundedSource) if he does not need special
> operations defined on a BoundedDataStream. If he needs this, then one could
> use the method BoundedDataStream env.boundedSource(boundedSource).
>
> If possible, we could enforce the proper usage of env.boundedSource() by
> introducing a BoundedSource type so that one cannot pass an
> unbounded source to it. That way users would not be able to shoot
> themselves in the foot.
>
> Maybe this has already been asked before but I was wondering why the
> SourceReader interface has the method pollNext which hands the
> responsibility of outputting elements to the SourceReader implementation?
> Has this been done for backwards compatibility reasons with the old source
> interface? If not, then one could define a Collection<E> getNextRecords()
> method which returns the currently retrieved records and then the caller
> emits them outside of the SourceReader. That way the interface would not
> allow to implement an outputting loop where we never hand back control to
> the caller. At the moment, this contract can be easily broken and is only
> mentioned loosely in the JavaDocs.
>
> Cheers,
> Till
>
> On Tue, Dec 10, 2019 at 7:49 AM Jingsong Li <[hidden email]>
> wrote:
>
> > Hi all,
> >
> > I think current design is good.
> >
> > My understanding is:
> >
> > For execution mode: bounded mode and continuous mode, It's totally
> > different. I don't think we have the ability to integrate the two models
> at
> > present. It's about scheduling, memory, algorithms, States, etc. we
> > shouldn't confuse them.
> >
> > For source capabilities: only bounded, only continuous, both bounded and
> > continuous.
> > I think Kafka is a source that can be ran both bounded
> > and continuous execution mode.
> > And Kafka with end offset should be ran both bounded
> > and continuous execution mode.  Using apache Beam with Flink runner, I
> used
> > to run a "bounded" Kafka in streaming mode. For our previous DataStream,
> it
> > is not necessarily required that the source cannot be bounded.
> >
> > So it is my thought for Dawid's question:
> > 1.pass a bounded source to continuousSource() +1
> > 2.pass a continuous source to boundedSource() -1, should throw exception.
> >
> > In StreamExecutionEnvironment, continuousSource and boundedSource define
> > the execution mode. It defines a clear boundary of execution mode.
> >
> > Best,
> > Jingsong Lee
> >
> > On Tue, Dec 10, 2019 at 10:37 AM Jark Wu <[hidden email]> wrote:
> >
> > > I agree with Dawid's point that the boundedness information should come
> > > from the source itself (e.g. the end timestamp), not through
> > > env.boundedSouce()/continuousSource().
> > > I think if we want to support something like `env.source()` that derive
> > the
> > > execution mode from source, `supportsBoundedness(Boundedness)`
> > > method is not enough, because we don't know whether it is bounded or
> not.
> > >
> > > Best,
> > > Jark
> > >
> > >
> > > On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <[hidden email]>
> > > wrote:
> > >
> > > > One more thing. In the current proposal, with the
> > > > supportsBoundedness(Boundedness) method and the boundedness coming
> from
> > > > either continuousSource or boundedSource I could not find how this
> > > > information is fed back to the SplitEnumerator.
> > > >
> > > > Best,
> > > >
> > > > Dawid
> > > >
> > > > On 09/12/2019 13:52, Becket Qin wrote:
> > > > > Hi Dawid,
> > > > >
> > > > > Thanks for the comments. This actually brings another relevant
> > question
> > > > > about what does a "bounded source" imply. I actually had the same
> > > > > impression when I look at the Source API. Here is what I understand
> > > after
> > > > > some discussion with Stephan. The bounded source has the following
> > > > impacts.
> > > > >
> > > > > 1. API validity.
> > > > > - A bounded source generates a bounded stream so some operations
> that
> > > > only
> > > > > works for bounded records would be performed, e.g. sort.
> > > > > - To expose these bounded stream only APIs, there are two options:
> > > > >      a. Add them to the DataStream API and throw exception if a
> > method
> > > is
> > > > > called on an unbounded stream.
> > > > >      b. Create a BoundedDataStream class which is returned from
> > > > > env.boundedSource(), while DataStream is returned from
> > > > env.continousSource().
> > > > > Note that this cannot be done by having single
> env.source(theSource)
> > > even
> > > > > the Source has a getBoundedness() method.
> > > > >
> > > > > 2. Scheduling
> > > > > - A bounded source could be computed stage by stage without
> bringing
> > up
> > > > all
> > > > > the tasks at the same time.
> > > > >
> > > > > 3. Operator behaviors
> > > > > - A bounded source indicates the records are finite so some
> operators
> > > can
> > > > > wait until it receives all the records before it starts the
> > processing.
> > > > >
> > > > > In the above impact, only 1 is relevant to the API design. And the
> > > > current
> > > > > proposal in FLIP-27 is following 1.b.
> > > > >
> > > > > // boundedness depends of source property, imo this should always
> be
> > > > >> preferred
> > > > >>
> > > > >
> > > > > DataStream<MyType> stream = env.source(theSource);
> > > > >
> > > > >
> > > > > In your proposal, does DataStream have bounded stream only methods?
> > It
> > > > > looks it should have, otherwise passing a bounded Source to
> > > env.source()
> > > > > would be confusing. In that case, we will essentially do 1.a if an
> > > > > unbounded Source is created from env.source(unboundedSource).
> > > > >
> > > > > If we have the methods only supported for bounded streams in
> > > DataStream,
> > > > it
> > > > > seems a little weird to have a separate BoundedDataStream
> interface.
> > > > >
> > > > > Am I understand it correctly?
> > > > >
> > > > > Thanks,
> > > > >
> > > > > Jiangjie (Becket) Qin
> > > > >
> > > > >
> > > > >
> > > > > On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <
> > > [hidden email]>
> > > > > wrote:
> > > > >
> > > > >> Hi all,
> > > > >>
> > > > >> Really well written proposal and very important one. I must admit
> I
> > > have
> > > > >> not understood all the intricacies of it yet.
> > > > >>
> > > > >> One question I have though is about where does the information
> about
> > > > >> boundedness come from. I think in most cases it is a property of
> the
> > > > >> source. As you described it might be e.g. end offset, a flag
> should
> > it
> > > > >> monitor new splits etc. I think it would be a really nice use case
> > to
> > > be
> > > > >> able to say:
> > > > >>
> > > > >> new KafkaSource().readUntil(long timestamp),
> > > > >>
> > > > >> which could work as an "end offset". Moreover I think all Bounded
> > > > sources
> > > > >> support continuous mode, but no intrinsically continuous source
> > > support
> > > > the
> > > > >> Bounded mode. If I understood the proposal correctly it suggest
> the
> > > > >> boundedness sort of "comes" from the outside of the source, from
> the
> > > > >> invokation of either boundedStream or continousSource.
> > > > >>
> > > > >> I am wondering if it would make sense to actually change the
> method
> > > > >>
> > > > >> boolean Source#supportsBoundedness(Boundedness)
> > > > >>
> > > > >> to
> > > > >>
> > > > >> Boundedness Source#getBoundedness().
> > > > >>
> > > > >> As for the methods #boundedSource, #continousSource, assuming the
> > > > >> boundedness is property of the source they do not affect how the
> > > > enumerator
> > > > >> works, but mostly how the dag is scheduled, right? I am not
> against
> > > > those
> > > > >> methods, but I think it is a very specific use case to actually
> > > override
> > > > >> the property of the source. In general I would expect users to
> only
> > > call
> > > > >> env.source(theSource), where the source tells if it is bounded or
> > > not. I
> > > > >> would suggest considering following set of methods:
> > > > >>
> > > > >> // boundedness depends of source property, imo this should always
> be
> > > > preferred
> > > > >>
> > > > >> DataStream<MyType> stream = env.source(theSource);
> > > > >>
> > > > >>
> > > > >> // always continous execution, whether bounded or unbounded source
> > > > >>
> > > > >> DataStream<MyType> boundedStream = env.continousSource(theSource);
> > > > >>
> > > > >> // imo this would make sense if the BoundedDataStream provides
> > > > additional features unavailable for continous mode
> > > > >> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
> > > > >>
> > > > >>
> > > > >> Best,
> > > > >>
> > > > >> Dawid
> > > > >>
> > > > >>
> > > > >> On 04/12/2019 11:25, Stephan Ewen wrote:
> > > > >>
> > > > >> Thanks, Becket, for updating this.
> > > > >>
> > > > >> I agree with moving the aspects you mentioned into separate FLIPs
> -
> > > this
> > > > >> one way becoming unwieldy in size.
> > > > >>
> > > > >> +1 to the FLIP in its current state. Its a very detailed write-up,
> > > > nicely
> > > > >> done!
> > > > >>
> > > > >> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]>
> <
> > > > [hidden email]> wrote:
> > > > >>
> > > > >>
> > > > >> Hi all,
> > > > >>
> > > > >> Sorry for the long belated update. I have updated FLIP-27 wiki
> page
> > > with
> > > > >> the latest proposals. Some noticeable changes include:
> > > > >> 1. A new generic communication mechanism between SplitEnumerator
> and
> > > > >> SourceReader.
> > > > >> 2. Some detail API method signature changes.
> > > > >>
> > > > >> We left a few things out of this FLIP and will address them in
> > > separate
> > > > >> FLIPs. Including:
> > > > >> 1. Per split event time.
> > > > >> 2. Event time alignment.
> > > > >> 3. Fine grained failover for SplitEnumerator failure.
> > > > >>
> > > > >> Please let us know if you have any question.
> > > > >>
> > > > >> Thanks,
> > > > >>
> > > > >> Jiangjie (Becket) Qin
> > > > >>
> > > > >> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]> <
> > > > [hidden email]> wrote:
> > > > >>
> > > > >>
> > > > >> Hi  Łukasz!
> > > > >>
> > > > >> Becket and me are working hard on figuring out the last details
> and
> > > > >> implementing the first PoC. We would update the FLIP hopefully
> next
> > > > week.
> > > > >>
> > > > >> There is a fair chance that a first version of this will be in
> 1.10,
> > > but
> > > > >>
> > > > >> I
> > > > >>
> > > > >> think it will take another release to battle test it and migrate
> the
> > > > >> connectors.
> > > > >>
> > > > >> Best,
> > > > >> Stephan
> > > > >>
> > > > >>
> > > > >>
> > > > >>
> > > > >> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <[hidden email]
> >
> > <
> > > > [hidden email]>
> > > > >>
> > > > >> wrote:
> > > > >>
> > > > >> Hi,
> > > > >>
> > > > >> This proposal looks very promising for us. Do you have any plans
> in
> > > > >>
> > > > >> which
> > > > >>
> > > > >> Flink release it is going to be released? We are thinking on
> using a
> > > > >>
> > > > >> Data
> > > > >>
> > > > >> Set API for our future use cases but on the other hand Data Set
> API
> > is
> > > > >> going to be deprecated so using proposed bounded data streams
> > solution
> > > > >> could be more viable in the long term.
> > > > >>
> > > > >> Thanks,
> > > > >> Łukasz
> > > > >>
> > > > >> On 2019/10/01 15:48:03, Thomas Weise <[hidden email]> <
> > > > [hidden email]> wrote:
> > > > >>
> > > > >> Thanks for putting together this proposal!
> > > > >>
> > > > >> I see that the "Per Split Event Time" and "Event Time Alignment"
> > > > >>
> > > > >> sections
> > > > >>
> > > > >> are still TBD.
> > > > >>
> > > > >> It would probably be good to flesh those out a bit before
> proceeding
> > > > >>
> > > > >> too
> > > > >>
> > > > >> far
> > > > >>
> > > > >> as the event time alignment will probably influence the
> interaction
> > > > >>
> > > > >> with
> > > > >>
> > > > >> the split reader, specifically ReaderStatus
> emitNext(SourceOutput<E>
> > > > >> output).
> > > > >>
> > > > >> We currently have only one implementation for event time alignment
> > in
> > > > >>
> > > > >> the
> > > > >>
> > > > >> Kinesis consumer. The synchronization in that case takes place as
> > the
> > > > >>
> > > > >> last
> > > > >>
> > > > >> step before records are emitted downstream (RecordEmitter). With
> the
> > > > >> currently proposed interfaces, the equivalent can be implemented
> in
> > > > >>
> > > > >> the
> > > > >>
> > > > >> reader loop, although note that in the Kinesis consumer the per
> > shard
> > > > >> threads push records.
> > > > >>
> > > > >> Synchronization has not been implemented for the Kafka consumer
> yet.
> > > > >> https://issues.apache.org/jira/browse/FLINK-12675
> > > > >>
> > > > >> When I looked at it, I realized that the implementation will look
> > > > >>
> > > > >> quite
> > > > >>
> > > > >> different
> > > > >> from Kinesis because it needs to take place in the pull part,
> where
> > > > >>
> > > > >> records
> > > > >>
> > > > >> are taken from the Kafka client. Due to the multiplexing it cannot
> > be
> > > > >>
> > > > >> done
> > > > >>
> > > > >> by blocking the split thread like it currently works for Kinesis.
> > > > >>
> > > > >> Reading
> > > > >>
> > > > >> from individual Kafka partitions needs to be controlled via
> > > > >>
> > > > >> pause/resume
> > > > >>
> > > > >> on the Kafka client.
> > > > >>
> > > > >> To take on that responsibility the split thread would need to be
> > > > >>
> > > > >> aware
> > > > >>
> > > > >> of
> > > > >>
> > > > >> the
> > > > >> watermarks or at least whether it should or should not continue to
> > > > >>
> > > > >> consume
> > > > >>
> > > > >> a given split and this may require a different SourceReader or
> > > > >>
> > > > >> SourceOutput
> > > > >>
> > > > >> interface.
> > > > >>
> > > > >> Thanks,
> > > > >> Thomas
> > > > >>
> > > > >>
> > > > >> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email]> <
> > > > [hidden email]> wrote:
> > > > >>
> > > > >>
> > > > >> Hi Stephan,
> > > > >>
> > > > >> Thank you for feedback!
> > > > >> Will take a look at your branch before public discussing.
> > > > >>
> > > > >>
> > > > >> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]>
> <
> > > > [hidden email]>
> > > > >>
> > > > >> wrote:
> > > > >>
> > > > >> Hi Biao!
> > > > >>
> > > > >> Thanks for reviving this. I would like to join this discussion,
> > > > >>
> > > > >> but
> > > > >>
> > > > >> am
> > > > >>
> > > > >> quite occupied with the 1.9 release, so can we maybe pause this
> > > > >>
> > > > >> discussion
> > > > >>
> > > > >> for a week or so?
> > > > >>
> > > > >> In the meantime I can share some suggestion based on prior
> > > > >>
> > > > >> experiments:
> > > > >>
> > > > >> How to do watermarks / timestamp extractors in a simpler and more
> > > > >>
> > > > >> flexible
> > > > >>
> > > > >> way. I think that part is quite promising should be part of the
> > > > >>
> > > > >> new
> > > > >>
> > > > >> source
> > > > >>
> > > > >> interface.
> > > > >>
> > > > >>
> > > > >>
> > > > >>
> > > >
> > >
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> > > > >>
> > > > >>
> > > >
> > >
> >
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> > > > >>
> > > > >> Some experiments on how to build the source reader and its
> > > > >>
> > > > >> library
> > > > >>
> > > > >> for
> > > > >>
> > > > >> common threading/split patterns:
> > > > >>
> > > > >>
> > > > >>
> > > > >>
> > > >
> > >
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> > > > >>
> > > > >> Best,
> > > > >> Stephan
> > > > >>
> > > > >>
> > > > >> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]> <
> > > > [hidden email]>
> > > > >>
> > > > >> wrote:
> > > > >>
> > > > >> Hi devs,
> > > > >>
> > > > >> Since 1.9 is nearly released, I think we could get back to
> > > > >>
> > > > >> FLIP-27.
> > > > >>
> > > > >> I
> > > > >>
> > > > >> believe it should be included in 1.10.
> > > > >>
> > > > >> There are so many things mentioned in document of FLIP-27. [1] I
> > > > >>
> > > > >> think
> > > > >>
> > > > >> we'd better discuss them separately. However the wiki is not a
> > > > >>
> > > > >> good
> > > > >>
> > > > >> place
> > > > >>
> > > > >> to discuss. I wrote google doc about SplitReader API which
> > > > >>
> > > > >> misses
> > > > >>
> > > > >> some
> > > > >>
> > > > >> details in the document. [2]
> > > > >>
> > > > >> 1.
> > > > >>
> > > > >>
> > > > >>
> > > >
> > >
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> > > > >>
> > > > >> 2.
> > > > >>
> > > > >>
> > > > >>
> > > >
> > >
> >
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> > > > >>
> > > > >> CC Stephan, Aljoscha, Piotrek, Becket
> > > > >>
> > > > >>
> > > > >> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email]> <
> > > > [hidden email]>
> > > > >>
> > > > >> wrote:
> > > > >>
> > > > >> Hi Steven,
> > > > >> Thank you for the feedback. Please take a look at the document
> > > > >>
> > > > >> FLIP-27
> > > > >>
> > > > >> <
> > > > >>
> > > > >>
> > > >
> > >
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> > > > >>
> > > > >> which
> > > > >>
> > > > >> is updated recently. A lot of details of enumerator were added
> > > > >>
> > > > >> in
> > > > >>
> > > > >> this
> > > > >>
> > > > >> document. I think it would help.
> > > > >>
> > > > >> Steven Wu <[hidden email]> <[hidden email]>
> > 于2019年3月28日周四
> > > > 下午12:52写道：
> > > > >>
> > > > >>
> > > > >> This proposal mentioned that SplitEnumerator might run on the
> > > > >> JobManager or
> > > > >> in a single task on a TaskManager.
> > > > >>
> > > > >> if enumerator is a single task on a taskmanager, then the job
> > > > >>
> > > > >> DAG
> > > > >>
> > > > >> can
> > > > >>
> > > > >> never
> > > > >> been embarrassingly parallel anymore. That will nullify the
> > > > >>
> > > > >> leverage
> > > > >>
> > > > >> of
> > > > >>
> > > > >> fine-grained recovery for embarrassingly parallel jobs.
> > > > >>
> > > > >> It's not clear to me what's the implication of running
> > > > >>
> > > > >> enumerator
> > > > >>
> > > > >> on
> > > > >>
> > > > >> the
> > > > >>
> > > > >> jobmanager. So I will leave that out for now.
> > > > >>
> > > > >> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email]> <
> > > > [hidden email]>
> > > > >>
> > > > >> wrote:
> > > > >>
> > > > >> Hi Stephan & Piotrek,
> > > > >>
> > > > >> Thank you for feedback.
> > > > >>
> > > > >> It seems that there are a lot of things to do in community.
> > > > >>
> > > > >> I
> > > > >>
> > > > >> am
> > > > >>
> > > > >> just
> > > > >>
> > > > >> afraid that this discussion may be forgotten since there so
> > > > >>
> > > > >> many
> > > > >>
> > > > >> proposals
> > > > >>
> > > > >> recently.
> > > > >> Anyway, wish to see the split topics soon :)
> > > > >>
> > > > >> Piotr Nowojski <[hidden email]> <[hidden email]>
> > > > 于2019年1月24日周四
> > > > >>
> > > > >> 下午8:21写道：
> > > > >>
> > > > >> Hi Biao!
> > > > >>
> > > > >> This discussion was stalled because of preparations for
> > > > >>
> > > > >> the
> > > > >>
> > > > >> open
> > > > >>
> > > > >> sourcing
> > > > >>
> > > > >> & merging Blink. I think before creating the tickets we
> > > > >>
> > > > >> should
> > > > >>
> > > > >> split this
> > > > >>
> > > > >> discussion into topics/areas outlined by Stephan and
> > > > >>
> > > > >> create
> > > > >>
> > > > >> Flips
> > > > >>
> > > > >> for
> > > > >>
> > > > >> that.
> > > > >>
> > > > >> I think there is no chance for this to be completed in
> > > > >>
> > > > >> couple
> > > > >>
> > > > >> of
> > > > >>
> > > > >> remaining
> > > > >>
> > > > >> weeks/1 month before 1.8 feature freeze, however it would
> > > > >>
> > > > >> be
> > > > >>
> > > > >> good
> > > > >>
> > > > >> to aim
> > > > >>
> > > > >> with those changes for 1.9.
> > > > >>
> > > > >> Piotrek
> > > > >>
> > > > >>
> > > > >> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email]> <
> > > > [hidden email]>
> > > > >>
> > > > >> wrote:
> > > > >>
> > > > >> Hi community,
> > > > >> The summary of Stephan makes a lot sense to me. It is
> > > > >>
> > > > >> much
> > > > >>
> > > > >> clearer
> > > > >>
> > > > >> indeed
> > > > >>
> > > > >> after splitting the complex topic into small ones.
> > > > >> I was wondering is there any detail plan for next step?
> > > > >>
> > > > >> If
> > > > >>
> > > > >> not,
> > > > >>
> > > > >> I
> > > > >>
> > > > >> would
> > > > >>
> > > > >> like to push this thing forward by creating some JIRA
> > > > >>
> > > > >> issues.
> > > > >>
> > > > >> Another question is that should version 1.8 include
> > > > >>
> > > > >> these
> > > > >>
> > > > >> features?
> > > > >>
> > > > >> Stephan Ewen <[hidden email]> <[hidden email]> 于2018年12月1日周六
> > > > 上午4:20写道：
> > > > >>
> > > > >>
> > > > >> Thanks everyone for the lively discussion. Let me try
> > > > >>
> > > > >> to
> > > > >>
> > > > >> summarize
> > > > >>
> > > > >> where I
> > > > >>
> > > > >> see convergence in the discussion and open issues.
> > > > >> I'll try to group this by design aspect of the source.
> > > > >>
> > > > >> Please
> > > > >>
> > > > >> let me
> > > > >>
> > > > >> know
> > > > >>
> > > > >> if I got things wrong or missed something crucial here.
> > > > >>
> > > > >> For issues 1-3, if the below reflects the state of the
> > > > >>
> > > > >> discussion, I
> > > > >>
> > > > >> would
> > > > >>
> > > > >> try and update the FLIP in the next days.
> > > > >> For the remaining ones we need more discussion.
> > > > >>
> > > > >> I would suggest to fork each of these aspects into a
> > > > >>
> > > > >> separate
> > > > >>
> > > > >> mail
> > > > >>
> > > > >> thread,
> > > > >>
> > > > >> or will loose sight of the individual aspects.
> > > > >>
> > > > >> *(1) Separation of Split Enumerator and Split Reader*
> > > > >>
> > > > >>  - All seem to agree this is a good thing
> > > > >>  - Split Enumerator could in the end live on JobManager
> > > > >>
> > > > >> (and
> > > > >>
> > > > >> assign
> > > > >>
> > > > >> splits
> > > > >>
> > > > >> via RPC) or in a task (and assign splits via data
> > > > >>
> > > > >> streams)
> > > > >>
> > > > >>  - this discussion is orthogonal and should come later,
> > > > >>
> > > > >> when
> > > > >>
> > > > >> the
> > > > >>
> > > > >> interface
> > > > >>
> > > > >> is agreed upon.
> > > > >>
> > > > >> *(2) Split Readers for one or more splits*
> > > > >>
> > > > >>  - Discussion seems to agree that we need to support
> > > > >>
> > > > >> one
> > > > >>
> > > > >> reader
> > > > >>
> > > > >> that
> > > > >>
> > > > >> possibly handles multiple splits concurrently.
> > > > >>  - The requirement comes from sources where one
> > > > >>
> > > > >> poll()-style
> > > > >>
> > > > >> call
> > > > >>
> > > > >> fetches
> > > > >>
> > > > >> data from different splits / partitions
> > > > >>    --> example sources that require that would be for
> > > > >>
> > > > >> example
> > > > >>
> > > > >> Kafka,
> > > > >>
> > > > >> Pravega, Pulsar
> > > > >>
> > > > >>  - Could have one split reader per source, or multiple
> > > > >>
> > > > >> split
> > > > >>
> > > > >> readers
> > > > >>
> > > > >> that
> > > > >>
> > > > >> share the "poll()" function
> > > > >>  - To not make it too complicated, we can start with
> > > > >>
> > > > >> thinking
> > > > >>
> > > > >> about
> > > > >>
> > > > >> one
> > > > >>
> > > > >> split reader for all splits initially and see if that
> > > > >>
> > > > >> covers
> > > > >>
> > > > >> all
> > > > >>
> > > > >> requirements
> > > > >>
> > > > >> *(3) Threading model of the Split Reader*
> > > > >>
> > > > >>  - Most active part of the discussion ;-)
> > > > >>
> > > > >>  - A non-blocking way for Flink's task code to interact
> > > > >>
> > > > >> with
> > > > >>
> > > > >> the
> > > > >>
> > > > >> source
> > > > >>
> > > > >> is
> > > > >>
> > > > >> needed in order to a task runtime code based on a
> > > > >> single-threaded/actor-style task design
> > > > >>    --> I personally am a big proponent of that, it will
> > > > >>
> > > > >> help
> > > > >>
> > > > >> with
> > > > >>
> > > > >> well-behaved checkpoints, efficiency, and simpler yet
> > > > >>
> > > > >> more
> > > > >>
> > > > >> robust
> > > > >>
> > > > >> runtime
> > > > >>
> > > > >> code
> > > > >>
> > > > >>  - Users care about simple abstraction, so as a
> > > > >>
> > > > >> subclass
> > > > >>
> > > > >> of
> > > > >>
> > > > >> SplitReader
> > > > >>
> > > > >> (non-blocking / async) we need to have a
> > > > >>
> > > > >> BlockingSplitReader
> > > > >>
> > > > >> which
> > > > >>
> > > > >> will
> > > > >>
> > > > >> form the basis of most source implementations.
> > > > >>
> > > > >> BlockingSplitReader
> > > > >>
> > > > >> lets
> > > > >>
> > > > >> users do blocking simple poll() calls.
> > > > >>  - The BlockingSplitReader would spawn a thread (or
> > > > >>
> > > > >> more)
> > > > >>
> > > > >> and
> > > > >>
> > > > >> the
> > > > >>
> > > > >> thread(s) can make blocking calls and hand over data
> > > > >>
> > > > >> buffers
> > > > >>
> > > > >> via
> > > > >>
> > > > >> a
> > > > >>
> > > > >> blocking
> > > > >>
> > > > >> queue
> > > > >>  - This should allow us to cover both, a fully async
> > > > >>
> > > > >> runtime,
> > > > >>
> > > > >> and a
> > > > >>
> > > > >> simple
> > > > >>
> > > > >> blocking interface for users.
> > > > >>  - This is actually very similar to how the Kafka
> > > > >>
> > > > >> connectors
> > > > >>
> > > > >> work.
> > > > >>
> > > > >> Kafka
> > > > >>
> > > > >> 9+ with one thread, Kafka 8 with multiple threads
> > > > >>
> > > > >>  - On the base SplitReader (the async one), the
> > > > >>
> > > > >> non-blocking
> > > > >>
> > > > >> method
> > > > >>
> > > > >> that
> > > > >>
> > > > >> gets the next chunk of data would signal data
> > > > >>
> > > > >> availability
> > > > >>
> > > > >> via
> > > > >>
> > > > >> a
> > > > >>
> > > > >> CompletableFuture, because that gives the best
> > > > >>
> > > > >> flexibility
> > > > >>
> > > > >> (can
> > > > >>
> > > > >> await
> > > > >>
> > > > >> completion or register notification handlers).
> > > > >>  - The source task would register a "thenHandle()" (or
> > > > >>
> > > > >> similar)
> > > > >>
> > > > >> on the
> > > > >>
> > > > >> future to put a "take next data" task into the
> > > > >>
> > > > >> actor-style
> > > > >>
> > > > >> mailbox
> > > > >>
> > > > >> *(4) Split Enumeration and Assignment*
> > > > >>
> > > > >>  - Splits may be generated lazily, both in cases where
> > > > >>
> > > > >> there
> > > > >>
> > > > >> is a
> > > > >>
> > > > >> limited
> > > > >>
> > > > >> number of splits (but very many), or splits are
> > > > >>
> > > > >> discovered
> > > > >>
> > > > >> over
> > > > >>
> > > > >> time
> > > > >>
> > > > >>  - Assignment should also be lazy, to get better load
> > > > >>
> > > > >> balancing
> > > > >>
> > > > >>  - Assignment needs support locality preferences
> > > > >>
> > > > >>  - Possible design based on discussion so far:
> > > > >>
> > > > >>    --> SplitReader has a method "addSplits(SplitT...)"
> > > > >>
> > > > >> to
> > > > >>
> > > > >> add
> > > > >>
> > > > >> one or
> > > > >>
> > > > >> more
> > > > >>
> > > > >> splits. Some split readers might assume they have only
> > > > >>
> > > > >> one
> > > > >>
> > > > >> split
> > > > >>
> > > > >> ever,
> > > > >>
> > > > >> concurrently, others assume multiple splits. (Note:
> > > > >>
> > > > >> idea
> > > > >>
> > > > >> behind
> > > > >>
> > > > >> being
> > > > >>
> > > > >> able
> > > > >>
> > > > >> to add multiple splits at the same time is to ease
> > > > >>
> > > > >> startup
> > > > >>
> > > > >> where
> > > > >>
> > > > >> multiple
> > > > >>
> > > > >> splits may be assigned instantly.)
> > > > >>    --> SplitReader has a context object on which it can
> > > > >>
> > > > >> call
> > > > >>
> > > > >> indicate
> > > > >>
> > > > >> when
> > > > >>
> > > > >> splits are completed. The enumerator gets that
> > > > >>
> > > > >> notification and
> > > > >>
> > > > >> can
> > > > >>
> > > > >> use
> > > > >>
> > > > >> to
> > > > >>
> > > > >> decide when to assign new splits. This should help both
> > > > >>
> > > > >> in
> > > > >>
> > > > >> cases
> > > > >>
> > > > >> of
> > > > >>
> > > > >> sources
> > > > >>
> > > > >> that take splits lazily (file readers) and in case the
> > > > >>
> > > > >> source
> > > > >>
> > > > >> needs to
> > > > >>
> > > > >> preserve a partial order between splits (Kinesis,
> > > > >>
> > > > >> Pravega,
> > > > >>
> > > > >> Pulsar may
> > > > >>
> > > > >> need
> > > > >>
> > > > >> that).
> > > > >>    --> SplitEnumerator gets notification when
> > > > >>
> > > > >> SplitReaders
> > > > >>
> > > > >> start
> > > > >>
> > > > >> and
> > > > >>
> > > > >> when
> > > > >>
> > > > >> they finish splits. They can decide at that moment to
> > > > >>
> > > > >> push
> > > > >>
> > > > >> more
> > > > >>
> > > > >> splits
> > > > >>
> > > > >> to
> > > > >>
> > > > >> that reader
> > > > >>    --> The SplitEnumerator should probably be aware of
> > > > >>
> > > > >> the
> > > > >>
> > > > >> source
> > > > >>
> > > > >> parallelism, to build its initial distribution.
> > > > >>
> > > > >>  - Open question: Should the source expose something
> > > > >>
> > > > >> like
> > > > >>
> > > > >> "host
> > > > >>
> > > > >> preferences", so that yarn/mesos/k8s can take this into
> > > > >>
> > > > >> account
> > > > >>
> > > > >> when
> > > > >>
> > > > >> selecting a node to start a TM on?
> > > > >>
> > > > >> *(5) Watermarks and event time alignment*
> > > > >>
> > > > >>  - Watermark generation, as well as idleness, needs to
> > > > >>
> > > > >> be
> > > > >>
> > > > >> per
> > > > >>
> > > > >> split
> > > > >>
> > > > >> (like
> > > > >>
> > > > >> currently in the Kafka Source, per partition)
> > > > >>  - It is desirable to support optional
> > > > >>
> > > > >> event-time-alignment,
> > > > >>
> > > > >> meaning
> > > > >>
> > > > >> that
> > > > >>
> > > > >> splits that are ahead are back-pressured or temporarily
> > > > >>
> > > > >> unsubscribed
> > > > >>
> > > > >>  - I think i would be desirable to encapsulate
> > > > >>
> > > > >> watermark
> > > > >>
> > > > >> generation
> > > > >>
> > > > >> logic
> > > > >>
> > > > >> in watermark generators, for a separation of concerns.
> > > > >>
> > > > >> The
> > > > >>
> > > > >> watermark
> > > > >>
> > > > >> generators should run per split.
> > > > >>  - Using watermark generators would also help with
> > > > >>
> > > > >> another
> > > > >>
> > > > >> problem of
> > > > >>
> > > > >> the
> > > > >>
> > > > >> suggested interface, namely supporting non-periodic
> > > > >>
> > > > >> watermarks
> > > > >>
> > > > >> efficiently.
> > > > >>
> > > > >>  - Need a way to "dispatch" next record to different
> > > > >>
> > > > >> watermark
> > > > >>
> > > > >> generators
> > > > >>
> > > > >>  - Need a way to tell SplitReader to "suspend" a split
> > > > >>
> > > > >> until a
> > > > >>
> > > > >> certain
> > > > >>
> > > > >> watermark is reached (event time backpressure)
> > > > >>  - This would in fact be not needed (and thus simpler)
> > > > >>
> > > > >> if
> > > > >>
> > > > >> we
> > > > >>
> > > > >> had
> > > > >>
> > > > >> a
> > > > >>
> > > > >> SplitReader per split and may be a reason to re-open
> > > > >>
> > > > >> that
> > > > >>
> > > > >> discussion
> > > > >>
> > > > >> *(6) Watermarks across splits and in the Split
> > > > >>
> > > > >> Enumerator*
> > > > >>
> > > > >>  - The split enumerator may need some watermark
> > > > >>
> > > > >> awareness,
> > > > >>
> > > > >> which
> > > > >>
> > > > >> should
> > > > >>
> > > > >> be
> > > > >>
> > > > >> purely based on split metadata (like create timestamp
> > > > >>
> > > > >> of
> > > > >>
> > > > >> file
> > > > >>
> > > > >> splits)
> > > > >>
> > > > >>  - If there are still more splits with overlapping
> > > > >>
> > > > >> event
> > > > >>
> > > > >> time
> > > > >>
> > > > >> range
> > > > >>
> > > > >> for
> > > > >>
> > > > >> a
> > > > >>
> > > > >> split reader, then that split reader should not advance
> > > > >>
> > > > >> the
> > > > >>
> > > > >> watermark
> > > > >>
> > > > >> within the split beyond the overlap boundary. Otherwise
> > > > >>
> > > > >> future
> > > > >>
> > > > >> splits
> > > > >>
> > > > >> will
> > > > >>
> > > > >> produce late data.
> > > > >>
> > > > >>  - One way to approach this could be that the split
> > > > >>
> > > > >> enumerator
> > > > >>
> > > > >> may
> > > > >>
> > > > >> send
> > > > >>
> > > > >> watermarks to the readers, and the readers cannot emit
> > > > >>
> > > > >> watermarks
> > > > >>
> > > > >> beyond
> > > > >>
> > > > >> that received watermark.
> > > > >>  - Many split enumerators would simply immediately send
> > > > >>
> > > > >> Long.MAX
> > > > >>
> > > > >> out
> > > > >>
> > > > >> and
> > > > >>
> > > > >> leave the progress purely to the split readers.
> > > > >>
> > > > >>  - For event-time alignment / split back pressure, this
> > > > >>
> > > > >> begs
> > > > >>
> > > > >> the
> > > > >>
> > > > >> question
> > > > >>
> > > > >> how we can avoid deadlocks that may arise when splits
> > > > >>
> > > > >> are
> > > > >>
> > > > >> suspended
> > > > >>
> > > > >> for
> > > > >>
> > > > >> event time back pressure,
> > > > >>
> > > > >> *(7) Batch and streaming Unification*
> > > > >>
> > > > >>  - Functionality wise, the above design should support
> > > > >>
> > > > >> both
> > > > >>
> > > > >>  - Batch often (mostly) does not care about reading "in
> > > > >>
> > > > >> order"
> > > > >>
> > > > >> and
> > > > >>
> > > > >> generating watermarks
> > > > >>    --> Might use different enumerator logic that is
> > > > >>
> > > > >> more
> > > > >>
> > > > >> locality
> > > > >>
> > > > >> aware
> > > > >>
> > > > >> and ignores event time order
> > > > >>    --> Does not generate watermarks
> > > > >>  - Would be great if bounded sources could be
> > > > >>
> > > > >> identified
> > > > >>
> > > > >> at
> > > > >>
> > > > >> compile
> > > > >>
> > > > >> time,
> > > > >>
> > > > >> so that "env.addBoundedSource(...)" is type safe and
> > > > >>
> > > > >> can
> > > > >>
> > > > >> return a
> > > > >>
> > > > >> "BoundedDataStream".
> > > > >>  - Possible to defer this discussion until later
> > > > >>
> > > > >> *Miscellaneous Comments*
> > > > >>
> > > > >>  - Should the source have a TypeInformation for the
> > > > >>
> > > > >> produced
> > > > >>
> > > > >> type,
> > > > >>
> > > > >> instead
> > > > >>
> > > > >> of a serializer? We need a type information in the
> > > > >>
> > > > >> stream
> > > > >>
> > > > >> anyways, and
> > > > >>
> > > > >> can
> > > > >>
> > > > >> derive the serializer from that. Plus, creating the
> > > > >>
> > > > >> serializer
> > > > >>
> > > > >> should
> > > > >>
> > > > >> respect the ExecutionConfig.
> > > > >>
> > > > >>  - The TypeSerializer interface is very powerful but
> > > > >>
> > > > >> also
> > > > >>
> > > > >> not
> > > > >>
> > > > >> easy to
> > > > >>
> > > > >> implement. Its purpose is to handle data super
> > > > >>
> > > > >> efficiently,
> > > > >>
> > > > >> support
> > > > >>
> > > > >> flexible ways of evolution, etc.
> > > > >>  For metadata I would suggest to look at the
> > > > >>
> > > > >> SimpleVersionedSerializer
> > > > >>
> > > > >> instead, which is used for example for checkpoint
> > > > >>
> > > > >> master
> > > > >>
> > > > >> hooks,
> > > > >>
> > > > >> or for
> > > > >>
> > > > >> the
> > > > >>
> > > > >> streaming file sink. I think that is is a good match
> > > > >>
> > > > >> for
> > > > >>
> > > > >> cases
> > > > >>
> > > > >> where
> > > > >>
> > > > >> we
> > > > >>
> > > > >> do
> > > > >>
> > > > >> not need more than ser/deser (no copy, etc.) and don't
> > > > >>
> > > > >> need to
> > > > >>
> > > > >> push
> > > > >>
> > > > >> versioning out of the serialization paths for best
> > > > >>
> > > > >> performance
> > > > >>
> > > > >> (as in
> > > > >>
> > > > >> the
> > > > >>
> > > > >> TypeSerializer)
> > > > >>
> > > > >>
> > > > >> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
> > > > [hidden email]>
> > > > >> wrote:
> > > > >>
> > > > >>
> > > > >> Hi Biao,
> > > > >>
> > > > >> Thanks for the answer!
> > > > >>
> > > > >> So given the multi-threaded readers, now we have as
> > > > >>
> > > > >> open
> > > > >>
> > > > >> questions:
> > > > >>
> > > > >> 1) How do we let the checkpoints pass through our
> > > > >>
> > > > >> multi-threaded
> > > > >>
> > > > >> reader
> > > > >>
> > > > >> operator?
> > > > >>
> > > > >> 2) Do we have separate reader and source operators or
> > > > >>
> > > > >> not? In
> > > > >>
> > > > >> the
> > > > >>
> > > > >> strategy
> > > > >>
> > > > >> that has a separate source, the source operator has a
> > > > >>
> > > > >> parallelism of
> > > > >>
> > > > >> 1
> > > > >>
> > > > >> and
> > > > >>
> > > > >> is responsible for split recovery only.
> > > > >>
> > > > >> For the first one, given also the constraints
> > > > >>
> > > > >> (blocking,
> > > > >>
> > > > >> finite
> > > > >>
> > > > >> queues,
> > > > >>
> > > > >> etc), I do not have an answer yet.
> > > > >>
> > > > >> For the 2nd, I think that we should go with separate
> > > > >>
> > > > >> operators
> > > > >>
> > > > >> for
> > > > >>
> > > > >> the
> > > > >>
> > > > >> source and the readers, for the following reasons:
> > > > >>
> > > > >> 1) This is more aligned with a potential future
> > > > >>
> > > > >> improvement
> > > > >>
> > > > >> where the
> > > > >>
> > > > >> split
> > > > >>
> > > > >> discovery becomes a responsibility of the JobManager
> > > > >>
> > > > >> and
> > > > >>
> > > > >> readers are
> > > > >>
> > > > >> pooling more work from the JM.
> > > > >>
> > > > >> 2) The source is going to be the "single point of
> > > > >>
> > > > >> truth".
> > > > >>
> > > > >> It
> > > > >>
> > > > >> will
> > > > >>
> > > > >> know
> > > > >>
> > > > >> what
> > > > >>
> > > > >> has been processed and what not. If the source and the
> > > > >>
> > > > >> readers
> > > > >>
> > > > >> are a
> > > > >>
> > > > >> single
> > > > >>
> > > > >> operator with parallelism > 1, or in general, if the
> > > > >>
> > > > >> split
> > > > >>
> > > > >> discovery
> > > > >>
> > > > >> is
> > > > >>
> > > > >> done by each task individually, then:
> > > > >>   i) we have to have a deterministic scheme for each
> > > > >>
> > > > >> reader to
> > > > >>
> > > > >> assign
> > > > >>
> > > > >> splits to itself (e.g. mod subtaskId). This is not
> > > > >>
> > > > >> necessarily
> > > > >>
> > > > >> trivial
> > > > >>
> > > > >> for
> > > > >>
> > > > >> all sources.
> > > > >>   ii) each reader would have to keep a copy of all its
> > > > >>
> > > > >> processed
> > > > >>
> > > > >> slpits
> > > > >>
> > > > >>   iii) the state has to be a union state with a
> > > > >>
> > > > >> non-trivial
> > > > >>
> > > > >> merging
> > > > >>
> > > > >> logic
> > > > >>
> > > > >> in order to support rescaling.
> > > > >>
> > > > >> Two additional points that you raised above:
> > > > >>
> > > > >> i) The point that you raised that we need to keep all
> > > > >>
> > > > >> splits
> > > > >>
> > > > >> (processed
> > > > >>
> > > > >> and
> > > > >>
> > > > >> not-processed) I think is a bit of a strong
> > > > >>
> > > > >> requirement.
> > > > >>
> > > > >> This
> > > > >>
> > > > >> would
> > > > >>
> > > > >> imply
> > > > >>
> > > > >> that for infinite sources the state will grow
> > > > >>
> > > > >> indefinitely.
> > > > >>
> > > > >> This is
> > > > >>
> > > > >> problem
> > > > >>
> > > > >> is even more pronounced if we do not have a single
> > > > >>
> > > > >> source
> > > > >>
> > > > >> that
> > > > >>
> > > > >> assigns
> > > > >>
> > > > >> splits to readers, as each reader will have its own
> > > > >>
> > > > >> copy
> > > > >>
> > > > >> of
> > > > >>
> > > > >> the
> > > > >>
> > > > >> state.
> > > > >>
> > > > >> ii) it is true that for finite sources we need to
> > > > >>
> > > > >> somehow
> > > > >>
> > > > >> not
> > > > >>
> > > > >> close
> > > > >>
> > > > >> the
> > > > >>
> > > > >> readers when the source/split discoverer finishes. The
> > > > >> ContinuousFileReaderOperator has a work-around for
> > > > >>
> > > > >> that.
> > > > >>
> > > > >> It is
> > > > >>
> > > > >> not
> > > > >>
> > > > >> elegant,
> > > > >>
> > > > >> and checkpoints are not emitted after closing the
> > > > >>
> > > > >> source,
> > > > >>
> > > > >> but
> > > > >>
> > > > >> this, I
> > > > >>
> > > > >> believe, is a bigger problem which requires more
> > > > >>
> > > > >> changes
> > > > >>
> > > > >> than
> > > > >>
> > > > >> just
> > > > >>
> > > > >> refactoring the source interface.
> > > > >>
> > > > >> Cheers,
> > > > >> Kostas
> > > > >>
> > > > >>
> > > > >>
> > > >
> > > >
> > >
> >
> >
> > --
> > Best, Jingsong Lee
> >
>

[dwysakowicz]

Hi Becket,

Issue #1 - Design of Source interface

I mentioned the lack of a method like Source#createEnumerator(Boundedness boundedness, SplitEnumeratorContext context), because without the current proposal is not complete/does not work.

If we say that boundedness is an intrinsic property of a source imo we don't need the Source#createEnumerator(Boundedness boundedness, SplitEnumeratorContext context) method.

Assuming a source from my previous example:

Source source = KafkaSource.builder()
  ...
  .untilTimestamp(...)
  .build()

Would the enumerator differ if created like source.createEnumerator(CONTINUOUS_UNBOUNDED, ...) vs source .createEnumerator(BOUNDED, ...)? I know I am repeating myself, but this is the part that my opinion differ the most from the current proposal. I really think it should always be the source that tells if it is bounded or not. In the current proposal methods continousSource/boundedSource somewhat reconfigure the source, which I think is misleading.

I think a call like:

Source source = KafkaSource.builder()
  ...
  .readContinously() / readUntilLatestOffset() / readUntilTimestamp / readUntilOffsets / ...
  .build()

is way cleaner (and expressive) than

Source source = KafkaSource.builder()
  ...
  .build()

env.continousSource(source) // which actually underneath would call createEnumerator(CONTINUOUS, ctx) which would be equivalent to source.readContinously().createEnumerator(ctx)
// or
env.boundedSource(source) // which actually underneath would call createEnumerator(BOUNDED, ctx) which would be equivalent to source.readUntilLatestOffset().createEnumerator(ctx)

Sorry for the comparison, but to me it seems there is too much magic happening underneath those two calls.

I really believe the Source interface should have getBoundedness method instead of (supportBoundedness) + createEnumerator(Boundedness, ...)

Issue #2 - Design of ExecutionEnvironment#source()/continuousSource()/boundedSource()

As you might have guessed I am slightly in favor of option #2 modified. Yes I am aware every step of the dag would have to be able to say if it is bounded or not. I have a feeling it would be easier to express cross bounded/unbounded operations, but I must admit I have not thought it through thoroughly, In the spirit of batch is just a special case of streaming I thought BoundedStream would extend from DataStream. Correct me if I am wrong. In such a setup the cross bounded/unbounded operation could be expressed quite easily I think:

DataStream {
  DataStream join(DataStream, ...); // we could not really tell if the result is bounded or not, but because bounded stream is a special case of unbounded the API object is correct, irrespective if the left or right side of the join is bounded
}

BoundedStream extends DataStream {
  BoundedStream join(BoundedStream, ...); // only if both sides are bounded the result can be bounded as well. However we do have access to the DataStream#join here, so you can still join with a DataStream
}

On the other hand I also see benefits of two completely disjointed APIs, as we could prohibit some streaming calls in the bounded API. I can't think of any unbounded operators that could not be implemented for bounded stream.

Besides I think we both agree we don't like the method:

DataStream boundedStream(Source)

suggested in the current state of the FLIP. Do we ? :)

Best,

Dawid

On 10/12/2019 18:57, Becket Qin wrote:

Hi folks,

Thanks for the discussion, great feedback. Also thanks Dawid for the
explanation, it is much clearer now.

One thing that is indeed missing from the FLIP is how the boundedness is
passed to the Source implementation. So the API should be
Source#createEnumerator(Boundedness boundedness, SplitEnumeratorContext
context)
And we can probably remove the Source#supportBoundedness(Boundedness
boundedness) method.

Assuming we have that, we are essentially choosing from one of the
following two options:

Option 1:
// The source is continuous source, and only unbounded operations can be
performed.
DataStream<Type> datastream = env.continuousSource(someSource);

// The source is bounded source, both bounded and unbounded operations can
be performed.
BoundedDataStream<Type> boundedDataStream = env.boundedSource(someSource);

  - Pros:
       a) explicit boundary between bounded / unbounded streams, it is
quite simple and clear to the users.
  - Cons:
       a) For applications that do not involve bounded operations, they
still have to call different API to distinguish bounded / unbounded streams.
       b) No support for bounded stream to run in a streaming runtime
setting, i.e. scheduling and operators behaviors.


Option 2:
// The source is either bounded or unbounded, but only unbounded operations
could be performed on the returned DataStream.
DataStream<Type> dataStream = env.source(someSource);

// The source must be a bounded source, otherwise exception is thrown.
BoundedDataStream<Type> boundedDataStream =
env.boundedSource(boundedSource);

The pros and cons are exactly the opposite of option 1.
  - Pros:
       a) For applications that do not involve bounded operations, they
still have to call different API to distinguish bounded / unbounded streams.
       b) Support for bounded stream to run in a streaming runtime setting,
i.e. scheduling and operators behaviors.
  - Cons:
       a) Bounded / unbounded streams are kind of mixed, i.e. given a
DataStream, it is not clear whether it is bounded or not, unless you have
the access to its source.


If we only think from the Source API perspective, option 2 seems a better
choice because functionality wise it is a superset of option 1, at the cost
of some seemingly acceptable ambiguity in the DataStream API.
But if we look at the DataStream API as a whole, option 1 seems a clearer
choice. For example, some times a library may have to know whether a
certain task will finish or not. And it would be difficult to tell if the
input is a DataStream, unless additional information is provided all the
way from the Source. One possible solution is to have a *modified option 2*
which adds a method to the DataStream API to indicate boundedness, such as
getBoundedness(). It would solve the problem with a potential confusion of
what is difference between a DataStream with getBoundedness()=true and a
BoundedDataStream. But that seems not super difficult to explain.

So from API's perspective, I don't have a strong opinion between *option 1*
and *modified option 2. *I like the cleanness of option 1, but modified
option 2 would be more attractive if we have concrete use case for the
"Bounded stream with unbounded streaming runtime settings".

Re: Till

Maybe this has already been asked before but I was wondering why the
SourceReader interface has the method pollNext which hands the
responsibility of outputting elements to the SourceReader implementation?
Has this been done for backwards compatibility reasons with the old source
interface? If not, then one could define a Collection<E> getNextRecords()
method which returns the currently retrieved records and then the caller
emits them outside of the SourceReader. That way the interface would not
allow to implement an outputting loop where we never hand back control to
the caller. At the moment, this contract can be easily broken and is only
mentioned loosely in the JavaDocs.

The primary reason we handover the SourceOutput to the SourceReader is
because sometimes it is difficult for a SourceReader to emit one record at
a time. One example is some batched messaging systems which only have an
offset for the entire batch instead of individual messages in the batch. In
that case, returning one record at a time would leave the SourceReader in
an uncheckpointable state because they can only checkpoint at the batch
boundaries.

Thanks,

Jiangjie (Becket) Qin

On Tue, Dec 10, 2019 at 5:33 PM Till Rohrmann [hidden email] wrote:

Hi everyone,

thanks for drafting this FLIP. It reads very well.

Concerning Dawid's proposal, I tend to agree. The boundedness could come
from the source and tell the system how to treat the operator (scheduling
wise). From a user's perspective it should be fine to get back a DataStream
when calling env.source(boundedSource) if he does not need special
operations defined on a BoundedDataStream. If he needs this, then one could
use the method BoundedDataStream env.boundedSource(boundedSource).

If possible, we could enforce the proper usage of env.boundedSource() by
introducing a BoundedSource type so that one cannot pass an
unbounded source to it. That way users would not be able to shoot
themselves in the foot.

Maybe this has already been asked before but I was wondering why the
SourceReader interface has the method pollNext which hands the
responsibility of outputting elements to the SourceReader implementation?
Has this been done for backwards compatibility reasons with the old source
interface? If not, then one could define a Collection<E> getNextRecords()
method which returns the currently retrieved records and then the caller
emits them outside of the SourceReader. That way the interface would not
allow to implement an outputting loop where we never hand back control to
the caller. At the moment, this contract can be easily broken and is only
mentioned loosely in the JavaDocs.

Cheers,
Till

On Tue, Dec 10, 2019 at 7:49 AM Jingsong Li [hidden email]
wrote:

Hi all,

I think current design is good.

My understanding is:

For execution mode: bounded mode and continuous mode, It's totally
different. I don't think we have the ability to integrate the two models

at

present. It's about scheduling, memory, algorithms, States, etc. we
shouldn't confuse them.

For source capabilities: only bounded, only continuous, both bounded and
continuous.
I think Kafka is a source that can be ran both bounded
and continuous execution mode.
And Kafka with end offset should be ran both bounded
and continuous execution mode.  Using apache Beam with Flink runner, I

used

to run a "bounded" Kafka in streaming mode. For our previous DataStream,

it

is not necessarily required that the source cannot be bounded.

So it is my thought for Dawid's question:
1.pass a bounded source to continuousSource() +1
2.pass a continuous source to boundedSource() -1, should throw exception.

In StreamExecutionEnvironment, continuousSource and boundedSource define
the execution mode. It defines a clear boundary of execution mode.

Best,
Jingsong Lee

On Tue, Dec 10, 2019 at 10:37 AM Jark Wu [hidden email] wrote:

I agree with Dawid's point that the boundedness information should come
from the source itself (e.g. the end timestamp), not through
env.boundedSouce()/continuousSource().
I think if we want to support something like `env.source()` that derive

the

execution mode from source, `supportsBoundedness(Boundedness)`
method is not enough, because we don't know whether it is bounded or

not.

Best,
Jark


On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz [hidden email]
wrote:

One more thing. In the current proposal, with the
supportsBoundedness(Boundedness) method and the boundedness coming

from

either continuousSource or boundedSource I could not find how this
information is fed back to the SplitEnumerator.

Best,

Dawid

On 09/12/2019 13:52, Becket Qin wrote:

Hi Dawid,

Thanks for the comments. This actually brings another relevant

question

about what does a "bounded source" imply. I actually had the same
impression when I look at the Source API. Here is what I understand

after

some discussion with Stephan. The bounded source has the following

impacts.

1. API validity.
- A bounded source generates a bounded stream so some operations

that

only

works for bounded records would be performed, e.g. sort.
- To expose these bounded stream only APIs, there are two options:
     a. Add them to the DataStream API and throw exception if a

method

is

called on an unbounded stream.
     b. Create a BoundedDataStream class which is returned from
env.boundedSource(), while DataStream is returned from

env.continousSource().

Note that this cannot be done by having single

env.source(theSource)

even

the Source has a getBoundedness() method.

2. Scheduling
- A bounded source could be computed stage by stage without

bringing

up

all

the tasks at the same time.

3. Operator behaviors
- A bounded source indicates the records are finite so some

operators

can

wait until it receives all the records before it starts the

processing.

In the above impact, only 1 is relevant to the API design. And the

current

proposal in FLIP-27 is following 1.b.

// boundedness depends of source property, imo this should always

be

preferred

DataStream<MyType> stream = env.source(theSource);


In your proposal, does DataStream have bounded stream only methods?

It

looks it should have, otherwise passing a bounded Source to

env.source()

would be confusing. In that case, we will essentially do 1.a if an
unbounded Source is created from env.source(unboundedSource).

If we have the methods only supported for bounded streams in

DataStream,

it

seems a little weird to have a separate BoundedDataStream

interface.

Am I understand it correctly?

Thanks,

Jiangjie (Becket) Qin



On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <

[hidden email]>

wrote:

Hi all,

Really well written proposal and very important one. I must admit

I

have

not understood all the intricacies of it yet.

One question I have though is about where does the information

about

boundedness come from. I think in most cases it is a property of

the

source. As you described it might be e.g. end offset, a flag

should

it

monitor new splits etc. I think it would be a really nice use case

to

be

able to say:

new KafkaSource().readUntil(long timestamp),

which could work as an "end offset". Moreover I think all Bounded

sources

support continuous mode, but no intrinsically continuous source

support

the

Bounded mode. If I understood the proposal correctly it suggest

the

boundedness sort of "comes" from the outside of the source, from

the

invokation of either boundedStream or continousSource.

I am wondering if it would make sense to actually change the

method

boolean Source#supportsBoundedness(Boundedness)

to

Boundedness Source#getBoundedness().

As for the methods #boundedSource, #continousSource, assuming the
boundedness is property of the source they do not affect how the

enumerator

works, but mostly how the dag is scheduled, right? I am not

against

those

methods, but I think it is a very specific use case to actually

override

the property of the source. In general I would expect users to

only

call

env.source(theSource), where the source tells if it is bounded or

not. I

would suggest considering following set of methods:

// boundedness depends of source property, imo this should always

be

preferred

DataStream<MyType> stream = env.source(theSource);


// always continous execution, whether bounded or unbounded source

DataStream<MyType> boundedStream = env.continousSource(theSource);

// imo this would make sense if the BoundedDataStream provides

additional features unavailable for continous mode

BoundedDataStream<MyType> batch = env.boundedSource(theSource);


Best,

Dawid


On 04/12/2019 11:25, Stephan Ewen wrote:

Thanks, Becket, for updating this.

I agree with moving the aspects you mentioned into separate FLIPs

-

this

one way becoming unwieldy in size.

+1 to the FLIP in its current state. Its a very detailed write-up,

nicely

done!

On Wed, Dec 4, 2019 at 7:38 AM Becket Qin [hidden email]

<

[hidden email]> wrote:

Hi all,

Sorry for the long belated update. I have updated FLIP-27 wiki

page

with

the latest proposals. Some noticeable changes include:
1. A new generic communication mechanism between SplitEnumerator

and

SourceReader.
2. Some detail API method signature changes.

We left a few things out of this FLIP and will address them in

separate

FLIPs. Including:
1. Per split event time.
2. Event time alignment.
3. Fine grained failover for SplitEnumerator failure.

Please let us know if you have any question.

Thanks,

Jiangjie (Becket) Qin

On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen [hidden email] <

[hidden email]> wrote:

Hi  Łukasz!

Becket and me are working hard on figuring out the last details

and

implementing the first PoC. We would update the FLIP hopefully

next

week.

There is a fair chance that a first version of this will be in

1.10,

but

I

think it will take another release to battle test it and migrate

the

connectors.

Best,
Stephan




On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <[hidden email]

<

[hidden email]>

wrote:

Hi,

This proposal looks very promising for us. Do you have any plans

in

which

Flink release it is going to be released? We are thinking on

using a

Data

Set API for our future use cases but on the other hand Data Set

API

is

going to be deprecated so using proposed bounded data streams

solution

could be more viable in the long term.

Thanks,
Łukasz

On 2019/10/01 15:48:03, Thomas Weise [hidden email] <

[hidden email]> wrote:

Thanks for putting together this proposal!

I see that the "Per Split Event Time" and "Event Time Alignment"

sections

are still TBD.

It would probably be good to flesh those out a bit before

proceeding

too

far

as the event time alignment will probably influence the

interaction

with

the split reader, specifically ReaderStatus

emitNext(SourceOutput<E>

output).

We currently have only one implementation for event time alignment

in

the

Kinesis consumer. The synchronization in that case takes place as

the

last

step before records are emitted downstream (RecordEmitter). With

the

currently proposed interfaces, the equivalent can be implemented

in

the

reader loop, although note that in the Kinesis consumer the per

shard

threads push records.

Synchronization has not been implemented for the Kafka consumer

yet.

https://issues.apache.org/jira/browse/FLINK-12675

When I looked at it, I realized that the implementation will look

quite

different
from Kinesis because it needs to take place in the pull part,

where

records

are taken from the Kafka client. Due to the multiplexing it cannot

be

done

by blocking the split thread like it currently works for Kinesis.

Reading

from individual Kafka partitions needs to be controlled via

pause/resume

on the Kafka client.

To take on that responsibility the split thread would need to be

aware

of

the
watermarks or at least whether it should or should not continue to

consume

a given split and this may require a different SourceReader or

SourceOutput

interface.

Thanks,
Thomas


On Fri, Jul 26, 2019 at 1:39 AM Biao Liu [hidden email] <

[hidden email]> wrote:

Hi Stephan,

Thank you for feedback!
Will take a look at your branch before public discussing.


On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen [hidden email]

<

[hidden email]>

wrote:

Hi Biao!

Thanks for reviving this. I would like to join this discussion,

but

am

quite occupied with the 1.9 release, so can we maybe pause this

discussion

for a week or so?

In the meantime I can share some suggestion based on prior

experiments:

How to do watermarks / timestamp extractors in a simpler and more

flexible

way. I think that part is quite promising should be part of the

new

source

interface.

https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime

https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java

Some experiments on how to build the source reader and its

library

for

common threading/split patterns:

https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src

Best,
Stephan


On Thu, Jul 25, 2019 at 10:03 AM Biao Liu [hidden email] <

[hidden email]>

wrote:

Hi devs,

Since 1.9 is nearly released, I think we could get back to

FLIP-27.

I

believe it should be included in 1.10.

There are so many things mentioned in document of FLIP-27. [1] I

think

we'd better discuss them separately. However the wiki is not a

good

place

to discuss. I wrote google doc about SplitReader API which

misses

some

details in the document. [2]

1.

https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface

2.

https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing

CC Stephan, Aljoscha, Piotrek, Becket


On Thu, Mar 28, 2019 at 4:38 PM Biao Liu [hidden email] <

[hidden email]>

wrote:

Hi Steven,
Thank you for the feedback. Please take a look at the document

FLIP-27

<

https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface

which

is updated recently. A lot of details of enumerator were added

in

this

document. I think it would help.

Steven Wu [hidden email] [hidden email]

于2019年3月28日周四

下午12:52写道：

This proposal mentioned that SplitEnumerator might run on the
JobManager or
in a single task on a TaskManager.

if enumerator is a single task on a taskmanager, then the job

DAG

can

never
been embarrassingly parallel anymore. That will nullify the

leverage

of

fine-grained recovery for embarrassingly parallel jobs.

It's not clear to me what's the implication of running

enumerator

on

the

jobmanager. So I will leave that out for now.

On Mon, Jan 28, 2019 at 3:05 AM Biao Liu [hidden email] <

[hidden email]>

wrote:

Hi Stephan & Piotrek,

Thank you for feedback.

It seems that there are a lot of things to do in community.

I

am

just

afraid that this discussion may be forgotten since there so

many

proposals

recently.
Anyway, wish to see the split topics soon :)

Piotr Nowojski [hidden email] [hidden email]

于2019年1月24日周四

下午8:21写道：

Hi Biao!

This discussion was stalled because of preparations for

the

open

sourcing

& merging Blink. I think before creating the tickets we

should

split this

discussion into topics/areas outlined by Stephan and

create

Flips

for

that.

I think there is no chance for this to be completed in

couple

of

remaining

weeks/1 month before 1.8 feature freeze, however it would

be

good

to aim

with those changes for 1.9.

Piotrek


On 20 Jan 2019, at 16:08, Biao Liu [hidden email] <

[hidden email]>

wrote:

Hi community,
The summary of Stephan makes a lot sense to me. It is

much

clearer

indeed

after splitting the complex topic into small ones.
I was wondering is there any detail plan for next step?

If

not,

I

would

like to push this thing forward by creating some JIRA

issues.

Another question is that should version 1.8 include

these

features?

Stephan Ewen [hidden email] [hidden email] 于2018年12月1日周六

上午4:20写道：

Thanks everyone for the lively discussion. Let me try

to

summarize

where I

see convergence in the discussion and open issues.
I'll try to group this by design aspect of the source.

Please

let me

know

if I got things wrong or missed something crucial here.

For issues 1-3, if the below reflects the state of the

discussion, I

would

try and update the FLIP in the next days.
For the remaining ones we need more discussion.

I would suggest to fork each of these aspects into a

separate

mail

thread,

or will loose sight of the individual aspects.

*(1) Separation of Split Enumerator and Split Reader*

 - All seem to agree this is a good thing
 - Split Enumerator could in the end live on JobManager

(and

assign

splits

via RPC) or in a task (and assign splits via data

streams)

 - this discussion is orthogonal and should come later,

when

the

interface

is agreed upon.

*(2) Split Readers for one or more splits*

 - Discussion seems to agree that we need to support

one

reader

that

possibly handles multiple splits concurrently.
 - The requirement comes from sources where one

poll()-style

call

fetches

data from different splits / partitions
   --> example sources that require that would be for

example

Kafka,

Pravega, Pulsar

 - Could have one split reader per source, or multiple

split

readers

that

share the "poll()" function
 - To not make it too complicated, we can start with

thinking

about

one

split reader for all splits initially and see if that

covers

all

requirements

*(3) Threading model of the Split Reader*

 - Most active part of the discussion ;-)

 - A non-blocking way for Flink's task code to interact

with

the

source

is

needed in order to a task runtime code based on a
single-threaded/actor-style task design
   --> I personally am a big proponent of that, it will

help

with

well-behaved checkpoints, efficiency, and simpler yet

more

robust

runtime

code

 - Users care about simple abstraction, so as a

subclass

of

SplitReader

(non-blocking / async) we need to have a

BlockingSplitReader

which

will

form the basis of most source implementations.

BlockingSplitReader

lets

users do blocking simple poll() calls.
 - The BlockingSplitReader would spawn a thread (or

more)

and

the

thread(s) can make blocking calls and hand over data

buffers

via

a

blocking

queue
 - This should allow us to cover both, a fully async

runtime,

and a

simple

blocking interface for users.
 - This is actually very similar to how the Kafka

connectors

work.

Kafka

9+ with one thread, Kafka 8 with multiple threads

 - On the base SplitReader (the async one), the

non-blocking

method

that

gets the next chunk of data would signal data

availability

via

a

CompletableFuture, because that gives the best

flexibility

(can

await

completion or register notification handlers).
 - The source task would register a "thenHandle()" (or

similar)

on the

future to put a "take next data" task into the

actor-style

mailbox

*(4) Split Enumeration and Assignment*

 - Splits may be generated lazily, both in cases where

there

is a

limited

number of splits (but very many), or splits are

discovered

over

time

 - Assignment should also be lazy, to get better load

balancing

 - Assignment needs support locality preferences

 - Possible design based on discussion so far:

   --> SplitReader has a method "addSplits(SplitT...)"

to

add

one or

more

splits. Some split readers might assume they have only

one

split

ever,

concurrently, others assume multiple splits. (Note:

idea

behind

being

able

to add multiple splits at the same time is to ease

startup

where

multiple

splits may be assigned instantly.)
   --> SplitReader has a context object on which it can

call

indicate

when

splits are completed. The enumerator gets that

notification and

can

use

to

decide when to assign new splits. This should help both

in

cases

of

sources

that take splits lazily (file readers) and in case the

source

needs to

preserve a partial order between splits (Kinesis,

Pravega,

Pulsar may

need

that).
   --> SplitEnumerator gets notification when

SplitReaders

start

and

when

they finish splits. They can decide at that moment to

push

more

splits

to

that reader
   --> The SplitEnumerator should probably be aware of

the

source

parallelism, to build its initial distribution.

 - Open question: Should the source expose something

like

"host

preferences", so that yarn/mesos/k8s can take this into

account

when

selecting a node to start a TM on?

*(5) Watermarks and event time alignment*

 - Watermark generation, as well as idleness, needs to

be

per

split

(like

currently in the Kafka Source, per partition)
 - It is desirable to support optional

event-time-alignment,

meaning

that

splits that are ahead are back-pressured or temporarily

unsubscribed

 - I think i would be desirable to encapsulate

watermark

generation

logic

in watermark generators, for a separation of concerns.

The

watermark

generators should run per split.
 - Using watermark generators would also help with

another

problem of

the

suggested interface, namely supporting non-periodic

watermarks

efficiently.

 - Need a way to "dispatch" next record to different

watermark

generators

 - Need a way to tell SplitReader to "suspend" a split

until a

certain

watermark is reached (event time backpressure)
 - This would in fact be not needed (and thus simpler)

if

we

had

a

SplitReader per split and may be a reason to re-open

that

discussion

*(6) Watermarks across splits and in the Split

Enumerator*

 - The split enumerator may need some watermark

awareness,

which

should

be

purely based on split metadata (like create timestamp

of

file

splits)

 - If there are still more splits with overlapping

event

time

range

for

a

split reader, then that split reader should not advance

the

watermark

within the split beyond the overlap boundary. Otherwise

future

splits

will

produce late data.

 - One way to approach this could be that the split

enumerator

may

send

watermarks to the readers, and the readers cannot emit

watermarks

beyond

that received watermark.
 - Many split enumerators would simply immediately send

Long.MAX

out

and

leave the progress purely to the split readers.

 - For event-time alignment / split back pressure, this

begs

the

question

how we can avoid deadlocks that may arise when splits

are

suspended

for

event time back pressure,

*(7) Batch and streaming Unification*

 - Functionality wise, the above design should support

both

 - Batch often (mostly) does not care about reading "in

order"

and

generating watermarks
   --> Might use different enumerator logic that is

more

locality

aware

and ignores event time order
   --> Does not generate watermarks
 - Would be great if bounded sources could be

identified

at

compile

time,

so that "env.addBoundedSource(...)" is type safe and

can

return a

"BoundedDataStream".
 - Possible to defer this discussion until later

*Miscellaneous Comments*

 - Should the source have a TypeInformation for the

produced

type,

instead

of a serializer? We need a type information in the

stream

anyways, and

can

derive the serializer from that. Plus, creating the

serializer

should

respect the ExecutionConfig.

 - The TypeSerializer interface is very powerful but

also

not

easy to

implement. Its purpose is to handle data super

efficiently,

support

flexible ways of evolution, etc.
 For metadata I would suggest to look at the

SimpleVersionedSerializer

instead, which is used for example for checkpoint

master

hooks,

or for

the

streaming file sink. I think that is is a good match

for

cases

where

we

do

not need more than ser/deser (no copy, etc.) and don't

need to

push

versioning out of the serialization paths for best

performance

(as in

the

TypeSerializer)


On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <

[hidden email]>

wrote:


Hi Biao,

Thanks for the answer!

So given the multi-threaded readers, now we have as

open

questions:

1) How do we let the checkpoints pass through our

multi-threaded

reader

operator?

2) Do we have separate reader and source operators or

not? In

the

strategy

that has a separate source, the source operator has a

parallelism of

1

and

is responsible for split recovery only.

For the first one, given also the constraints

(blocking,

finite

queues,

etc), I do not have an answer yet.

For the 2nd, I think that we should go with separate

operators

for

the

source and the readers, for the following reasons:

1) This is more aligned with a potential future

improvement

where the

split

discovery becomes a responsibility of the JobManager

and

readers are

pooling more work from the JM.

2) The source is going to be the "single point of

truth".

It

will

know

what

has been processed and what not. If the source and the

readers

are a

single

operator with parallelism > 1, or in general, if the

split

discovery

is

done by each task individually, then:
  i) we have to have a deterministic scheme for each

reader to

assign

splits to itself (e.g. mod subtaskId). This is not

necessarily

trivial

for

all sources.
  ii) each reader would have to keep a copy of all its

processed

slpits

  iii) the state has to be a union state with a

non-trivial

merging

logic

in order to support rescaling.

Two additional points that you raised above:

i) The point that you raised that we need to keep all

splits

(processed

and

not-processed) I think is a bit of a strong

requirement.

This

would

imply

that for infinite sources the state will grow

indefinitely.

This is

problem

is even more pronounced if we do not have a single

source

that

assigns

splits to readers, as each reader will have its own

copy

of

the

state.

ii) it is true that for finite sources we need to

somehow

not

close

the

readers when the source/split discoverer finishes. The
ContinuousFileReaderOperator has a work-around for

that.

It is

not

elegant,

and checkpoints are not emitted after closing the

source,

but

this, I

believe, is a bigger problem which requires more

changes

than

just

refactoring the source interface.

Cheers,
Kostas

--
Best, Jingsong Lee

[Till Rohrmann]

Hi Becket,

quick clarification from my side because I think you misunderstood my
question. I did not suggest to let the SourceReader return only a single
record at a time when calling getNextRecords. As the return type indicates,
the method can return an arbitrary number of records.

Cheers,
Till

On Wed, Dec 11, 2019 at 10:13 AM Dawid Wysakowicz <[hidden email]>
wrote:

> Hi Becket,
>
> Issue #1 - Design of Source interface
>
> I mentioned the lack of a method like Source#createEnumerator(Boundedness
> boundedness, SplitEnumeratorContext context), because without the current
> proposal is not complete/does not work.
>
> If we say that boundedness is an intrinsic property of a source imo we
> don't need the Source#createEnumerator(Boundedness boundedness,
> SplitEnumeratorContext context) method.
>
> Assuming a source from my previous example:
>
> Source source = KafkaSource.builder()
>   ...
>   .untilTimestamp(...)
>   .build()
>
> Would the enumerator differ if created like
> source.createEnumerator(CONTINUOUS_UNBOUNDED, ...) vs source
> .createEnumerator(BOUNDED, ...)? I know I am repeating myself, but this is
> the part that my opinion differ the most from the current proposal. I
> really think it should always be the source that tells if it is bounded or
> not. In the current proposal methods continousSource/boundedSource somewhat
> reconfigure the source, which I think is misleading.
>
> I think a call like:
>
> Source source = KafkaSource.builder()
>   ...
>   .readContinously() / readUntilLatestOffset() / readUntilTimestamp / readUntilOffsets / ...
>   .build()
>
> is way cleaner (and expressive) than
>
> Source source = KafkaSource.builder()
>   ...
>   .build()
>
>
> env.continousSource(source) // which actually underneath would call createEnumerator(CONTINUOUS, ctx) which would be equivalent to source.readContinously().createEnumerator(ctx)
> // or
> env.boundedSource(source) // which actually underneath would call createEnumerator(BOUNDED, ctx) which would be equivalent to source.readUntilLatestOffset().createEnumerator(ctx)
>
>
> Sorry for the comparison, but to me it seems there is too much magic
> happening underneath those two calls.
>
> I really believe the Source interface should have getBoundedness method
> instead of (supportBoundedness) + createEnumerator(Boundedness, ...)
>
>
> Issue #2 - Design of
> ExecutionEnvironment#source()/continuousSource()/boundedSource()
>
> As you might have guessed I am slightly in favor of option #2 modified.
> Yes I am aware every step of the dag would have to be able to say if it is
> bounded or not. I have a feeling it would be easier to express cross
> bounded/unbounded operations, but I must admit I have not thought it
> through thoroughly, In the spirit of batch is just a special case of
> streaming I thought BoundedStream would extend from DataStream. Correct me
> if I am wrong. In such a setup the cross bounded/unbounded operation could
> be expressed quite easily I think:
>
> DataStream {
>   DataStream join(DataStream, ...); // we could not really tell if the result is bounded or not, but because bounded stream is a special case of unbounded the API object is correct, irrespective if the left or right side of the join is bounded
> }
>
> BoundedStream extends DataStream {
>   BoundedStream join(BoundedStream, ...); // only if both sides are bounded the result can be bounded as well. However we do have access to the DataStream#join here, so you can still join with a DataStream
> }
>
>
> On the other hand I also see benefits of two completely disjointed APIs,
> as we could prohibit some streaming calls in the bounded API. I can't think
> of any unbounded operators that could not be implemented for bounded stream.
>
> Besides I think we both agree we don't like the method:
>
> DataStream boundedStream(Source)
>
> suggested in the current state of the FLIP. Do we ? :)
>
> Best,
>
> Dawid
>
> On 10/12/2019 18:57, Becket Qin wrote:
>
> Hi folks,
>
> Thanks for the discussion, great feedback. Also thanks Dawid for the
> explanation, it is much clearer now.
>
> One thing that is indeed missing from the FLIP is how the boundedness is
> passed to the Source implementation. So the API should be
> Source#createEnumerator(Boundedness boundedness, SplitEnumeratorContext
> context)
> And we can probably remove the Source#supportBoundedness(Boundedness
> boundedness) method.
>
> Assuming we have that, we are essentially choosing from one of the
> following two options:
>
> Option 1:
> // The source is continuous source, and only unbounded operations can be
> performed.
> DataStream<Type> datastream = env.continuousSource(someSource);
>
> // The source is bounded source, both bounded and unbounded operations can
> be performed.
> BoundedDataStream<Type> boundedDataStream = env.boundedSource(someSource);
>
>   - Pros:
>        a) explicit boundary between bounded / unbounded streams, it is
> quite simple and clear to the users.
>   - Cons:
>        a) For applications that do not involve bounded operations, they
> still have to call different API to distinguish bounded / unbounded streams.
>        b) No support for bounded stream to run in a streaming runtime
> setting, i.e. scheduling and operators behaviors.
>
>
> Option 2:
> // The source is either bounded or unbounded, but only unbounded operations
> could be performed on the returned DataStream.
> DataStream<Type> dataStream = env.source(someSource);
>
> // The source must be a bounded source, otherwise exception is thrown.
> BoundedDataStream<Type> boundedDataStream =
> env.boundedSource(boundedSource);
>
> The pros and cons are exactly the opposite of option 1.
>   - Pros:
>        a) For applications that do not involve bounded operations, they
> still have to call different API to distinguish bounded / unbounded streams.
>        b) Support for bounded stream to run in a streaming runtime setting,
> i.e. scheduling and operators behaviors.
>   - Cons:
>        a) Bounded / unbounded streams are kind of mixed, i.e. given a
> DataStream, it is not clear whether it is bounded or not, unless you have
> the access to its source.
>
>
> If we only think from the Source API perspective, option 2 seems a better
> choice because functionality wise it is a superset of option 1, at the cost
> of some seemingly acceptable ambiguity in the DataStream API.
> But if we look at the DataStream API as a whole, option 1 seems a clearer
> choice. For example, some times a library may have to know whether a
> certain task will finish or not. And it would be difficult to tell if the
> input is a DataStream, unless additional information is provided all the
> way from the Source. One possible solution is to have a *modified option 2*
> which adds a method to the DataStream API to indicate boundedness, such as
> getBoundedness(). It would solve the problem with a potential confusion of
> what is difference between a DataStream with getBoundedness()=true and a
> BoundedDataStream. But that seems not super difficult to explain.
>
> So from API's perspective, I don't have a strong opinion between *option 1*
> and *modified option 2. *I like the cleanness of option 1, but modified
> option 2 would be more attractive if we have concrete use case for the
> "Bounded stream with unbounded streaming runtime settings".
>
> Re: Till
>
>
> Maybe this has already been asked before but I was wondering why the
> SourceReader interface has the method pollNext which hands the
> responsibility of outputting elements to the SourceReader implementation?
> Has this been done for backwards compatibility reasons with the old source
> interface? If not, then one could define a Collection<E> getNextRecords()
> method which returns the currently retrieved records and then the caller
> emits them outside of the SourceReader. That way the interface would not
> allow to implement an outputting loop where we never hand back control to
> the caller. At the moment, this contract can be easily broken and is only
> mentioned loosely in the JavaDocs.
>
>
> The primary reason we handover the SourceOutput to the SourceReader is
> because sometimes it is difficult for a SourceReader to emit one record at
> a time. One example is some batched messaging systems which only have an
> offset for the entire batch instead of individual messages in the batch. In
> that case, returning one record at a time would leave the SourceReader in
> an uncheckpointable state because they can only checkpoint at the batch
> boundaries.
>
> Thanks,
>
> Jiangjie (Becket) Qin
>
> On Tue, Dec 10, 2019 at 5:33 PM Till Rohrmann <[hidden email]> <[hidden email]> wrote:
>
>
> Hi everyone,
>
> thanks for drafting this FLIP. It reads very well.
>
> Concerning Dawid's proposal, I tend to agree. The boundedness could come
> from the source and tell the system how to treat the operator (scheduling
> wise). From a user's perspective it should be fine to get back a DataStream
> when calling env.source(boundedSource) if he does not need special
> operations defined on a BoundedDataStream. If he needs this, then one could
> use the method BoundedDataStream env.boundedSource(boundedSource).
>
> If possible, we could enforce the proper usage of env.boundedSource() by
> introducing a BoundedSource type so that one cannot pass an
> unbounded source to it. That way users would not be able to shoot
> themselves in the foot.
>
> Maybe this has already been asked before but I was wondering why the
> SourceReader interface has the method pollNext which hands the
> responsibility of outputting elements to the SourceReader implementation?
> Has this been done for backwards compatibility reasons with the old source
> interface? If not, then one could define a Collection<E> getNextRecords()
> method which returns the currently retrieved records and then the caller
> emits them outside of the SourceReader. That way the interface would not
> allow to implement an outputting loop where we never hand back control to
> the caller. At the moment, this contract can be easily broken and is only
> mentioned loosely in the JavaDocs.
>
> Cheers,
> Till
>
> On Tue, Dec 10, 2019 at 7:49 AM Jingsong Li <[hidden email]> <[hidden email]>
> wrote:
>
>
> Hi all,
>
> I think current design is good.
>
> My understanding is:
>
> For execution mode: bounded mode and continuous mode, It's totally
> different. I don't think we have the ability to integrate the two models
>
> at
>
> present. It's about scheduling, memory, algorithms, States, etc. we
> shouldn't confuse them.
>
> For source capabilities: only bounded, only continuous, both bounded and
> continuous.
> I think Kafka is a source that can be ran both bounded
> and continuous execution mode.
> And Kafka with end offset should be ran both bounded
> and continuous execution mode.  Using apache Beam with Flink runner, I
>
> used
>
> to run a "bounded" Kafka in streaming mode. For our previous DataStream,
>
> it
>
> is not necessarily required that the source cannot be bounded.
>
> So it is my thought for Dawid's question:
> 1.pass a bounded source to continuousSource() +1
> 2.pass a continuous source to boundedSource() -1, should throw exception.
>
> In StreamExecutionEnvironment, continuousSource and boundedSource define
> the execution mode. It defines a clear boundary of execution mode.
>
> Best,
> Jingsong Lee
>
> On Tue, Dec 10, 2019 at 10:37 AM Jark Wu <[hidden email]> <[hidden email]> wrote:
>
>
> I agree with Dawid's point that the boundedness information should come
> from the source itself (e.g. the end timestamp), not through
> env.boundedSouce()/continuousSource().
> I think if we want to support something like `env.source()` that derive
>
> the
>
> execution mode from source, `supportsBoundedness(Boundedness)`
> method is not enough, because we don't know whether it is bounded or
>
> not.
>
> Best,
> Jark
>
>
> On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <[hidden email]> <[hidden email]>
> wrote:
>
>
> One more thing. In the current proposal, with the
> supportsBoundedness(Boundedness) method and the boundedness coming
>
> from
>
> either continuousSource or boundedSource I could not find how this
> information is fed back to the SplitEnumerator.
>
> Best,
>
> Dawid
>
> On 09/12/2019 13:52, Becket Qin wrote:
>
> Hi Dawid,
>
> Thanks for the comments. This actually brings another relevant
>
> question
>
> about what does a "bounded source" imply. I actually had the same
> impression when I look at the Source API. Here is what I understand
>
> after
>
> some discussion with Stephan. The bounded source has the following
>
> impacts.
>
> 1. API validity.
> - A bounded source generates a bounded stream so some operations
>
> that
>
> only
>
> works for bounded records would be performed, e.g. sort.
> - To expose these bounded stream only APIs, there are two options:
>      a. Add them to the DataStream API and throw exception if a
>
> method
>
> is
>
> called on an unbounded stream.
>      b. Create a BoundedDataStream class which is returned from
> env.boundedSource(), while DataStream is returned from
>
> env.continousSource().
>
> Note that this cannot be done by having single
>
> env.source(theSource)
>
> even
>
> the Source has a getBoundedness() method.
>
> 2. Scheduling
> - A bounded source could be computed stage by stage without
>
> bringing
>
> up
>
> all
>
> the tasks at the same time.
>
> 3. Operator behaviors
> - A bounded source indicates the records are finite so some
>
> operators
>
> can
>
> wait until it receives all the records before it starts the
>
> processing.
>
> In the above impact, only 1 is relevant to the API design. And the
>
> current
>
> proposal in FLIP-27 is following 1.b.
>
> // boundedness depends of source property, imo this should always
>
> be
>
> preferred
>
>
> DataStream<MyType> stream = env.source(theSource);
>
>
> In your proposal, does DataStream have bounded stream only methods?
>
> It
>
> looks it should have, otherwise passing a bounded Source to
>
> env.source()
>
> would be confusing. In that case, we will essentially do 1.a if an
> unbounded Source is created from env.source(unboundedSource).
>
> If we have the methods only supported for bounded streams in
>
> DataStream,
>
> it
>
> seems a little weird to have a separate BoundedDataStream
>
> interface.
>
> Am I understand it correctly?
>
> Thanks,
>
> Jiangjie (Becket) Qin
>
>
>
> On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <
>
> [hidden email]>
>
> wrote:
>
>
> Hi all,
>
> Really well written proposal and very important one. I must admit
>
> I
>
> have
>
> not understood all the intricacies of it yet.
>
> One question I have though is about where does the information
>
> about
>
> boundedness come from. I think in most cases it is a property of
>
> the
>
> source. As you described it might be e.g. end offset, a flag
>
> should
>
> it
>
> monitor new splits etc. I think it would be a really nice use case
>
> to
>
> be
>
> able to say:
>
> new KafkaSource().readUntil(long timestamp),
>
> which could work as an "end offset". Moreover I think all Bounded
>
> sources
>
> support continuous mode, but no intrinsically continuous source
>
> support
>
> the
>
> Bounded mode. If I understood the proposal correctly it suggest
>
> the
>
> boundedness sort of "comes" from the outside of the source, from
>
> the
>
> invokation of either boundedStream or continousSource.
>
> I am wondering if it would make sense to actually change the
>
> method
>
> boolean Source#supportsBoundedness(Boundedness)
>
> to
>
> Boundedness Source#getBoundedness().
>
> As for the methods #boundedSource, #continousSource, assuming the
> boundedness is property of the source they do not affect how the
>
> enumerator
>
> works, but mostly how the dag is scheduled, right? I am not
>
> against
>
> those
>
> methods, but I think it is a very specific use case to actually
>
> override
>
> the property of the source. In general I would expect users to
>
> only
>
> call
>
> env.source(theSource), where the source tells if it is bounded or
>
> not. I
>
> would suggest considering following set of methods:
>
> // boundedness depends of source property, imo this should always
>
> be
>
> preferred
>
> DataStream<MyType> stream = env.source(theSource);
>
>
> // always continous execution, whether bounded or unbounded source
>
> DataStream<MyType> boundedStream = env.continousSource(theSource);
>
> // imo this would make sense if the BoundedDataStream provides
>
> additional features unavailable for continous mode
>
> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
>
>
> Best,
>
> Dawid
>
>
> On 04/12/2019 11:25, Stephan Ewen wrote:
>
> Thanks, Becket, for updating this.
>
> I agree with moving the aspects you mentioned into separate FLIPs
>
> -
>
> this
>
> one way becoming unwieldy in size.
>
> +1 to the FLIP in its current state. Its a very detailed write-up,
>
> nicely
>
> done!
>
> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]> <[hidden email]>
>
> <
>
> [hidden email]> wrote:
>
> Hi all,
>
> Sorry for the long belated update. I have updated FLIP-27 wiki
>
> page
>
> with
>
> the latest proposals. Some noticeable changes include:
> 1. A new generic communication mechanism between SplitEnumerator
>
> and
>
> SourceReader.
> 2. Some detail API method signature changes.
>
> We left a few things out of this FLIP and will address them in
>
> separate
>
> FLIPs. Including:
> 1. Per split event time.
> 2. Event time alignment.
> 3. Fine grained failover for SplitEnumerator failure.
>
> Please let us know if you have any question.
>
> Thanks,
>
> Jiangjie (Becket) Qin
>
> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]> <[hidden email]> <
>
> [hidden email]> wrote:
>
> Hi  Łukasz!
>
> Becket and me are working hard on figuring out the last details
>
> and
>
> implementing the first PoC. We would update the FLIP hopefully
>
> next
>
> week.
>
> There is a fair chance that a first version of this will be in
>
> 1.10,
>
> but
>
> I
>
> think it will take another release to battle test it and migrate
>
> the
>
> connectors.
>
> Best,
> Stephan
>
>
>
>
> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <[hidden email]
>
> <
>
> [hidden email]>
>
> wrote:
>
> Hi,
>
> This proposal looks very promising for us. Do you have any plans
>
> in
>
> which
>
> Flink release it is going to be released? We are thinking on
>
> using a
>
> Data
>
> Set API for our future use cases but on the other hand Data Set
>
> API
>
> is
>
> going to be deprecated so using proposed bounded data streams
>
> solution
>
> could be more viable in the long term.
>
> Thanks,
> Łukasz
>
> On 2019/10/01 15:48:03, Thomas Weise <[hidden email]> <[hidden email]> <
>
> [hidden email]> wrote:
>
> Thanks for putting together this proposal!
>
> I see that the "Per Split Event Time" and "Event Time Alignment"
>
> sections
>
> are still TBD.
>
> It would probably be good to flesh those out a bit before
>
> proceeding
>
> too
>
> far
>
> as the event time alignment will probably influence the
>
> interaction
>
> with
>
> the split reader, specifically ReaderStatus
>
> emitNext(SourceOutput<E>
>
> output).
>
> We currently have only one implementation for event time alignment
>
> in
>
> the
>
> Kinesis consumer. The synchronization in that case takes place as
>
> the
>
> last
>
> step before records are emitted downstream (RecordEmitter). With
>
> the
>
> currently proposed interfaces, the equivalent can be implemented
>
> in
>
> the
>
> reader loop, although note that in the Kinesis consumer the per
>
> shard
>
> threads push records.
>
> Synchronization has not been implemented for the Kafka consumer
>
> yet.
>
> https://issues.apache.org/jira/browse/FLINK-12675
>
> When I looked at it, I realized that the implementation will look
>
> quite
>
> different
> from Kinesis because it needs to take place in the pull part,
>
> where
>
> records
>
> are taken from the Kafka client. Due to the multiplexing it cannot
>
> be
>
> done
>
> by blocking the split thread like it currently works for Kinesis.
>
> Reading
>
> from individual Kafka partitions needs to be controlled via
>
> pause/resume
>
> on the Kafka client.
>
> To take on that responsibility the split thread would need to be
>
> aware
>
> of
>
> the
> watermarks or at least whether it should or should not continue to
>
> consume
>
> a given split and this may require a different SourceReader or
>
> SourceOutput
>
> interface.
>
> Thanks,
> Thomas
>
>
> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email]> <[hidden email]> <
>
> [hidden email]> wrote:
>
> Hi Stephan,
>
> Thank you for feedback!
> Will take a look at your branch before public discussing.
>
>
> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]> <[hidden email]>
>
> <
>
> [hidden email]>
>
> wrote:
>
> Hi Biao!
>
> Thanks for reviving this. I would like to join this discussion,
>
> but
>
> am
>
> quite occupied with the 1.9 release, so can we maybe pause this
>
> discussion
>
> for a week or so?
>
> In the meantime I can share some suggestion based on prior
>
> experiments:
>
> How to do watermarks / timestamp extractors in a simpler and more
>
> flexible
>
> way. I think that part is quite promising should be part of the
>
> new
>
> source
>
> interface.
>
>
>
>
>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
>
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
>
> Some experiments on how to build the source reader and its
>
> library
>
> for
>
> common threading/split patterns:
>
>
>
>
>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
>
> Best,
> Stephan
>
>
> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]> <[hidden email]> <
>
> [hidden email]>
>
> wrote:
>
> Hi devs,
>
> Since 1.9 is nearly released, I think we could get back to
>
> FLIP-27.
>
> I
>
> believe it should be included in 1.10.
>
> There are so many things mentioned in document of FLIP-27. [1] I
>
> think
>
> we'd better discuss them separately. However the wiki is not a
>
> good
>
> place
>
> to discuss. I wrote google doc about SplitReader API which
>
> misses
>
> some
>
> details in the document. [2]
>
> 1.
>
>
>
>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
>
> 2.
>
>
>
>
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
>
> CC Stephan, Aljoscha, Piotrek, Becket
>
>
> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email]> <[hidden email]> <
>
> [hidden email]>
>
> wrote:
>
> Hi Steven,
> Thank you for the feedback. Please take a look at the document
>
> FLIP-27
>
> <
>
>
>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
>
> which
>
> is updated recently. A lot of details of enumerator were added
>
> in
>
> this
>
> document. I think it would help.
>
> Steven Wu <[hidden email]> <[hidden email]> <[hidden email]> <[hidden email]>
>
> 于2019年3月28日周四
>
> 下午12:52写道：
>
> This proposal mentioned that SplitEnumerator might run on the
> JobManager or
> in a single task on a TaskManager.
>
> if enumerator is a single task on a taskmanager, then the job
>
> DAG
>
> can
>
> never
> been embarrassingly parallel anymore. That will nullify the
>
> leverage
>
> of
>
> fine-grained recovery for embarrassingly parallel jobs.
>
> It's not clear to me what's the implication of running
>
> enumerator
>
> on
>
> the
>
> jobmanager. So I will leave that out for now.
>
> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email]> <[hidden email]> <
>
> [hidden email]>
>
> wrote:
>
> Hi Stephan & Piotrek,
>
> Thank you for feedback.
>
> It seems that there are a lot of things to do in community.
>
> I
>
> am
>
> just
>
> afraid that this discussion may be forgotten since there so
>
> many
>
> proposals
>
> recently.
> Anyway, wish to see the split topics soon :)
>
> Piotr Nowojski <[hidden email]> <[hidden email]> <[hidden email]> <[hidden email]>
>
> 于2019年1月24日周四
>
> 下午8:21写道：
>
> Hi Biao!
>
> This discussion was stalled because of preparations for
>
> the
>
> open
>
> sourcing
>
> & merging Blink. I think before creating the tickets we
>
> should
>
> split this
>
> discussion into topics/areas outlined by Stephan and
>
> create
>
> Flips
>
> for
>
> that.
>
> I think there is no chance for this to be completed in
>
> couple
>
> of
>
> remaining
>
> weeks/1 month before 1.8 feature freeze, however it would
>
> be
>
> good
>
> to aim
>
> with those changes for 1.9.
>
> Piotrek
>
>
> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email]> <[hidden email]> <
>
> [hidden email]>
>
> wrote:
>
> Hi community,
> The summary of Stephan makes a lot sense to me. It is
>
> much
>
> clearer
>
> indeed
>
> after splitting the complex topic into small ones.
> I was wondering is there any detail plan for next step?
>
> If
>
> not,
>
> I
>
> would
>
> like to push this thing forward by creating some JIRA
>
> issues.
>
> Another question is that should version 1.8 include
>
> these
>
> features?
>
> Stephan Ewen <[hidden email]> <[hidden email]> <[hidden email]> <[hidden email]> 于2018年12月1日周六
>
> 上午4:20写道：
>
> Thanks everyone for the lively discussion. Let me try
>
> to
>
> summarize
>
> where I
>
> see convergence in the discussion and open issues.
> I'll try to group this by design aspect of the source.
>
> Please
>
> let me
>
> know
>
> if I got things wrong or missed something crucial here.
>
> For issues 1-3, if the below reflects the state of the
>
> discussion, I
>
> would
>
> try and update the FLIP in the next days.
> For the remaining ones we need more discussion.
>
> I would suggest to fork each of these aspects into a
>
> separate
>
> mail
>
> thread,
>
> or will loose sight of the individual aspects.
>
> *(1) Separation of Split Enumerator and Split Reader*
>
>  - All seem to agree this is a good thing
>  - Split Enumerator could in the end live on JobManager
>
> (and
>
> assign
>
> splits
>
> via RPC) or in a task (and assign splits via data
>
> streams)
>
>  - this discussion is orthogonal and should come later,
>
> when
>
> the
>
> interface
>
> is agreed upon.
>
> *(2) Split Readers for one or more splits*
>
>  - Discussion seems to agree that we need to support
>
> one
>
> reader
>
> that
>
> possibly handles multiple splits concurrently.
>  - The requirement comes from sources where one
>
> poll()-style
>
> call
>
> fetches
>
> data from different splits / partitions
>    --> example sources that require that would be for
>
> example
>
> Kafka,
>
> Pravega, Pulsar
>
>  - Could have one split reader per source, or multiple
>
> split
>
> readers
>
> that
>
> share the "poll()" function
>  - To not make it too complicated, we can start with
>
> thinking
>
> about
>
> one
>
> split reader for all splits initially and see if that
>
> covers
>
> all
>
> requirements
>
> *(3) Threading model of the Split Reader*
>
>  - Most active part of the discussion ;-)
>
>  - A non-blocking way for Flink's task code to interact
>
> with
>
> the
>
> source
>
> is
>
> needed in order to a task runtime code based on a
> single-threaded/actor-style task design
>    --> I personally am a big proponent of that, it will
>
> help
>
> with
>
> well-behaved checkpoints, efficiency, and simpler yet
>
> more
>
> robust
>
> runtime
>
> code
>
>  - Users care about simple abstraction, so as a
>
> subclass
>
> of
>
> SplitReader
>
> (non-blocking / async) we need to have a
>
> BlockingSplitReader
>
> which
>
> will
>
> form the basis of most source implementations.
>
> BlockingSplitReader
>
> lets
>
> users do blocking simple poll() calls.
>  - The BlockingSplitReader would spawn a thread (or
>
> more)
>
> and
>
> the
>
> thread(s) can make blocking calls and hand over data
>
> buffers
>
> via
>
> a
>
> blocking
>
> queue
>  - This should allow us to cover both, a fully async
>
> runtime,
>
> and a
>
> simple
>
> blocking interface for users.
>  - This is actually very similar to how the Kafka
>
> connectors
>
> work.
>
> Kafka
>
> 9+ with one thread, Kafka 8 with multiple threads
>
>  - On the base SplitReader (the async one), the
>
> non-blocking
>
> method
>
> that
>
> gets the next chunk of data would signal data
>
> availability
>
> via
>
> a
>
> CompletableFuture, because that gives the best
>
> flexibility
>
> (can
>
> await
>
> completion or register notification handlers).
>  - The source task would register a "thenHandle()" (or
>
> similar)
>
> on the
>
> future to put a "take next data" task into the
>
> actor-style
>
> mailbox
>
> *(4) Split Enumeration and Assignment*
>
>  - Splits may be generated lazily, both in cases where
>
> there
>
> is a
>
> limited
>
> number of splits (but very many), or splits are
>
> discovered
>
> over
>
> time
>
>  - Assignment should also be lazy, to get better load
>
> balancing
>
>  - Assignment needs support locality preferences
>
>  - Possible design based on discussion so far:
>
>    --> SplitReader has a method "addSplits(SplitT...)"
>
> to
>
> add
>
> one or
>
> more
>
> splits. Some split readers might assume they have only
>
> one
>
> split
>
> ever,
>
> concurrently, others assume multiple splits. (Note:
>
> idea
>
> behind
>
> being
>
> able
>
> to add multiple splits at the same time is to ease
>
> startup
>
> where
>
> multiple
>
> splits may be assigned instantly.)
>    --> SplitReader has a context object on which it can
>
> call
>
> indicate
>
> when
>
> splits are completed. The enumerator gets that
>
> notification and
>
> can
>
> use
>
> to
>
> decide when to assign new splits. This should help both
>
> in
>
> cases
>
> of
>
> sources
>
> that take splits lazily (file readers) and in case the
>
> source
>
> needs to
>
> preserve a partial order between splits (Kinesis,
>
> Pravega,
>
> Pulsar may
>
> need
>
> that).
>    --> SplitEnumerator gets notification when
>
> SplitReaders
>
> start
>
> and
>
> when
>
> they finish splits. They can decide at that moment to
>
> push
>
> more
>
> splits
>
> to
>
> that reader
>    --> The SplitEnumerator should probably be aware of
>
> the
>
> source
>
> parallelism, to build its initial distribution.
>
>  - Open question: Should the source expose something
>
> like
>
> "host
>
> preferences", so that yarn/mesos/k8s can take this into
>
> account
>
> when
>
> selecting a node to start a TM on?
>
> *(5) Watermarks and event time alignment*
>
>  - Watermark generation, as well as idleness, needs to
>
> be
>
> per
>
> split
>
> (like
>
> currently in the Kafka Source, per partition)
>  - It is desirable to support optional
>
> event-time-alignment,
>
> meaning
>
> that
>
> splits that are ahead are back-pressured or temporarily
>
> unsubscribed
>
>  - I think i would be desirable to encapsulate
>
> watermark
>
> generation
>
> logic
>
> in watermark generators, for a separation of concerns.
>
> The
>
> watermark
>
> generators should run per split.
>  - Using watermark generators would also help with
>
> another
>
> problem of
>
> the
>
> suggested interface, namely supporting non-periodic
>
> watermarks
>
> efficiently.
>
>  - Need a way to "dispatch" next record to different
>
> watermark
>
> generators
>
>  - Need a way to tell SplitReader to "suspend" a split
>
> until a
>
> certain
>
> watermark is reached (event time backpressure)
>  - This would in fact be not needed (and thus simpler)
>
> if
>
> we
>
> had
>
> a
>
> SplitReader per split and may be a reason to re-open
>
> that
>
> discussion
>
> *(6) Watermarks across splits and in the Split
>
> Enumerator*
>
>  - The split enumerator may need some watermark
>
> awareness,
>
> which
>
> should
>
> be
>
> purely based on split metadata (like create timestamp
>
> of
>
> file
>
> splits)
>
>  - If there are still more splits with overlapping
>
> event
>
> time
>
> range
>
> for
>
> a
>
> split reader, then that split reader should not advance
>
> the
>
> watermark
>
> within the split beyond the overlap boundary. Otherwise
>
> future
>
> splits
>
> will
>
> produce late data.
>
>  - One way to approach this could be that the split
>
> enumerator
>
> may
>
> send
>
> watermarks to the readers, and the readers cannot emit
>
> watermarks
>
> beyond
>
> that received watermark.
>  - Many split enumerators would simply immediately send
>
> Long.MAX
>
> out
>
> and
>
> leave the progress purely to the split readers.
>
>  - For event-time alignment / split back pressure, this
>
> begs
>
> the
>
> question
>
> how we can avoid deadlocks that may arise when splits
>
> are
>
> suspended
>
> for
>
> event time back pressure,
>
> *(7) Batch and streaming Unification*
>
>  - Functionality wise, the above design should support
>
> both
>
>  - Batch often (mostly) does not care about reading "in
>
> order"
>
> and
>
> generating watermarks
>    --> Might use different enumerator logic that is
>
> more
>
> locality
>
> aware
>
> and ignores event time order
>    --> Does not generate watermarks
>  - Would be great if bounded sources could be
>
> identified
>
> at
>
> compile
>
> time,
>
> so that "env.addBoundedSource(...)" is type safe and
>
> can
>
> return a
>
> "BoundedDataStream".
>  - Possible to defer this discussion until later
>
> *Miscellaneous Comments*
>
>  - Should the source have a TypeInformation for the
>
> produced
>
> type,
>
> instead
>
> of a serializer? We need a type information in the
>
> stream
>
> anyways, and
>
> can
>
> derive the serializer from that. Plus, creating the
>
> serializer
>
> should
>
> respect the ExecutionConfig.
>
>  - The TypeSerializer interface is very powerful but
>
> also
>
> not
>
> easy to
>
> implement. Its purpose is to handle data super
>
> efficiently,
>
> support
>
> flexible ways of evolution, etc.
>  For metadata I would suggest to look at the
>
> SimpleVersionedSerializer
>
> instead, which is used for example for checkpoint
>
> master
>
> hooks,
>
> or for
>
> the
>
> streaming file sink. I think that is is a good match
>
> for
>
> cases
>
> where
>
> we
>
> do
>
> not need more than ser/deser (no copy, etc.) and don't
>
> need to
>
> push
>
> versioning out of the serialization paths for best
>
> performance
>
> (as in
>
> the
>
> TypeSerializer)
>
>
> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
>
> [hidden email]>
>
> wrote:
>
>
> Hi Biao,
>
> Thanks for the answer!
>
> So given the multi-threaded readers, now we have as
>
> open
>
> questions:
>
> 1) How do we let the checkpoints pass through our
>
> multi-threaded
>
> reader
>
> operator?
>
> 2) Do we have separate reader and source operators or
>
> not? In
>
> the
>
> strategy
>
> that has a separate source, the source operator has a
>
> parallelism of
>
> 1
>
> and
>
> is responsible for split recovery only.
>
> For the first one, given also the constraints
>
> (blocking,
>
> finite
>
> queues,
>
> etc), I do not have an answer yet.
>
> For the 2nd, I think that we should go with separate
>
> operators
>
> for
>
> the
>
> source and the readers, for the following reasons:
>
> 1) This is more aligned with a potential future
>
> improvement
>
> where the
>
> split
>
> discovery becomes a responsibility of the JobManager
>
> and
>
> readers are
>
> pooling more work from the JM.
>
> 2) The source is going to be the "single point of
>
> truth".
>
> It
>
> will
>
> know
>
> what
>
> has been processed and what not. If the source and the
>
> readers
>
> are a
>
> single
>
> operator with parallelism > 1, or in general, if the
>
> split
>
> discovery
>
> is
>
> done by each task individually, then:
>   i) we have to have a deterministic scheme for each
>
> reader to
>
> assign
>
> splits to itself (e.g. mod subtaskId). This is not
>
> necessarily
>
> trivial
>
> for
>
> all sources.
>   ii) each reader would have to keep a copy of all its
>
> processed
>
> slpits
>
>   iii) the state has to be a union state with a
>
> non-trivial
>
> merging
>
> logic
>
> in order to support rescaling.
>
> Two additional points that you raised above:
>
> i) The point that you raised that we need to keep all
>
> splits
>
> (processed
>
> and
>
> not-processed) I think is a bit of a strong
>
> requirement.
>
> This
>
> would
>
> imply
>
> that for infinite sources the state will grow
>
> indefinitely.
>
> This is
>
> problem
>
> is even more pronounced if we do not have a single
>
> source
>
> that
>
> assigns
>
> splits to readers, as each reader will have its own
>
> copy
>
> of
>
> the
>
> state.
>
> ii) it is true that for finite sources we need to
>
> somehow
>
> not
>
> close
>
> the
>
> readers when the source/split discoverer finishes. The
> ContinuousFileReaderOperator has a work-around for
>
> that.
>
> It is
>
> not
>
> elegant,
>
> and checkpoints are not emitted after closing the
>
> source,
>
> but
>
> this, I
>
> believe, is a bigger problem which requires more
>
> changes
>
> than
>
> just
>
> refactoring the source interface.
>
> Cheers,
> Kostas
>
>
>
>
> --
> Best, Jingsong Lee
>
>
>

[Piotr Nowojski-3]

Hi,

Regarding the:

Collection<E> getNextRecords()

I’m pretty sure such design would unfortunately impact the performance (accessing and potentially creating the collection on the hot path).

Also the

InputStatus emitNext(DataOutput<T> output) throws Exception;
or
Status pollNext(SourceOutput<T> sourceOutput) throws Exception;

Gives us some opportunities in the future, to allow Source hot looping inside, until it receives some signal “please exit because of some reasons” (output collector could return such hint upon collecting the result). But that’s another topic outside of this FLIP’s scope.

Piotrek

> On 11 Dec 2019, at 10:41, Till Rohrmann <[hidden email]> wrote:
>
> Hi Becket,
>
> quick clarification from my side because I think you misunderstood my
> question. I did not suggest to let the SourceReader return only a single
> record at a time when calling getNextRecords. As the return type indicates,
> the method can return an arbitrary number of records.
>
> Cheers,
> Till
>
> On Wed, Dec 11, 2019 at 10:13 AM Dawid Wysakowicz <[hidden email] <mailto:[hidden email]>>
> wrote:
>
>> Hi Becket,
>>
>> Issue #1 - Design of Source interface
>>
>> I mentioned the lack of a method like Source#createEnumerator(Boundedness
>> boundedness, SplitEnumeratorContext context), because without the current
>> proposal is not complete/does not work.
>>
>> If we say that boundedness is an intrinsic property of a source imo we
>> don't need the Source#createEnumerator(Boundedness boundedness,
>> SplitEnumeratorContext context) method.
>>
>> Assuming a source from my previous example:
>>
>> Source source = KafkaSource.builder()
>>  ...
>>  .untilTimestamp(...)
>>  .build()
>>
>> Would the enumerator differ if created like
>> source.createEnumerator(CONTINUOUS_UNBOUNDED, ...) vs source
>> .createEnumerator(BOUNDED, ...)? I know I am repeating myself, but this is
>> the part that my opinion differ the most from the current proposal. I
>> really think it should always be the source that tells if it is bounded or
>> not. In the current proposal methods continousSource/boundedSource somewhat
>> reconfigure the source, which I think is misleading.
>>
>> I think a call like:
>>
>> Source source = KafkaSource.builder()
>>  ...
>>  .readContinously() / readUntilLatestOffset() / readUntilTimestamp / readUntilOffsets / ...
>>  .build()
>>
>> is way cleaner (and expressive) than
>>
>> Source source = KafkaSource.builder()
>>  ...
>>  .build()
>>
>>
>> env.continousSource(source) // which actually underneath would call createEnumerator(CONTINUOUS, ctx) which would be equivalent to source.readContinously().createEnumerator(ctx)
>> // or
>> env.boundedSource(source) // which actually underneath would call createEnumerator(BOUNDED, ctx) which would be equivalent to source.readUntilLatestOffset().createEnumerator(ctx)
>>
>>
>> Sorry for the comparison, but to me it seems there is too much magic
>> happening underneath those two calls.
>>
>> I really believe the Source interface should have getBoundedness method
>> instead of (supportBoundedness) + createEnumerator(Boundedness, ...)
>>
>>
>> Issue #2 - Design of
>> ExecutionEnvironment#source()/continuousSource()/boundedSource()
>>
>> As you might have guessed I am slightly in favor of option #2 modified.
>> Yes I am aware every step of the dag would have to be able to say if it is
>> bounded or not. I have a feeling it would be easier to express cross
>> bounded/unbounded operations, but I must admit I have not thought it
>> through thoroughly, In the spirit of batch is just a special case of
>> streaming I thought BoundedStream would extend from DataStream. Correct me
>> if I am wrong. In such a setup the cross bounded/unbounded operation could
>> be expressed quite easily I think:
>>
>> DataStream {
>>  DataStream join(DataStream, ...); // we could not really tell if the result is bounded or not, but because bounded stream is a special case of unbounded the API object is correct, irrespective if the left or right side of the join is bounded
>> }
>>
>> BoundedStream extends DataStream {
>>  BoundedStream join(BoundedStream, ...); // only if both sides are bounded the result can be bounded as well. However we do have access to the DataStream#join here, so you can still join with a DataStream
>> }
>>
>>
>> On the other hand I also see benefits of two completely disjointed APIs,
>> as we could prohibit some streaming calls in the bounded API. I can't think
>> of any unbounded operators that could not be implemented for bounded stream.
>>
>> Besides I think we both agree we don't like the method:
>>
>> DataStream boundedStream(Source)
>>
>> suggested in the current state of the FLIP. Do we ? :)
>>
>> Best,
>>
>> Dawid
>>
>> On 10/12/2019 18:57, Becket Qin wrote:
>>
>> Hi folks,
>>
>> Thanks for the discussion, great feedback. Also thanks Dawid for the
>> explanation, it is much clearer now.
>>
>> One thing that is indeed missing from the FLIP is how the boundedness is
>> passed to the Source implementation. So the API should be
>> Source#createEnumerator(Boundedness boundedness, SplitEnumeratorContext
>> context)
>> And we can probably remove the Source#supportBoundedness(Boundedness
>> boundedness) method.
>>
>> Assuming we have that, we are essentially choosing from one of the
>> following two options:
>>
>> Option 1:
>> // The source is continuous source, and only unbounded operations can be
>> performed.
>> DataStream<Type> datastream = env.continuousSource(someSource);
>>
>> // The source is bounded source, both bounded and unbounded operations can
>> be performed.
>> BoundedDataStream<Type> boundedDataStream = env.boundedSource(someSource);
>>
>>  - Pros:
>>       a) explicit boundary between bounded / unbounded streams, it is
>> quite simple and clear to the users.
>>  - Cons:
>>       a) For applications that do not involve bounded operations, they
>> still have to call different API to distinguish bounded / unbounded streams.
>>       b) No support for bounded stream to run in a streaming runtime
>> setting, i.e. scheduling and operators behaviors.
>>
>>
>> Option 2:
>> // The source is either bounded or unbounded, but only unbounded operations
>> could be performed on the returned DataStream.
>> DataStream<Type> dataStream = env.source(someSource);
>>
>> // The source must be a bounded source, otherwise exception is thrown.
>> BoundedDataStream<Type> boundedDataStream =
>> env.boundedSource(boundedSource);
>>
>> The pros and cons are exactly the opposite of option 1.
>>  - Pros:
>>       a) For applications that do not involve bounded operations, they
>> still have to call different API to distinguish bounded / unbounded streams.
>>       b) Support for bounded stream to run in a streaming runtime setting,
>> i.e. scheduling and operators behaviors.
>>  - Cons:
>>       a) Bounded / unbounded streams are kind of mixed, i.e. given a
>> DataStream, it is not clear whether it is bounded or not, unless you have
>> the access to its source.
>>
>>
>> If we only think from the Source API perspective, option 2 seems a better
>> choice because functionality wise it is a superset of option 1, at the cost
>> of some seemingly acceptable ambiguity in the DataStream API.
>> But if we look at the DataStream API as a whole, option 1 seems a clearer
>> choice. For example, some times a library may have to know whether a
>> certain task will finish or not. And it would be difficult to tell if the
>> input is a DataStream, unless additional information is provided all the
>> way from the Source. One possible solution is to have a *modified option 2*
>> which adds a method to the DataStream API to indicate boundedness, such as
>> getBoundedness(). It would solve the problem with a potential confusion of
>> what is difference between a DataStream with getBoundedness()=true and a
>> BoundedDataStream. But that seems not super difficult to explain.
>>
>> So from API's perspective, I don't have a strong opinion between *option 1*
>> and *modified option 2. *I like the cleanness of option 1, but modified
>> option 2 would be more attractive if we have concrete use case for the
>> "Bounded stream with unbounded streaming runtime settings".
>>
>> Re: Till
>>
>>
>> Maybe this has already been asked before but I was wondering why the
>> SourceReader interface has the method pollNext which hands the
>> responsibility of outputting elements to the SourceReader implementation?
>> Has this been done for backwards compatibility reasons with the old source
>> interface? If not, then one could define a Collection<E> getNextRecords()
>> method which returns the currently retrieved records and then the caller
>> emits them outside of the SourceReader. That way the interface would not
>> allow to implement an outputting loop where we never hand back control to
>> the caller. At the moment, this contract can be easily broken and is only
>> mentioned loosely in the JavaDocs.
>>
>>
>> The primary reason we handover the SourceOutput to the SourceReader is
>> because sometimes it is difficult for a SourceReader to emit one record at
>> a time. One example is some batched messaging systems which only have an
>> offset for the entire batch instead of individual messages in the batch. In
>> that case, returning one record at a time would leave the SourceReader in
>> an uncheckpointable state because they can only checkpoint at the batch
>> boundaries.
>>
>> Thanks,
>>
>> Jiangjie (Becket) Qin
>>
>> On Tue, Dec 10, 2019 at 5:33 PM Till Rohrmann <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> wrote:
>>
>>
>> Hi everyone,
>>
>> thanks for drafting this FLIP. It reads very well.
>>
>> Concerning Dawid's proposal, I tend to agree. The boundedness could come
>> from the source and tell the system how to treat the operator (scheduling
>> wise). From a user's perspective it should be fine to get back a DataStream
>> when calling env.source(boundedSource) if he does not need special
>> operations defined on a BoundedDataStream. If he needs this, then one could
>> use the method BoundedDataStream env.boundedSource(boundedSource).
>>
>> If possible, we could enforce the proper usage of env.boundedSource() by
>> introducing a BoundedSource type so that one cannot pass an
>> unbounded source to it. That way users would not be able to shoot
>> themselves in the foot.
>>
>> Maybe this has already been asked before but I was wondering why the
>> SourceReader interface has the method pollNext which hands the
>> responsibility of outputting elements to the SourceReader implementation?
>> Has this been done for backwards compatibility reasons with the old source
>> interface? If not, then one could define a Collection<E> getNextRecords()
>> method which returns the currently retrieved records and then the caller
>> emits them outside of the SourceReader. That way the interface would not
>> allow to implement an outputting loop where we never hand back control to
>> the caller. At the moment, this contract can be easily broken and is only
>> mentioned loosely in the JavaDocs.
>>
>> Cheers,
>> Till
>>
>> On Tue, Dec 10, 2019 at 7:49 AM Jingsong Li <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>>
>> wrote:
>>
>>
>> Hi all,
>>
>> I think current design is good.
>>
>> My understanding is:
>>
>> For execution mode: bounded mode and continuous mode, It's totally
>> different. I don't think we have the ability to integrate the two models
>>
>> at
>>
>> present. It's about scheduling, memory, algorithms, States, etc. we
>> shouldn't confuse them.
>>
>> For source capabilities: only bounded, only continuous, both bounded and
>> continuous.
>> I think Kafka is a source that can be ran both bounded
>> and continuous execution mode.
>> And Kafka with end offset should be ran both bounded
>> and continuous execution mode.  Using apache Beam with Flink runner, I
>>
>> used
>>
>> to run a "bounded" Kafka in streaming mode. For our previous DataStream,
>>
>> it
>>
>> is not necessarily required that the source cannot be bounded.
>>
>> So it is my thought for Dawid's question:
>> 1.pass a bounded source to continuousSource() +1
>> 2.pass a continuous source to boundedSource() -1, should throw exception.
>>
>> In StreamExecutionEnvironment, continuousSource and boundedSource define
>> the execution mode. It defines a clear boundary of execution mode.
>>
>> Best,
>> Jingsong Lee
>>
>> On Tue, Dec 10, 2019 at 10:37 AM Jark Wu <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> wrote:
>>
>>
>> I agree with Dawid's point that the boundedness information should come
>> from the source itself (e.g. the end timestamp), not through
>> env.boundedSouce()/continuousSource().
>> I think if we want to support something like `env.source()` that derive
>>
>> the
>>
>> execution mode from source, `supportsBoundedness(Boundedness)`
>> method is not enough, because we don't know whether it is bounded or
>>
>> not.
>>
>> Best,
>> Jark
>>
>>
>> On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>>
>> wrote:
>>
>>
>> One more thing. In the current proposal, with the
>> supportsBoundedness(Boundedness) method and the boundedness coming
>>
>> from
>>
>> either continuousSource or boundedSource I could not find how this
>> information is fed back to the SplitEnumerator.
>>
>> Best,
>>
>> Dawid
>>
>> On 09/12/2019 13:52, Becket Qin wrote:
>>
>> Hi Dawid,
>>
>> Thanks for the comments. This actually brings another relevant
>>
>> question
>>
>> about what does a "bounded source" imply. I actually had the same
>> impression when I look at the Source API. Here is what I understand
>>
>> after
>>
>> some discussion with Stephan. The bounded source has the following
>>
>> impacts.
>>
>> 1. API validity.
>> - A bounded source generates a bounded stream so some operations
>>
>> that
>>
>> only
>>
>> works for bounded records would be performed, e.g. sort.
>> - To expose these bounded stream only APIs, there are two options:
>>     a. Add them to the DataStream API and throw exception if a
>>
>> method
>>
>> is
>>
>> called on an unbounded stream.
>>     b. Create a BoundedDataStream class which is returned from
>> env.boundedSource(), while DataStream is returned from
>>
>> env.continousSource().
>>
>> Note that this cannot be done by having single
>>
>> env.source(theSource)
>>
>> even
>>
>> the Source has a getBoundedness() method.
>>
>> 2. Scheduling
>> - A bounded source could be computed stage by stage without
>>
>> bringing
>>
>> up
>>
>> all
>>
>> the tasks at the same time.
>>
>> 3. Operator behaviors
>> - A bounded source indicates the records are finite so some
>>
>> operators
>>
>> can
>>
>> wait until it receives all the records before it starts the
>>
>> processing.
>>
>> In the above impact, only 1 is relevant to the API design. And the
>>
>> current
>>
>> proposal in FLIP-27 is following 1.b.
>>
>> // boundedness depends of source property, imo this should always
>>
>> be
>>
>> preferred
>>
>>
>> DataStream<MyType> stream = env.source(theSource);
>>
>>
>> In your proposal, does DataStream have bounded stream only methods?
>>
>> It
>>
>> looks it should have, otherwise passing a bounded Source to
>>
>> env.source()
>>
>> would be confusing. In that case, we will essentially do 1.a if an
>> unbounded Source is created from env.source(unboundedSource).
>>
>> If we have the methods only supported for bounded streams in
>>
>> DataStream,
>>
>> it
>>
>> seems a little weird to have a separate BoundedDataStream
>>
>> interface.
>>
>> Am I understand it correctly?
>>
>> Thanks,
>>
>> Jiangjie (Becket) Qin
>>
>>
>>
>> On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <
>>
>> [hidden email] <mailto:[hidden email]>>
>>
>> wrote:
>>
>>
>> Hi all,
>>
>> Really well written proposal and very important one. I must admit
>>
>> I
>>
>> have
>>
>> not understood all the intricacies of it yet.
>>
>> One question I have though is about where does the information
>>
>> about
>>
>> boundedness come from. I think in most cases it is a property of
>>
>> the
>>
>> source. As you described it might be e.g. end offset, a flag
>>
>> should
>>
>> it
>>
>> monitor new splits etc. I think it would be a really nice use case
>>
>> to
>>
>> be
>>
>> able to say:
>>
>> new KafkaSource().readUntil(long timestamp),
>>
>> which could work as an "end offset". Moreover I think all Bounded
>>
>> sources
>>
>> support continuous mode, but no intrinsically continuous source
>>
>> support
>>
>> the
>>
>> Bounded mode. If I understood the proposal correctly it suggest
>>
>> the
>>
>> boundedness sort of "comes" from the outside of the source, from
>>
>> the
>>
>> invokation of either boundedStream or continousSource.
>>
>> I am wondering if it would make sense to actually change the
>>
>> method
>>
>> boolean Source#supportsBoundedness(Boundedness)
>>
>> to
>>
>> Boundedness Source#getBoundedness().
>>
>> As for the methods #boundedSource, #continousSource, assuming the
>> boundedness is property of the source they do not affect how the
>>
>> enumerator
>>
>> works, but mostly how the dag is scheduled, right? I am not
>>
>> against
>>
>> those
>>
>> methods, but I think it is a very specific use case to actually
>>
>> override
>>
>> the property of the source. In general I would expect users to
>>
>> only
>>
>> call
>>
>> env.source(theSource), where the source tells if it is bounded or
>>
>> not. I
>>
>> would suggest considering following set of methods:
>>
>> // boundedness depends of source property, imo this should always
>>
>> be
>>
>> preferred
>>
>> DataStream<MyType> stream = env.source(theSource);
>>
>>
>> // always continous execution, whether bounded or unbounded source
>>
>> DataStream<MyType> boundedStream = env.continousSource(theSource);
>>
>> // imo this would make sense if the BoundedDataStream provides
>>
>> additional features unavailable for continous mode
>>
>> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
>>
>>
>> Best,
>>
>> Dawid
>>
>>
>> On 04/12/2019 11:25, Stephan Ewen wrote:
>>
>> Thanks, Becket, for updating this.
>>
>> I agree with moving the aspects you mentioned into separate FLIPs
>>
>> -
>>
>> this
>>
>> one way becoming unwieldy in size.
>>
>> +1 to the FLIP in its current state. Its a very detailed write-up,
>>
>> nicely
>>
>> done!
>>
>> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>>
>>
>> <
>>
>> [hidden email] <mailto:[hidden email]>> wrote:
>>
>> Hi all,
>>
>> Sorry for the long belated update. I have updated FLIP-27 wiki
>>
>> page
>>
>> with
>>
>> the latest proposals. Some noticeable changes include:
>> 1. A new generic communication mechanism between SplitEnumerator
>>
>> and
>>
>> SourceReader.
>> 2. Some detail API method signature changes.
>>
>> We left a few things out of this FLIP and will address them in
>>
>> separate
>>
>> FLIPs. Including:
>> 1. Per split event time.
>> 2. Event time alignment.
>> 3. Fine grained failover for SplitEnumerator failure.
>>
>> Please let us know if you have any question.
>>
>> Thanks,
>>
>> Jiangjie (Becket) Qin
>>
>> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> <
>>
>> [hidden email] <mailto:[hidden email]>> wrote:
>>
>> Hi  Łukasz!
>>
>> Becket and me are working hard on figuring out the last details
>>
>> and
>>
>> implementing the first PoC. We would update the FLIP hopefully
>>
>> next
>>
>> week.
>>
>> There is a fair chance that a first version of this will be in
>>
>> 1.10,
>>
>> but
>>
>> I
>>
>> think it will take another release to battle test it and migrate
>>
>> the
>>
>> connectors.
>>
>> Best,
>> Stephan
>>
>>
>>
>>
>> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <[hidden email] <mailto:[hidden email]>
>>
>> <
>>
>> [hidden email] <mailto:[hidden email]>>
>>
>> wrote:
>>
>> Hi,
>>
>> This proposal looks very promising for us. Do you have any plans
>>
>> in
>>
>> which
>>
>> Flink release it is going to be released? We are thinking on
>>
>> using a
>>
>> Data
>>
>> Set API for our future use cases but on the other hand Data Set
>>
>> API
>>
>> is
>>
>> going to be deprecated so using proposed bounded data streams
>>
>> solution
>>
>> could be more viable in the long term.
>>
>> Thanks,
>> Łukasz
>>
>> On 2019/10/01 15:48:03, Thomas Weise <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> <
>>
>> [hidden email] <mailto:[hidden email]>> wrote:
>>
>> Thanks for putting together this proposal!
>>
>> I see that the "Per Split Event Time" and "Event Time Alignment"
>>
>> sections
>>
>> are still TBD.
>>
>> It would probably be good to flesh those out a bit before
>>
>> proceeding
>>
>> too
>>
>> far
>>
>> as the event time alignment will probably influence the
>>
>> interaction
>>
>> with
>>
>> the split reader, specifically ReaderStatus
>>
>> emitNext(SourceOutput<E>
>>
>> output).
>>
>> We currently have only one implementation for event time alignment
>>
>> in
>>
>> the
>>
>> Kinesis consumer. The synchronization in that case takes place as
>>
>> the
>>
>> last
>>
>> step before records are emitted downstream (RecordEmitter). With
>>
>> the
>>
>> currently proposed interfaces, the equivalent can be implemented
>>
>> in
>>
>> the
>>
>> reader loop, although note that in the Kinesis consumer the per
>>
>> shard
>>
>> threads push records.
>>
>> Synchronization has not been implemented for the Kafka consumer
>>
>> yet.
>>
>> https://issues.apache.org/jira/browse/FLINK-12675 <https://issues.apache.org/jira/browse/FLINK-12675>
>>
>> When I looked at it, I realized that the implementation will look
>>
>> quite
>>
>> different
>> from Kinesis because it needs to take place in the pull part,
>>
>> where
>>
>> records
>>
>> are taken from the Kafka client. Due to the multiplexing it cannot
>>
>> be
>>
>> done
>>
>> by blocking the split thread like it currently works for Kinesis.
>>
>> Reading
>>
>> from individual Kafka partitions needs to be controlled via
>>
>> pause/resume
>>
>> on the Kafka client.
>>
>> To take on that responsibility the split thread would need to be
>>
>> aware
>>
>> of
>>
>> the
>> watermarks or at least whether it should or should not continue to
>>
>> consume
>>
>> a given split and this may require a different SourceReader or
>>
>> SourceOutput
>>
>> interface.
>>
>> Thanks,
>> Thomas
>>
>>
>> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> <
>>
>> [hidden email] <mailto:[hidden email]>> wrote:
>>
>> Hi Stephan,
>>
>> Thank you for feedback!
>> Will take a look at your branch before public discussing.
>>
>>
>> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>>
>>
>> <
>>
>> [hidden email] <mailto:[hidden email]>>
>>
>> wrote:
>>
>> Hi Biao!
>>
>> Thanks for reviving this. I would like to join this discussion,
>>
>> but
>>
>> am
>>
>> quite occupied with the 1.9 release, so can we maybe pause this
>>
>> discussion
>>
>> for a week or so?
>>
>> In the meantime I can share some suggestion based on prior
>>
>> experiments:
>>
>> How to do watermarks / timestamp extractors in a simpler and more
>>
>> flexible
>>
>> way. I think that part is quite promising should be part of the
>>
>> new
>>
>> source
>>
>> interface.
>>
>>
>>
>>
>>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime <https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime>
>>
>> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java <https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java>
>>
>> Some experiments on how to build the source reader and its
>>
>> library
>>
>> for
>>
>> common threading/split patterns:
>>
>>
>>
>>
>>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src <https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src>
>>
>> Best,
>> Stephan
>>
>>
>> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> <
>>
>> [hidden email] <mailto:[hidden email]>>
>>
>> wrote:
>>
>> Hi devs,
>>
>> Since 1.9 is nearly released, I think we could get back to
>>
>> FLIP-27.
>>
>> I
>>
>> believe it should be included in 1.10.
>>
>> There are so many things mentioned in document of FLIP-27. [1] I
>>
>> think
>>
>> we'd better discuss them separately. However the wiki is not a
>>
>> good
>>
>> place
>>
>> to discuss. I wrote google doc about SplitReader API which
>>
>> misses
>>
>> some
>>
>> details in the document. [2]
>>
>> 1.
>>
>>
>>
>>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface <https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface>
>>
>> 2.
>>
>>
>>
>>
>> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing <https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing>
>>
>> CC Stephan, Aljoscha, Piotrek, Becket
>>
>>
>> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> <
>>
>> [hidden email] <mailto:[hidden email]>>
>>
>> wrote:
>>
>> Hi Steven,
>> Thank you for the feedback. Please take a look at the document
>>
>> FLIP-27
>>
>> <
>>
>>
>>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface <https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface>
>>
>> which
>>
>> is updated recently. A lot of details of enumerator were added
>>
>> in
>>
>> this
>>
>> document. I think it would help.
>>
>> Steven Wu <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>>
>>
>> 于2019年3月28日周四
>>
>> 下午12:52写道：
>>
>> This proposal mentioned that SplitEnumerator might run on the
>> JobManager or
>> in a single task on a TaskManager.
>>
>> if enumerator is a single task on a taskmanager, then the job
>>
>> DAG
>>
>> can
>>
>> never
>> been embarrassingly parallel anymore. That will nullify the
>>
>> leverage
>>
>> of
>>
>> fine-grained recovery for embarrassingly parallel jobs.
>>
>> It's not clear to me what's the implication of running
>>
>> enumerator
>>
>> on
>>
>> the
>>
>> jobmanager. So I will leave that out for now.
>>
>> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> <
>>
>> [hidden email] <mailto:[hidden email]>>
>>
>> wrote:
>>
>> Hi Stephan & Piotrek,
>>
>> Thank you for feedback.
>>
>> It seems that there are a lot of things to do in community.
>>
>> I
>>
>> am
>>
>> just
>>
>> afraid that this discussion may be forgotten since there so
>>
>> many
>>
>> proposals
>>
>> recently.
>> Anyway, wish to see the split topics soon :)
>>
>> Piotr Nowojski <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>>
>>
>> 于2019年1月24日周四
>>
>> 下午8:21写道：
>>
>> Hi Biao!
>>
>> This discussion was stalled because of preparations for
>>
>> the
>>
>> open
>>
>> sourcing
>>
>> & merging Blink. I think before creating the tickets we
>>
>> should
>>
>> split this
>>
>> discussion into topics/areas outlined by Stephan and
>>
>> create
>>
>> Flips
>>
>> for
>>
>> that.
>>
>> I think there is no chance for this to be completed in
>>
>> couple
>>
>> of
>>
>> remaining
>>
>> weeks/1 month before 1.8 feature freeze, however it would
>>
>> be
>>
>> good
>>
>> to aim
>>
>> with those changes for 1.9.
>>
>> Piotrek
>>
>>
>> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> <
>>
>> [hidden email] <mailto:[hidden email]>>
>>
>> wrote:
>>
>> Hi community,
>> The summary of Stephan makes a lot sense to me. It is
>>
>> much
>>
>> clearer
>>
>> indeed
>>
>> after splitting the complex topic into small ones.
>> I was wondering is there any detail plan for next step?
>>
>> If
>>
>> not,
>>
>> I
>>
>> would
>>
>> like to push this thing forward by creating some JIRA
>>
>> issues.
>>
>> Another question is that should version 1.8 include
>>
>> these
>>
>> features?
>>
>> Stephan Ewen <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>> 于2018年12月1日周六
>>
>> 上午4:20写道：
>>
>> Thanks everyone for the lively discussion. Let me try
>>
>> to
>>
>> summarize
>>
>> where I
>>
>> see convergence in the discussion and open issues.
>> I'll try to group this by design aspect of the source.
>>
>> Please
>>
>> let me
>>
>> know
>>
>> if I got things wrong or missed something crucial here.
>>
>> For issues 1-3, if the below reflects the state of the
>>
>> discussion, I
>>
>> would
>>
>> try and update the FLIP in the next days.
>> For the remaining ones we need more discussion.
>>
>> I would suggest to fork each of these aspects into a
>>
>> separate
>>
>> mail
>>
>> thread,
>>
>> or will loose sight of the individual aspects.
>>
>> *(1) Separation of Split Enumerator and Split Reader*
>>
>> - All seem to agree this is a good thing
>> - Split Enumerator could in the end live on JobManager
>>
>> (and
>>
>> assign
>>
>> splits
>>
>> via RPC) or in a task (and assign splits via data
>>
>> streams)
>>
>> - this discussion is orthogonal and should come later,
>>
>> when
>>
>> the
>>
>> interface
>>
>> is agreed upon.
>>
>> *(2) Split Readers for one or more splits*
>>
>> - Discussion seems to agree that we need to support
>>
>> one
>>
>> reader
>>
>> that
>>
>> possibly handles multiple splits concurrently.
>> - The requirement comes from sources where one
>>
>> poll()-style
>>
>> call
>>
>> fetches
>>
>> data from different splits / partitions
>>   --> example sources that require that would be for
>>
>> example
>>
>> Kafka,
>>
>> Pravega, Pulsar
>>
>> - Could have one split reader per source, or multiple
>>
>> split
>>
>> readers
>>
>> that
>>
>> share the "poll()" function
>> - To not make it too complicated, we can start with
>>
>> thinking
>>
>> about
>>
>> one
>>
>> split reader for all splits initially and see if that
>>
>> covers
>>
>> all
>>
>> requirements
>>
>> *(3) Threading model of the Split Reader*
>>
>> - Most active part of the discussion ;-)
>>
>> - A non-blocking way for Flink's task code to interact
>>
>> with
>>
>> the
>>
>> source
>>
>> is
>>
>> needed in order to a task runtime code based on a
>> single-threaded/actor-style task design
>>   --> I personally am a big proponent of that, it will
>>
>> help
>>
>> with
>>
>> well-behaved checkpoints, efficiency, and simpler yet
>>
>> more
>>
>> robust
>>
>> runtime
>>
>> code
>>
>> - Users care about simple abstraction, so as a
>>
>> subclass
>>
>> of
>>
>> SplitReader
>>
>> (non-blocking / async) we need to have a
>>
>> BlockingSplitReader
>>
>> which
>>
>> will
>>
>> form the basis of most source implementations.
>>
>> BlockingSplitReader
>>
>> lets
>>
>> users do blocking simple poll() calls.
>> - The BlockingSplitReader would spawn a thread (or
>>
>> more)
>>
>> and
>>
>> the
>>
>> thread(s) can make blocking calls and hand over data
>>
>> buffers
>>
>> via
>>
>> a
>>
>> blocking
>>
>> queue
>> - This should allow us to cover both, a fully async
>>
>> runtime,
>>
>> and a
>>
>> simple
>>
>> blocking interface for users.
>> - This is actually very similar to how the Kafka
>>
>> connectors
>>
>> work.
>>
>> Kafka
>>
>> 9+ with one thread, Kafka 8 with multiple threads
>>
>> - On the base SplitReader (the async one), the
>>
>> non-blocking
>>
>> method
>>
>> that
>>
>> gets the next chunk of data would signal data
>>
>> availability
>>
>> via
>>
>> a
>>
>> CompletableFuture, because that gives the best
>>
>> flexibility
>>
>> (can
>>
>> await
>>
>> completion or register notification handlers).
>> - The source task would register a "thenHandle()" (or
>>
>> similar)
>>
>> on the
>>
>> future to put a "take next data" task into the
>>
>> actor-style
>>
>> mailbox
>>
>> *(4) Split Enumeration and Assignment*
>>
>> - Splits may be generated lazily, both in cases where
>>
>> there
>>
>> is a
>>
>> limited
>>
>> number of splits (but very many), or splits are
>>
>> discovered
>>
>> over
>>
>> time
>>
>> - Assignment should also be lazy, to get better load
>>
>> balancing
>>
>> - Assignment needs support locality preferences
>>
>> - Possible design based on discussion so far:
>>
>>   --> SplitReader has a method "addSplits(SplitT...)"
>>
>> to
>>
>> add
>>
>> one or
>>
>> more
>>
>> splits. Some split readers might assume they have only
>>
>> one
>>
>> split
>>
>> ever,
>>
>> concurrently, others assume multiple splits. (Note:
>>
>> idea
>>
>> behind
>>
>> being
>>
>> able
>>
>> to add multiple splits at the same time is to ease
>>
>> startup
>>
>> where
>>
>> multiple
>>
>> splits may be assigned instantly.)
>>   --> SplitReader has a context object on which it can
>>
>> call
>>
>> indicate
>>
>> when
>>
>> splits are completed. The enumerator gets that
>>
>> notification and
>>
>> can
>>
>> use
>>
>> to
>>
>> decide when to assign new splits. This should help both
>>
>> in
>>
>> cases
>>
>> of
>>
>> sources
>>
>> that take splits lazily (file readers) and in case the
>>
>> source
>>
>> needs to
>>
>> preserve a partial order between splits (Kinesis,
>>
>> Pravega,
>>
>> Pulsar may
>>
>> need
>>
>> that).
>>   --> SplitEnumerator gets notification when
>>
>> SplitReaders
>>
>> start
>>
>> and
>>
>> when
>>
>> they finish splits. They can decide at that moment to
>>
>> push
>>
>> more
>>
>> splits
>>
>> to
>>
>> that reader
>>   --> The SplitEnumerator should probably be aware of
>>
>> the
>>
>> source
>>
>> parallelism, to build its initial distribution.
>>
>> - Open question: Should the source expose something
>>
>> like
>>
>> "host
>>
>> preferences", so that yarn/mesos/k8s can take this into
>>
>> account
>>
>> when
>>
>> selecting a node to start a TM on?
>>
>> *(5) Watermarks and event time alignment*
>>
>> - Watermark generation, as well as idleness, needs to
>>
>> be
>>
>> per
>>
>> split
>>
>> (like
>>
>> currently in the Kafka Source, per partition)
>> - It is desirable to support optional
>>
>> event-time-alignment,
>>
>> meaning
>>
>> that
>>
>> splits that are ahead are back-pressured or temporarily
>>
>> unsubscribed
>>
>> - I think i would be desirable to encapsulate
>>
>> watermark
>>
>> generation
>>
>> logic
>>
>> in watermark generators, for a separation of concerns.
>>
>> The
>>
>> watermark
>>
>> generators should run per split.
>> - Using watermark generators would also help with
>>
>> another
>>
>> problem of
>>
>> the
>>
>> suggested interface, namely supporting non-periodic
>>
>> watermarks
>>
>> efficiently.
>>
>> - Need a way to "dispatch" next record to different
>>
>> watermark
>>
>> generators
>>
>> - Need a way to tell SplitReader to "suspend" a split
>>
>> until a
>>
>> certain
>>
>> watermark is reached (event time backpressure)
>> - This would in fact be not needed (and thus simpler)
>>
>> if
>>
>> we
>>
>> had
>>
>> a
>>
>> SplitReader per split and may be a reason to re-open
>>
>> that
>>
>> discussion
>>
>> *(6) Watermarks across splits and in the Split
>>
>> Enumerator*
>>
>> - The split enumerator may need some watermark
>>
>> awareness,
>>
>> which
>>
>> should
>>
>> be
>>
>> purely based on split metadata (like create timestamp
>>
>> of
>>
>> file
>>
>> splits)
>>
>> - If there are still more splits with overlapping
>>
>> event
>>
>> time
>>
>> range
>>
>> for
>>
>> a
>>
>> split reader, then that split reader should not advance
>>
>> the
>>
>> watermark
>>
>> within the split beyond the overlap boundary. Otherwise
>>
>> future
>>
>> splits
>>
>> will
>>
>> produce late data.
>>
>> - One way to approach this could be that the split
>>
>> enumerator
>>
>> may
>>
>> send
>>
>> watermarks to the readers, and the readers cannot emit
>>
>> watermarks
>>
>> beyond
>>
>> that received watermark.
>> - Many split enumerators would simply immediately send
>>
>> Long.MAX
>>
>> out
>>
>> and
>>
>> leave the progress purely to the split readers.
>>
>> - For event-time alignment / split back pressure, this
>>
>> begs
>>
>> the
>>
>> question
>>
>> how we can avoid deadlocks that may arise when splits
>>
>> are
>>
>> suspended
>>
>> for
>>
>> event time back pressure,
>>
>> *(7) Batch and streaming Unification*
>>
>> - Functionality wise, the above design should support
>>
>> both
>>
>> - Batch often (mostly) does not care about reading "in
>>
>> order"
>>
>> and
>>
>> generating watermarks
>>   --> Might use different enumerator logic that is
>>
>> more
>>
>> locality
>>
>> aware
>>
>> and ignores event time order
>>   --> Does not generate watermarks
>> - Would be great if bounded sources could be
>>
>> identified
>>
>> at
>>
>> compile
>>
>> time,
>>
>> so that "env.addBoundedSource(...)" is type safe and
>>
>> can
>>
>> return a
>>
>> "BoundedDataStream".
>> - Possible to defer this discussion until later
>>
>> *Miscellaneous Comments*
>>
>> - Should the source have a TypeInformation for the
>>
>> produced
>>
>> type,
>>
>> instead
>>
>> of a serializer? We need a type information in the
>>
>> stream
>>
>> anyways, and
>>
>> can
>>
>> derive the serializer from that. Plus, creating the
>>
>> serializer
>>
>> should
>>
>> respect the ExecutionConfig.
>>
>> - The TypeSerializer interface is very powerful but
>>
>> also
>>
>> not
>>
>> easy to
>>
>> implement. Its purpose is to handle data super
>>
>> efficiently,
>>
>> support
>>
>> flexible ways of evolution, etc.
>> For metadata I would suggest to look at the
>>
>> SimpleVersionedSerializer
>>
>> instead, which is used for example for checkpoint
>>
>> master
>>
>> hooks,
>>
>> or for
>>
>> the
>>
>> streaming file sink. I think that is is a good match
>>
>> for
>>
>> cases
>>
>> where
>>
>> we
>>
>> do
>>
>> not need more than ser/deser (no copy, etc.) and don't
>>
>> need to
>>
>> push
>>
>> versioning out of the serialization paths for best
>>
>> performance
>>
>> (as in
>>
>> the
>>
>> TypeSerializer)
>>
>>
>> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
>>
>> [hidden email]>
>>
>> wrote:
>>
>>
>> Hi Biao,
>>
>> Thanks for the answer!
>>
>> So given the multi-threaded readers, now we have as
>>
>> open
>>
>> questions:
>>
>> 1) How do we let the checkpoints pass through our
>>
>> multi-threaded
>>
>> reader
>>
>> operator?
>>
>> 2) Do we have separate reader and source operators or
>>
>> not? In
>>
>> the
>>
>> strategy
>>
>> that has a separate source, the source operator has a
>>
>> parallelism of
>>
>> 1
>>
>> and
>>
>> is responsible for split recovery only.
>>
>> For the first one, given also the constraints
>>
>> (blocking,
>>
>> finite
>>
>> queues,
>>
>> etc), I do not have an answer yet.
>>
>> For the 2nd, I think that we should go with separate
>>
>> operators
>>
>> for
>>
>> the
>>
>> source and the readers, for the following reasons:
>>
>> 1) This is more aligned with a potential future
>>
>> improvement
>>
>> where the
>>
>> split
>>
>> discovery becomes a responsibility of the JobManager
>>
>> and
>>
>> readers are
>>
>> pooling more work from the JM.
>>
>> 2) The source is going to be the "single point of
>>
>> truth".
>>
>> It
>>
>> will
>>
>> know
>>
>> what
>>
>> has been processed and what not. If the source and the
>>
>> readers
>>
>> are a
>>
>> single
>>
>> operator with parallelism > 1, or in general, if the
>>
>> split
>>
>> discovery
>>
>> is
>>
>> done by each task individually, then:
>>  i) we have to have a deterministic scheme for each
>>
>> reader to
>>
>> assign
>>
>> splits to itself (e.g. mod subtaskId). This is not
>>
>> necessarily
>>
>> trivial
>>
>> for
>>
>> all sources.
>>  ii) each reader would have to keep a copy of all its
>>
>> processed
>>
>> slpits
>>
>>  iii) the state has to be a union state with a
>>
>> non-trivial
>>
>> merging
>>
>> logic
>>
>> in order to support rescaling.
>>
>> Two additional points that you raised above:
>>
>> i) The point that you raised that we need to keep all
>>
>> splits
>>
>> (processed
>>
>> and
>>
>> not-processed) I think is a bit of a strong
>>
>> requirement.
>>
>> This
>>
>> would
>>
>> imply
>>
>> that for infinite sources the state will grow
>>
>> indefinitely.
>>
>> This is
>>
>> problem
>>
>> is even more pronounced if we do not have a single
>>
>> source
>>
>> that
>>
>> assigns
>>
>> splits to readers, as each reader will have its own
>>
>> copy
>>
>> of
>>
>> the
>>
>> state.
>>
>> ii) it is true that for finite sources we need to
>>
>> somehow
>>
>> not
>>
>> close
>>
>> the
>>
>> readers when the source/split discoverer finishes. The
>> ContinuousFileReaderOperator has a work-around for
>>
>> that.
>>
>> It is
>>
>> not
>>
>> elegant,
>>
>> and checkpoints are not emitted after closing the
>>
>> source,
>>
>> but
>>
>> this, I
>>
>> believe, is a bigger problem which requires more
>>
>> changes
>>
>> than
>>
>> just
>>
>> refactoring the source interface.
>>
>> Cheers,
>> Kostas
>>
>>
>>
>>
>> --
>> Best, Jingsong Lee

[Jark Wu-2]

Hi Becket,

I think Dawid explained things clearly and makes a lot of sense.
I'm also in favor of #2, because #1 doesn't work for our future unified
envrionment.

You can see the vision in this documentation [1]. In the future, we would
like to
drop the global streaming/batch mode in SQL (i.e.
EnvironmentSettings#inStreamingMode/inBatchMode).
A source is bounded or unbounded once defined, so queries can be inferred
from source to run
in streaming or batch or hybrid mode. However, in #1, we will lose this
ability because the framework
doesn't know whether the source is bounded or unbounded.

Best,
Jark


[1]:
https://docs.google.com/document/d/1yrKXEIRATfxHJJ0K3t6wUgXAtZq8D-XgvEnvl2uUcr0/edit#heading=h.v4ib17buma1p

On Wed, 11 Dec 2019 at 20:52, Piotr Nowojski <[hidden email]> wrote:

> Hi,
>
> Regarding the:
>
> Collection<E> getNextRecords()
>
> I’m pretty sure such design would unfortunately impact the performance
> (accessing and potentially creating the collection on the hot path).
>
> Also the
>
> InputStatus emitNext(DataOutput<T> output) throws Exception;
> or
> Status pollNext(SourceOutput<T> sourceOutput) throws Exception;
>
> Gives us some opportunities in the future, to allow Source hot looping
> inside, until it receives some signal “please exit because of some reasons”
> (output collector could return such hint upon collecting the result). But
> that’s another topic outside of this FLIP’s scope.
>
> Piotrek
>
> > On 11 Dec 2019, at 10:41, Till Rohrmann <[hidden email]> wrote:
> >
> > Hi Becket,
> >
> > quick clarification from my side because I think you misunderstood my
> > question. I did not suggest to let the SourceReader return only a single
> > record at a time when calling getNextRecords. As the return type
> indicates,
> > the method can return an arbitrary number of records.
> >
> > Cheers,
> > Till
> >
> > On Wed, Dec 11, 2019 at 10:13 AM Dawid Wysakowicz <
> [hidden email] <mailto:[hidden email]>>
> > wrote:
> >
> >> Hi Becket,
> >>
> >> Issue #1 - Design of Source interface
> >>
> >> I mentioned the lack of a method like
> Source#createEnumerator(Boundedness
> >> boundedness, SplitEnumeratorContext context), because without the
> current
> >> proposal is not complete/does not work.
> >>
> >> If we say that boundedness is an intrinsic property of a source imo we
> >> don't need the Source#createEnumerator(Boundedness boundedness,
> >> SplitEnumeratorContext context) method.
> >>
> >> Assuming a source from my previous example:
> >>
> >> Source source = KafkaSource.builder()
> >>  ...
> >>  .untilTimestamp(...)
> >>  .build()
> >>
> >> Would the enumerator differ if created like
> >> source.createEnumerator(CONTINUOUS_UNBOUNDED, ...) vs source
> >> .createEnumerator(BOUNDED, ...)? I know I am repeating myself, but this
> is
> >> the part that my opinion differ the most from the current proposal. I
> >> really think it should always be the source that tells if it is bounded
> or
> >> not. In the current proposal methods continousSource/boundedSource
> somewhat
> >> reconfigure the source, which I think is misleading.
> >>
> >> I think a call like:
> >>
> >> Source source = KafkaSource.builder()
> >>  ...
> >>  .readContinously() / readUntilLatestOffset() / readUntilTimestamp /
> readUntilOffsets / ...
> >>  .build()
> >>
> >> is way cleaner (and expressive) than
> >>
> >> Source source = KafkaSource.builder()
> >>  ...
> >>  .build()
> >>
> >>
> >> env.continousSource(source) // which actually underneath would call
> createEnumerator(CONTINUOUS, ctx) which would be equivalent to
> source.readContinously().createEnumerator(ctx)
> >> // or
> >> env.boundedSource(source) // which actually underneath would call
> createEnumerator(BOUNDED, ctx) which would be equivalent to
> source.readUntilLatestOffset().createEnumerator(ctx)
> >>
> >>
> >> Sorry for the comparison, but to me it seems there is too much magic
> >> happening underneath those two calls.
> >>
> >> I really believe the Source interface should have getBoundedness method
> >> instead of (supportBoundedness) + createEnumerator(Boundedness, ...)
> >>
> >>
> >> Issue #2 - Design of
> >> ExecutionEnvironment#source()/continuousSource()/boundedSource()
> >>
> >> As you might have guessed I am slightly in favor of option #2 modified.
> >> Yes I am aware every step of the dag would have to be able to say if it
> is
> >> bounded or not. I have a feeling it would be easier to express cross
> >> bounded/unbounded operations, but I must admit I have not thought it
> >> through thoroughly, In the spirit of batch is just a special case of
> >> streaming I thought BoundedStream would extend from DataStream. Correct
> me
> >> if I am wrong. In such a setup the cross bounded/unbounded operation
> could
> >> be expressed quite easily I think:
> >>
> >> DataStream {
> >>  DataStream join(DataStream, ...); // we could not really tell if the
> result is bounded or not, but because bounded stream is a special case of
> unbounded the API object is correct, irrespective if the left or right side
> of the join is bounded
> >> }
> >>
> >> BoundedStream extends DataStream {
> >>  BoundedStream join(BoundedStream, ...); // only if both sides are
> bounded the result can be bounded as well. However we do have access to the
> DataStream#join here, so you can still join with a DataStream
> >> }
> >>
> >>
> >> On the other hand I also see benefits of two completely disjointed APIs,
> >> as we could prohibit some streaming calls in the bounded API. I can't
> think
> >> of any unbounded operators that could not be implemented for bounded
> stream.
> >>
> >> Besides I think we both agree we don't like the method:
> >>
> >> DataStream boundedStream(Source)
> >>
> >> suggested in the current state of the FLIP. Do we ? :)
> >>
> >> Best,
> >>
> >> Dawid
> >>
> >> On 10/12/2019 18:57, Becket Qin wrote:
> >>
> >> Hi folks,
> >>
> >> Thanks for the discussion, great feedback. Also thanks Dawid for the
> >> explanation, it is much clearer now.
> >>
> >> One thing that is indeed missing from the FLIP is how the boundedness is
> >> passed to the Source implementation. So the API should be
> >> Source#createEnumerator(Boundedness boundedness, SplitEnumeratorContext
> >> context)
> >> And we can probably remove the Source#supportBoundedness(Boundedness
> >> boundedness) method.
> >>
> >> Assuming we have that, we are essentially choosing from one of the
> >> following two options:
> >>
> >> Option 1:
> >> // The source is continuous source, and only unbounded operations can be
> >> performed.
> >> DataStream<Type> datastream = env.continuousSource(someSource);
> >>
> >> // The source is bounded source, both bounded and unbounded operations
> can
> >> be performed.
> >> BoundedDataStream<Type> boundedDataStream =
> env.boundedSource(someSource);
> >>
> >>  - Pros:
> >>       a) explicit boundary between bounded / unbounded streams, it is
> >> quite simple and clear to the users.
> >>  - Cons:
> >>       a) For applications that do not involve bounded operations, they
> >> still have to call different API to distinguish bounded / unbounded
> streams.
> >>       b) No support for bounded stream to run in a streaming runtime
> >> setting, i.e. scheduling and operators behaviors.
> >>
> >>
> >> Option 2:
> >> // The source is either bounded or unbounded, but only unbounded
> operations
> >> could be performed on the returned DataStream.
> >> DataStream<Type> dataStream = env.source(someSource);
> >>
> >> // The source must be a bounded source, otherwise exception is thrown.
> >> BoundedDataStream<Type> boundedDataStream =
> >> env.boundedSource(boundedSource);
> >>
> >> The pros and cons are exactly the opposite of option 1.
> >>  - Pros:
> >>       a) For applications that do not involve bounded operations, they
> >> still have to call different API to distinguish bounded / unbounded
> streams.
> >>       b) Support for bounded stream to run in a streaming runtime
> setting,
> >> i.e. scheduling and operators behaviors.
> >>  - Cons:
> >>       a) Bounded / unbounded streams are kind of mixed, i.e. given a
> >> DataStream, it is not clear whether it is bounded or not, unless you
> have
> >> the access to its source.
> >>
> >>
> >> If we only think from the Source API perspective, option 2 seems a
> better
> >> choice because functionality wise it is a superset of option 1, at the
> cost
> >> of some seemingly acceptable ambiguity in the DataStream API.
> >> But if we look at the DataStream API as a whole, option 1 seems a
> clearer
> >> choice. For example, some times a library may have to know whether a
> >> certain task will finish or not. And it would be difficult to tell if
> the
> >> input is a DataStream, unless additional information is provided all the
> >> way from the Source. One possible solution is to have a *modified
> option 2*
> >> which adds a method to the DataStream API to indicate boundedness, such
> as
> >> getBoundedness(). It would solve the problem with a potential confusion
> of
> >> what is difference between a DataStream with getBoundedness()=true and a
> >> BoundedDataStream. But that seems not super difficult to explain.
> >>
> >> So from API's perspective, I don't have a strong opinion between
> *option 1*
> >> and *modified option 2. *I like the cleanness of option 1, but modified
> >> option 2 would be more attractive if we have concrete use case for the
> >> "Bounded stream with unbounded streaming runtime settings".
> >>
> >> Re: Till
> >>
> >>
> >> Maybe this has already been asked before but I was wondering why the
> >> SourceReader interface has the method pollNext which hands the
> >> responsibility of outputting elements to the SourceReader
> implementation?
> >> Has this been done for backwards compatibility reasons with the old
> source
> >> interface? If not, then one could define a Collection<E>
> getNextRecords()
> >> method which returns the currently retrieved records and then the caller
> >> emits them outside of the SourceReader. That way the interface would not
> >> allow to implement an outputting loop where we never hand back control
> to
> >> the caller. At the moment, this contract can be easily broken and is
> only
> >> mentioned loosely in the JavaDocs.
> >>
> >>
> >> The primary reason we handover the SourceOutput to the SourceReader is
> >> because sometimes it is difficult for a SourceReader to emit one record
> at
> >> a time. One example is some batched messaging systems which only have an
> >> offset for the entire batch instead of individual messages in the
> batch. In
> >> that case, returning one record at a time would leave the SourceReader
> in
> >> an uncheckpointable state because they can only checkpoint at the batch
> >> boundaries.
> >>
> >> Thanks,
> >>
> >> Jiangjie (Becket) Qin
> >>
> >> On Tue, Dec 10, 2019 at 5:33 PM Till Rohrmann <[hidden email]
> <mailto:[hidden email]>> <[hidden email] <mailto:
> [hidden email]>> wrote:
> >>
> >>
> >> Hi everyone,
> >>
> >> thanks for drafting this FLIP. It reads very well.
> >>
> >> Concerning Dawid's proposal, I tend to agree. The boundedness could come
> >> from the source and tell the system how to treat the operator
> (scheduling
> >> wise). From a user's perspective it should be fine to get back a
> DataStream
> >> when calling env.source(boundedSource) if he does not need special
> >> operations defined on a BoundedDataStream. If he needs this, then one
> could
> >> use the method BoundedDataStream env.boundedSource(boundedSource).
> >>
> >> If possible, we could enforce the proper usage of env.boundedSource() by
> >> introducing a BoundedSource type so that one cannot pass an
> >> unbounded source to it. That way users would not be able to shoot
> >> themselves in the foot.
> >>
> >> Maybe this has already been asked before but I was wondering why the
> >> SourceReader interface has the method pollNext which hands the
> >> responsibility of outputting elements to the SourceReader
> implementation?
> >> Has this been done for backwards compatibility reasons with the old
> source
> >> interface? If not, then one could define a Collection<E>
> getNextRecords()
> >> method which returns the currently retrieved records and then the caller
> >> emits them outside of the SourceReader. That way the interface would not
> >> allow to implement an outputting loop where we never hand back control
> to
> >> the caller. At the moment, this contract can be easily broken and is
> only
> >> mentioned loosely in the JavaDocs.
> >>
> >> Cheers,
> >> Till
> >>
> >> On Tue, Dec 10, 2019 at 7:49 AM Jingsong Li <[hidden email]
> <mailto:[hidden email]>> <[hidden email] <mailto:
> [hidden email]>>
> >> wrote:
> >>
> >>
> >> Hi all,
> >>
> >> I think current design is good.
> >>
> >> My understanding is:
> >>
> >> For execution mode: bounded mode and continuous mode, It's totally
> >> different. I don't think we have the ability to integrate the two models
> >>
> >> at
> >>
> >> present. It's about scheduling, memory, algorithms, States, etc. we
> >> shouldn't confuse them.
> >>
> >> For source capabilities: only bounded, only continuous, both bounded and
> >> continuous.
> >> I think Kafka is a source that can be ran both bounded
> >> and continuous execution mode.
> >> And Kafka with end offset should be ran both bounded
> >> and continuous execution mode.  Using apache Beam with Flink runner, I
> >>
> >> used
> >>
> >> to run a "bounded" Kafka in streaming mode. For our previous DataStream,
> >>
> >> it
> >>
> >> is not necessarily required that the source cannot be bounded.
> >>
> >> So it is my thought for Dawid's question:
> >> 1.pass a bounded source to continuousSource() +1
> >> 2.pass a continuous source to boundedSource() -1, should throw
> exception.
> >>
> >> In StreamExecutionEnvironment, continuousSource and boundedSource define
> >> the execution mode. It defines a clear boundary of execution mode.
> >>
> >> Best,
> >> Jingsong Lee
> >>
> >> On Tue, Dec 10, 2019 at 10:37 AM Jark Wu <[hidden email] <mailto:
> [hidden email]>> <[hidden email] <mailto:[hidden email]>> wrote:
> >>
> >>
> >> I agree with Dawid's point that the boundedness information should come
> >> from the source itself (e.g. the end timestamp), not through
> >> env.boundedSouce()/continuousSource().
> >> I think if we want to support something like `env.source()` that derive
> >>
> >> the
> >>
> >> execution mode from source, `supportsBoundedness(Boundedness)`
> >> method is not enough, because we don't know whether it is bounded or
> >>
> >> not.
> >>
> >> Best,
> >> Jark
> >>
> >>
> >> On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <[hidden email]
> <mailto:[hidden email]>> <[hidden email] <mailto:
> [hidden email]>>
> >> wrote:
> >>
> >>
> >> One more thing. In the current proposal, with the
> >> supportsBoundedness(Boundedness) method and the boundedness coming
> >>
> >> from
> >>
> >> either continuousSource or boundedSource I could not find how this
> >> information is fed back to the SplitEnumerator.
> >>
> >> Best,
> >>
> >> Dawid
> >>
> >> On 09/12/2019 13:52, Becket Qin wrote:
> >>
> >> Hi Dawid,
> >>
> >> Thanks for the comments. This actually brings another relevant
> >>
> >> question
> >>
> >> about what does a "bounded source" imply. I actually had the same
> >> impression when I look at the Source API. Here is what I understand
> >>
> >> after
> >>
> >> some discussion with Stephan. The bounded source has the following
> >>
> >> impacts.
> >>
> >> 1. API validity.
> >> - A bounded source generates a bounded stream so some operations
> >>
> >> that
> >>
> >> only
> >>
> >> works for bounded records would be performed, e.g. sort.
> >> - To expose these bounded stream only APIs, there are two options:
> >>     a. Add them to the DataStream API and throw exception if a
> >>
> >> method
> >>
> >> is
> >>
> >> called on an unbounded stream.
> >>     b. Create a BoundedDataStream class which is returned from
> >> env.boundedSource(), while DataStream is returned from
> >>
> >> env.continousSource().
> >>
> >> Note that this cannot be done by having single
> >>
> >> env.source(theSource)
> >>
> >> even
> >>
> >> the Source has a getBoundedness() method.
> >>
> >> 2. Scheduling
> >> - A bounded source could be computed stage by stage without
> >>
> >> bringing
> >>
> >> up
> >>
> >> all
> >>
> >> the tasks at the same time.
> >>
> >> 3. Operator behaviors
> >> - A bounded source indicates the records are finite so some
> >>
> >> operators
> >>
> >> can
> >>
> >> wait until it receives all the records before it starts the
> >>
> >> processing.
> >>
> >> In the above impact, only 1 is relevant to the API design. And the
> >>
> >> current
> >>
> >> proposal in FLIP-27 is following 1.b.
> >>
> >> // boundedness depends of source property, imo this should always
> >>
> >> be
> >>
> >> preferred
> >>
> >>
> >> DataStream<MyType> stream = env.source(theSource);
> >>
> >>
> >> In your proposal, does DataStream have bounded stream only methods?
> >>
> >> It
> >>
> >> looks it should have, otherwise passing a bounded Source to
> >>
> >> env.source()
> >>
> >> would be confusing. In that case, we will essentially do 1.a if an
> >> unbounded Source is created from env.source(unboundedSource).
> >>
> >> If we have the methods only supported for bounded streams in
> >>
> >> DataStream,
> >>
> >> it
> >>
> >> seems a little weird to have a separate BoundedDataStream
> >>
> >> interface.
> >>
> >> Am I understand it correctly?
> >>
> >> Thanks,
> >>
> >> Jiangjie (Becket) Qin
> >>
> >>
> >>
> >> On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <
> >>
> >> [hidden email] <mailto:[hidden email]>>
> >>
> >> wrote:
> >>
> >>
> >> Hi all,
> >>
> >> Really well written proposal and very important one. I must admit
> >>
> >> I
> >>
> >> have
> >>
> >> not understood all the intricacies of it yet.
> >>
> >> One question I have though is about where does the information
> >>
> >> about
> >>
> >> boundedness come from. I think in most cases it is a property of
> >>
> >> the
> >>
> >> source. As you described it might be e.g. end offset, a flag
> >>
> >> should
> >>
> >> it
> >>
> >> monitor new splits etc. I think it would be a really nice use case
> >>
> >> to
> >>
> >> be
> >>
> >> able to say:
> >>
> >> new KafkaSource().readUntil(long timestamp),
> >>
> >> which could work as an "end offset". Moreover I think all Bounded
> >>
> >> sources
> >>
> >> support continuous mode, but no intrinsically continuous source
> >>
> >> support
> >>
> >> the
> >>
> >> Bounded mode. If I understood the proposal correctly it suggest
> >>
> >> the
> >>
> >> boundedness sort of "comes" from the outside of the source, from
> >>
> >> the
> >>
> >> invokation of either boundedStream or continousSource.
> >>
> >> I am wondering if it would make sense to actually change the
> >>
> >> method
> >>
> >> boolean Source#supportsBoundedness(Boundedness)
> >>
> >> to
> >>
> >> Boundedness Source#getBoundedness().
> >>
> >> As for the methods #boundedSource, #continousSource, assuming the
> >> boundedness is property of the source they do not affect how the
> >>
> >> enumerator
> >>
> >> works, but mostly how the dag is scheduled, right? I am not
> >>
> >> against
> >>
> >> those
> >>
> >> methods, but I think it is a very specific use case to actually
> >>
> >> override
> >>
> >> the property of the source. In general I would expect users to
> >>
> >> only
> >>
> >> call
> >>
> >> env.source(theSource), where the source tells if it is bounded or
> >>
> >> not. I
> >>
> >> would suggest considering following set of methods:
> >>
> >> // boundedness depends of source property, imo this should always
> >>
> >> be
> >>
> >> preferred
> >>
> >> DataStream<MyType> stream = env.source(theSource);
> >>
> >>
> >> // always continous execution, whether bounded or unbounded source
> >>
> >> DataStream<MyType> boundedStream = env.continousSource(theSource);
> >>
> >> // imo this would make sense if the BoundedDataStream provides
> >>
> >> additional features unavailable for continous mode
> >>
> >> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
> >>
> >>
> >> Best,
> >>
> >> Dawid
> >>
> >>
> >> On 04/12/2019 11:25, Stephan Ewen wrote:
> >>
> >> Thanks, Becket, for updating this.
> >>
> >> I agree with moving the aspects you mentioned into separate FLIPs
> >>
> >> -
> >>
> >> this
> >>
> >> one way becoming unwieldy in size.
> >>
> >> +1 to the FLIP in its current state. Its a very detailed write-up,
> >>
> >> nicely
> >>
> >> done!
> >>
> >> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]
> <mailto:[hidden email]>> <[hidden email] <mailto:
> [hidden email]>>
> >>
> >> <
> >>
> >> [hidden email] <mailto:[hidden email]>> wrote:
> >>
> >> Hi all,
> >>
> >> Sorry for the long belated update. I have updated FLIP-27 wiki
> >>
> >> page
> >>
> >> with
> >>
> >> the latest proposals. Some noticeable changes include:
> >> 1. A new generic communication mechanism between SplitEnumerator
> >>
> >> and
> >>
> >> SourceReader.
> >> 2. Some detail API method signature changes.
> >>
> >> We left a few things out of this FLIP and will address them in
> >>
> >> separate
> >>
> >> FLIPs. Including:
> >> 1. Per split event time.
> >> 2. Event time alignment.
> >> 3. Fine grained failover for SplitEnumerator failure.
> >>
> >> Please let us know if you have any question.
> >>
> >> Thanks,
> >>
> >> Jiangjie (Becket) Qin
> >>
> >> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email] <mailto:
> [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> >>
> >> [hidden email] <mailto:[hidden email]>> wrote:
> >>
> >> Hi  Łukasz!
> >>
> >> Becket and me are working hard on figuring out the last details
> >>
> >> and
> >>
> >> implementing the first PoC. We would update the FLIP hopefully
> >>
> >> next
> >>
> >> week.
> >>
> >> There is a fair chance that a first version of this will be in
> >>
> >> 1.10,
> >>
> >> but
> >>
> >> I
> >>
> >> think it will take another release to battle test it and migrate
> >>
> >> the
> >>
> >> connectors.
> >>
> >> Best,
> >> Stephan
> >>
> >>
> >>
> >>
> >> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <[hidden email]
> <mailto:[hidden email]>
> >>
> >> <
> >>
> >> [hidden email] <mailto:[hidden email]>>
> >>
> >> wrote:
> >>
> >> Hi,
> >>
> >> This proposal looks very promising for us. Do you have any plans
> >>
> >> in
> >>
> >> which
> >>
> >> Flink release it is going to be released? We are thinking on
> >>
> >> using a
> >>
> >> Data
> >>
> >> Set API for our future use cases but on the other hand Data Set
> >>
> >> API
> >>
> >> is
> >>
> >> going to be deprecated so using proposed bounded data streams
> >>
> >> solution
> >>
> >> could be more viable in the long term.
> >>
> >> Thanks,
> >> Łukasz
> >>
> >> On 2019/10/01 15:48:03, Thomas Weise <[hidden email] <mailto:
> [hidden email]>> <[hidden email] <mailto:
> [hidden email]>> <
> >>
> >> [hidden email] <mailto:[hidden email]>> wrote:
> >>
> >> Thanks for putting together this proposal!
> >>
> >> I see that the "Per Split Event Time" and "Event Time Alignment"
> >>
> >> sections
> >>
> >> are still TBD.
> >>
> >> It would probably be good to flesh those out a bit before
> >>
> >> proceeding
> >>
> >> too
> >>
> >> far
> >>
> >> as the event time alignment will probably influence the
> >>
> >> interaction
> >>
> >> with
> >>
> >> the split reader, specifically ReaderStatus
> >>
> >> emitNext(SourceOutput<E>
> >>
> >> output).
> >>
> >> We currently have only one implementation for event time alignment
> >>
> >> in
> >>
> >> the
> >>
> >> Kinesis consumer. The synchronization in that case takes place as
> >>
> >> the
> >>
> >> last
> >>
> >> step before records are emitted downstream (RecordEmitter). With
> >>
> >> the
> >>
> >> currently proposed interfaces, the equivalent can be implemented
> >>
> >> in
> >>
> >> the
> >>
> >> reader loop, although note that in the Kinesis consumer the per
> >>
> >> shard
> >>
> >> threads push records.
> >>
> >> Synchronization has not been implemented for the Kafka consumer
> >>
> >> yet.
> >>
> >> https://issues.apache.org/jira/browse/FLINK-12675 <
> https://issues.apache.org/jira/browse/FLINK-12675>
> >>
> >> When I looked at it, I realized that the implementation will look
> >>
> >> quite
> >>
> >> different
> >> from Kinesis because it needs to take place in the pull part,
> >>
> >> where
> >>
> >> records
> >>
> >> are taken from the Kafka client. Due to the multiplexing it cannot
> >>
> >> be
> >>
> >> done
> >>
> >> by blocking the split thread like it currently works for Kinesis.
> >>
> >> Reading
> >>
> >> from individual Kafka partitions needs to be controlled via
> >>
> >> pause/resume
> >>
> >> on the Kafka client.
> >>
> >> To take on that responsibility the split thread would need to be
> >>
> >> aware
> >>
> >> of
> >>
> >> the
> >> watermarks or at least whether it should or should not continue to
> >>
> >> consume
> >>
> >> a given split and this may require a different SourceReader or
> >>
> >> SourceOutput
> >>
> >> interface.
> >>
> >> Thanks,
> >> Thomas
> >>
> >>
> >> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email] <mailto:
> [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> >>
> >> [hidden email] <mailto:[hidden email]>> wrote:
> >>
> >> Hi Stephan,
> >>
> >> Thank you for feedback!
> >> Will take a look at your branch before public discussing.
> >>
> >>
> >> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]
> <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>>
> >>
> >> <
> >>
> >> [hidden email] <mailto:[hidden email]>>
> >>
> >> wrote:
> >>
> >> Hi Biao!
> >>
> >> Thanks for reviving this. I would like to join this discussion,
> >>
> >> but
> >>
> >> am
> >>
> >> quite occupied with the 1.9 release, so can we maybe pause this
> >>
> >> discussion
> >>
> >> for a week or so?
> >>
> >> In the meantime I can share some suggestion based on prior
> >>
> >> experiments:
> >>
> >> How to do watermarks / timestamp extractors in a simpler and more
> >>
> >> flexible
> >>
> >> way. I think that part is quite promising should be part of the
> >>
> >> new
> >>
> >> source
> >>
> >> interface.
> >>
> >>
> >>
> >>
> >>
> >>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> <
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> >
> >>
> >>
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> <
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> >
> >>
> >> Some experiments on how to build the source reader and its
> >>
> >> library
> >>
> >> for
> >>
> >> common threading/split patterns:
> >>
> >>
> >>
> >>
> >>
> >>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> <
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> >
> >>
> >> Best,
> >> Stephan
> >>
> >>
> >> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email] <mailto:
> [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> >>
> >> [hidden email] <mailto:[hidden email]>>
> >>
> >> wrote:
> >>
> >> Hi devs,
> >>
> >> Since 1.9 is nearly released, I think we could get back to
> >>
> >> FLIP-27.
> >>
> >> I
> >>
> >> believe it should be included in 1.10.
> >>
> >> There are so many things mentioned in document of FLIP-27. [1] I
> >>
> >> think
> >>
> >> we'd better discuss them separately. However the wiki is not a
> >>
> >> good
> >>
> >> place
> >>
> >> to discuss. I wrote google doc about SplitReader API which
> >>
> >> misses
> >>
> >> some
> >>
> >> details in the document. [2]
> >>
> >> 1.
> >>
> >>
> >>
> >>
> >>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> <
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> >
> >>
> >> 2.
> >>
> >>
> >>
> >>
> >>
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> <
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> >
> >>
> >> CC Stephan, Aljoscha, Piotrek, Becket
> >>
> >>
> >> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email] <mailto:
> [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> >>
> >> [hidden email] <mailto:[hidden email]>>
> >>
> >> wrote:
> >>
> >> Hi Steven,
> >> Thank you for the feedback. Please take a look at the document
> >>
> >> FLIP-27
> >>
> >> <
> >>
> >>
> >>
> >>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> <
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> >
> >>
> >> which
> >>
> >> is updated recently. A lot of details of enumerator were added
> >>
> >> in
> >>
> >> this
> >>
> >> document. I think it would help.
> >>
> >> Steven Wu <[hidden email] <mailto:[hidden email]>> <
> [hidden email] <mailto:[hidden email]>> <[hidden email]
> <mailto:[hidden email]>> <[hidden email] <mailto:
> [hidden email]>>
> >>
> >> 于2019年3月28日周四
> >>
> >> 下午12:52写道：
> >>
> >> This proposal mentioned that SplitEnumerator might run on the
> >> JobManager or
> >> in a single task on a TaskManager.
> >>
> >> if enumerator is a single task on a taskmanager, then the job
> >>
> >> DAG
> >>
> >> can
> >>
> >> never
> >> been embarrassingly parallel anymore. That will nullify the
> >>
> >> leverage
> >>
> >> of
> >>
> >> fine-grained recovery for embarrassingly parallel jobs.
> >>
> >> It's not clear to me what's the implication of running
> >>
> >> enumerator
> >>
> >> on
> >>
> >> the
> >>
> >> jobmanager. So I will leave that out for now.
> >>
> >> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email] <mailto:
> [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> >>
> >> [hidden email] <mailto:[hidden email]>>
> >>
> >> wrote:
> >>
> >> Hi Stephan & Piotrek,
> >>
> >> Thank you for feedback.
> >>
> >> It seems that there are a lot of things to do in community.
> >>
> >> I
> >>
> >> am
> >>
> >> just
> >>
> >> afraid that this discussion may be forgotten since there so
> >>
> >> many
> >>
> >> proposals
> >>
> >> recently.
> >> Anyway, wish to see the split topics soon :)
> >>
> >> Piotr Nowojski <[hidden email] <mailto:[hidden email]>> <
> [hidden email] <mailto:[hidden email]>> <
> [hidden email] <mailto:[hidden email]>> <
> [hidden email] <mailto:[hidden email]>>
> >>
> >> 于2019年1月24日周四
> >>
> >> 下午8:21写道：
> >>
> >> Hi Biao!
> >>
> >> This discussion was stalled because of preparations for
> >>
> >> the
> >>
> >> open
> >>
> >> sourcing
> >>
> >> & merging Blink. I think before creating the tickets we
> >>
> >> should
> >>
> >> split this
> >>
> >> discussion into topics/areas outlined by Stephan and
> >>
> >> create
> >>
> >> Flips
> >>
> >> for
> >>
> >> that.
> >>
> >> I think there is no chance for this to be completed in
> >>
> >> couple
> >>
> >> of
> >>
> >> remaining
> >>
> >> weeks/1 month before 1.8 feature freeze, however it would
> >>
> >> be
> >>
> >> good
> >>
> >> to aim
> >>
> >> with those changes for 1.9.
> >>
> >> Piotrek
> >>
> >>
> >> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email] <mailto:
> [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> >>
> >> [hidden email] <mailto:[hidden email]>>
> >>
> >> wrote:
> >>
> >> Hi community,
> >> The summary of Stephan makes a lot sense to me. It is
> >>
> >> much
> >>
> >> clearer
> >>
> >> indeed
> >>
> >> after splitting the complex topic into small ones.
> >> I was wondering is there any detail plan for next step?
> >>
> >> If
> >>
> >> not,
> >>
> >> I
> >>
> >> would
> >>
> >> like to push this thing forward by creating some JIRA
> >>
> >> issues.
> >>
> >> Another question is that should version 1.8 include
> >>
> >> these
> >>
> >> features?
> >>
> >> Stephan Ewen <[hidden email] <mailto:[hidden email]>> <
> [hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:
> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> 于2018年12月1日周六
> >>
> >> 上午4:20写道：
> >>
> >> Thanks everyone for the lively discussion. Let me try
> >>
> >> to
> >>
> >> summarize
> >>
> >> where I
> >>
> >> see convergence in the discussion and open issues.
> >> I'll try to group this by design aspect of the source.
> >>
> >> Please
> >>
> >> let me
> >>
> >> know
> >>
> >> if I got things wrong or missed something crucial here.
> >>
> >> For issues 1-3, if the below reflects the state of the
> >>
> >> discussion, I
> >>
> >> would
> >>
> >> try and update the FLIP in the next days.
> >> For the remaining ones we need more discussion.
> >>
> >> I would suggest to fork each of these aspects into a
> >>
> >> separate
> >>
> >> mail
> >>
> >> thread,
> >>
> >> or will loose sight of the individual aspects.
> >>
> >> *(1) Separation of Split Enumerator and Split Reader*
> >>
> >> - All seem to agree this is a good thing
> >> - Split Enumerator could in the end live on JobManager
> >>
> >> (and
> >>
> >> assign
> >>
> >> splits
> >>
> >> via RPC) or in a task (and assign splits via data
> >>
> >> streams)
> >>
> >> - this discussion is orthogonal and should come later,
> >>
> >> when
> >>
> >> the
> >>
> >> interface
> >>
> >> is agreed upon.
> >>
> >> *(2) Split Readers for one or more splits*
> >>
> >> - Discussion seems to agree that we need to support
> >>
> >> one
> >>
> >> reader
> >>
> >> that
> >>
> >> possibly handles multiple splits concurrently.
> >> - The requirement comes from sources where one
> >>
> >> poll()-style
> >>
> >> call
> >>
> >> fetches
> >>
> >> data from different splits / partitions
> >>   --> example sources that require that would be for
> >>
> >> example
> >>
> >> Kafka,
> >>
> >> Pravega, Pulsar
> >>
> >> - Could have one split reader per source, or multiple
> >>
> >> split
> >>
> >> readers
> >>
> >> that
> >>
> >> share the "poll()" function
> >> - To not make it too complicated, we can start with
> >>
> >> thinking
> >>
> >> about
> >>
> >> one
> >>
> >> split reader for all splits initially and see if that
> >>
> >> covers
> >>
> >> all
> >>
> >> requirements
> >>
> >> *(3) Threading model of the Split Reader*
> >>
> >> - Most active part of the discussion ;-)
> >>
> >> - A non-blocking way for Flink's task code to interact
> >>
> >> with
> >>
> >> the
> >>
> >> source
> >>
> >> is
> >>
> >> needed in order to a task runtime code based on a
> >> single-threaded/actor-style task design
> >>   --> I personally am a big proponent of that, it will
> >>
> >> help
> >>
> >> with
> >>
> >> well-behaved checkpoints, efficiency, and simpler yet
> >>
> >> more
> >>
> >> robust
> >>
> >> runtime
> >>
> >> code
> >>
> >> - Users care about simple abstraction, so as a
> >>
> >> subclass
> >>
> >> of
> >>
> >> SplitReader
> >>
> >> (non-blocking / async) we need to have a
> >>
> >> BlockingSplitReader
> >>
> >> which
> >>
> >> will
> >>
> >> form the basis of most source implementations.
> >>
> >> BlockingSplitReader
> >>
> >> lets
> >>
> >> users do blocking simple poll() calls.
> >> - The BlockingSplitReader would spawn a thread (or
> >>
> >> more)
> >>
> >> and
> >>
> >> the
> >>
> >> thread(s) can make blocking calls and hand over data
> >>
> >> buffers
> >>
> >> via
> >>
> >> a
> >>
> >> blocking
> >>
> >> queue
> >> - This should allow us to cover both, a fully async
> >>
> >> runtime,
> >>
> >> and a
> >>
> >> simple
> >>
> >> blocking interface for users.
> >> - This is actually very similar to how the Kafka
> >>
> >> connectors
> >>
> >> work.
> >>
> >> Kafka
> >>
> >> 9+ with one thread, Kafka 8 with multiple threads
> >>
> >> - On the base SplitReader (the async one), the
> >>
> >> non-blocking
> >>
> >> method
> >>
> >> that
> >>
> >> gets the next chunk of data would signal data
> >>
> >> availability
> >>
> >> via
> >>
> >> a
> >>
> >> CompletableFuture, because that gives the best
> >>
> >> flexibility
> >>
> >> (can
> >>
> >> await
> >>
> >> completion or register notification handlers).
> >> - The source task would register a "thenHandle()" (or
> >>
> >> similar)
> >>
> >> on the
> >>
> >> future to put a "take next data" task into the
> >>
> >> actor-style
> >>
> >> mailbox
> >>
> >> *(4) Split Enumeration and Assignment*
> >>
> >> - Splits may be generated lazily, both in cases where
> >>
> >> there
> >>
> >> is a
> >>
> >> limited
> >>
> >> number of splits (but very many), or splits are
> >>
> >> discovered
> >>
> >> over
> >>
> >> time
> >>
> >> - Assignment should also be lazy, to get better load
> >>
> >> balancing
> >>
> >> - Assignment needs support locality preferences
> >>
> >> - Possible design based on discussion so far:
> >>
> >>   --> SplitReader has a method "addSplits(SplitT...)"
> >>
> >> to
> >>
> >> add
> >>
> >> one or
> >>
> >> more
> >>
> >> splits. Some split readers might assume they have only
> >>
> >> one
> >>
> >> split
> >>
> >> ever,
> >>
> >> concurrently, others assume multiple splits. (Note:
> >>
> >> idea
> >>
> >> behind
> >>
> >> being
> >>
> >> able
> >>
> >> to add multiple splits at the same time is to ease
> >>
> >> startup
> >>
> >> where
> >>
> >> multiple
> >>
> >> splits may be assigned instantly.)
> >>   --> SplitReader has a context object on which it can
> >>
> >> call
> >>
> >> indicate
> >>
> >> when
> >>
> >> splits are completed. The enumerator gets that
> >>
> >> notification and
> >>
> >> can
> >>
> >> use
> >>
> >> to
> >>
> >> decide when to assign new splits. This should help both
> >>
> >> in
> >>
> >> cases
> >>
> >> of
> >>
> >> sources
> >>
> >> that take splits lazily (file readers) and in case the
> >>
> >> source
> >>
> >> needs to
> >>
> >> preserve a partial order between splits (Kinesis,
> >>
> >> Pravega,
> >>
> >> Pulsar may
> >>
> >> need
> >>
> >> that).
> >>   --> SplitEnumerator gets notification when
> >>
> >> SplitReaders
> >>
> >> start
> >>
> >> and
> >>
> >> when
> >>
> >> they finish splits. They can decide at that moment to
> >>
> >> push
> >>
> >> more
> >>
> >> splits
> >>
> >> to
> >>
> >> that reader
> >>   --> The SplitEnumerator should probably be aware of
> >>
> >> the
> >>
> >> source
> >>
> >> parallelism, to build its initial distribution.
> >>
> >> - Open question: Should the source expose something
> >>
> >> like
> >>
> >> "host
> >>
> >> preferences", so that yarn/mesos/k8s can take this into
> >>
> >> account
> >>
> >> when
> >>
> >> selecting a node to start a TM on?
> >>
> >> *(5) Watermarks and event time alignment*
> >>
> >> - Watermark generation, as well as idleness, needs to
> >>
> >> be
> >>
> >> per
> >>
> >> split
> >>
> >> (like
> >>
> >> currently in the Kafka Source, per partition)
> >> - It is desirable to support optional
> >>
> >> event-time-alignment,
> >>
> >> meaning
> >>
> >> that
> >>
> >> splits that are ahead are back-pressured or temporarily
> >>
> >> unsubscribed
> >>
> >> - I think i would be desirable to encapsulate
> >>
> >> watermark
> >>
> >> generation
> >>
> >> logic
> >>
> >> in watermark generators, for a separation of concerns.
> >>
> >> The
> >>
> >> watermark
> >>
> >> generators should run per split.
> >> - Using watermark generators would also help with
> >>
> >> another
> >>
> >> problem of
> >>
> >> the
> >>
> >> suggested interface, namely supporting non-periodic
> >>
> >> watermarks
> >>
> >> efficiently.
> >>
> >> - Need a way to "dispatch" next record to different
> >>
> >> watermark
> >>
> >> generators
> >>
> >> - Need a way to tell SplitReader to "suspend" a split
> >>
> >> until a
> >>
> >> certain
> >>
> >> watermark is reached (event time backpressure)
> >> - This would in fact be not needed (and thus simpler)
> >>
> >> if
> >>
> >> we
> >>
> >> had
> >>
> >> a
> >>
> >> SplitReader per split and may be a reason to re-open
> >>
> >> that
> >>
> >> discussion
> >>
> >> *(6) Watermarks across splits and in the Split
> >>
> >> Enumerator*
> >>
> >> - The split enumerator may need some watermark
> >>
> >> awareness,
> >>
> >> which
> >>
> >> should
> >>
> >> be
> >>
> >> purely based on split metadata (like create timestamp
> >>
> >> of
> >>
> >> file
> >>
> >> splits)
> >>
> >> - If there are still more splits with overlapping
> >>
> >> event
> >>
> >> time
> >>
> >> range
> >>
> >> for
> >>
> >> a
> >>
> >> split reader, then that split reader should not advance
> >>
> >> the
> >>
> >> watermark
> >>
> >> within the split beyond the overlap boundary. Otherwise
> >>
> >> future
> >>
> >> splits
> >>
> >> will
> >>
> >> produce late data.
> >>
> >> - One way to approach this could be that the split
> >>
> >> enumerator
> >>
> >> may
> >>
> >> send
> >>
> >> watermarks to the readers, and the readers cannot emit
> >>
> >> watermarks
> >>
> >> beyond
> >>
> >> that received watermark.
> >> - Many split enumerators would simply immediately send
> >>
> >> Long.MAX
> >>
> >> out
> >>
> >> and
> >>
> >> leave the progress purely to the split readers.
> >>
> >> - For event-time alignment / split back pressure, this
> >>
> >> begs
> >>
> >> the
> >>
> >> question
> >>
> >> how we can avoid deadlocks that may arise when splits
> >>
> >> are
> >>
> >> suspended
> >>
> >> for
> >>
> >> event time back pressure,
> >>
> >> *(7) Batch and streaming Unification*
> >>
> >> - Functionality wise, the above design should support
> >>
> >> both
> >>
> >> - Batch often (mostly) does not care about reading "in
> >>
> >> order"
> >>
> >> and
> >>
> >> generating watermarks
> >>   --> Might use different enumerator logic that is
> >>
> >> more
> >>
> >> locality
> >>
> >> aware
> >>
> >> and ignores event time order
> >>   --> Does not generate watermarks
> >> - Would be great if bounded sources could be
> >>
> >> identified
> >>
> >> at
> >>
> >> compile
> >>
> >> time,
> >>
> >> so that "env.addBoundedSource(...)" is type safe and
> >>
> >> can
> >>
> >> return a
> >>
> >> "BoundedDataStream".
> >> - Possible to defer this discussion until later
> >>
> >> *Miscellaneous Comments*
> >>
> >> - Should the source have a TypeInformation for the
> >>
> >> produced
> >>
> >> type,
> >>
> >> instead
> >>
> >> of a serializer? We need a type information in the
> >>
> >> stream
> >>
> >> anyways, and
> >>
> >> can
> >>
> >> derive the serializer from that. Plus, creating the
> >>
> >> serializer
> >>
> >> should
> >>
> >> respect the ExecutionConfig.
> >>
> >> - The TypeSerializer interface is very powerful but
> >>
> >> also
> >>
> >> not
> >>
> >> easy to
> >>
> >> implement. Its purpose is to handle data super
> >>
> >> efficiently,
> >>
> >> support
> >>
> >> flexible ways of evolution, etc.
> >> For metadata I would suggest to look at the
> >>
> >> SimpleVersionedSerializer
> >>
> >> instead, which is used for example for checkpoint
> >>
> >> master
> >>
> >> hooks,
> >>
> >> or for
> >>
> >> the
> >>
> >> streaming file sink. I think that is is a good match
> >>
> >> for
> >>
> >> cases
> >>
> >> where
> >>
> >> we
> >>
> >> do
> >>
> >> not need more than ser/deser (no copy, etc.) and don't
> >>
> >> need to
> >>
> >> push
> >>
> >> versioning out of the serialization paths for best
> >>
> >> performance
> >>
> >> (as in
> >>
> >> the
> >>
> >> TypeSerializer)
> >>
> >>
> >> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
> >>
> >> [hidden email]>
> >>
> >> wrote:
> >>
> >>
> >> Hi Biao,
> >>
> >> Thanks for the answer!
> >>
> >> So given the multi-threaded readers, now we have as
> >>
> >> open
> >>
> >> questions:
> >>
> >> 1) How do we let the checkpoints pass through our
> >>
> >> multi-threaded
> >>
> >> reader
> >>
> >> operator?
> >>
> >> 2) Do we have separate reader and source operators or
> >>
> >> not? In
> >>
> >> the
> >>
> >> strategy
> >>
> >> that has a separate source, the source operator has a
> >>
> >> parallelism of
> >>
> >> 1
> >>
> >> and
> >>
> >> is responsible for split recovery only.
> >>
> >> For the first one, given also the constraints
> >>
> >> (blocking,
> >>
> >> finite
> >>
> >> queues,
> >>
> >> etc), I do not have an answer yet.
> >>
> >> For the 2nd, I think that we should go with separate
> >>
> >> operators
> >>
> >> for
> >>
> >> the
> >>
> >> source and the readers, for the following reasons:
> >>
> >> 1) This is more aligned with a potential future
> >>
> >> improvement
> >>
> >> where the
> >>
> >> split
> >>
> >> discovery becomes a responsibility of the JobManager
> >>
> >> and
> >>
> >> readers are
> >>
> >> pooling more work from the JM.
> >>
> >> 2) The source is going to be the "single point of
> >>
> >> truth".
> >>
> >> It
> >>
> >> will
> >>
> >> know
> >>
> >> what
> >>
> >> has been processed and what not. If the source and the
> >>
> >> readers
> >>
> >> are a
> >>
> >> single
> >>
> >> operator with parallelism > 1, or in general, if the
> >>
> >> split
> >>
> >> discovery
> >>
> >> is
> >>
> >> done by each task individually, then:
> >>  i) we have to have a deterministic scheme for each
> >>
> >> reader to
> >>
> >> assign
> >>
> >> splits to itself (e.g. mod subtaskId). This is not
> >>
> >> necessarily
> >>
> >> trivial
> >>
> >> for
> >>
> >> all sources.
> >>  ii) each reader would have to keep a copy of all its
> >>
> >> processed
> >>
> >> slpits
> >>
> >>  iii) the state has to be a union state with a
> >>
> >> non-trivial
> >>
> >> merging
> >>
> >> logic
> >>
> >> in order to support rescaling.
> >>
> >> Two additional points that you raised above:
> >>
> >> i) The point that you raised that we need to keep all
> >>
> >> splits
> >>
> >> (processed
> >>
> >> and
> >>
> >> not-processed) I think is a bit of a strong
> >>
> >> requirement.
> >>
> >> This
> >>
> >> would
> >>
> >> imply
> >>
> >> that for infinite sources the state will grow
> >>
> >> indefinitely.
> >>
> >> This is
> >>
> >> problem
> >>
> >> is even more pronounced if we do not have a single
> >>
> >> source
> >>
> >> that
> >>
> >> assigns
> >>
> >> splits to readers, as each reader will have its own
> >>
> >> copy
> >>
> >> of
> >>
> >> the
> >>
> >> state.
> >>
> >> ii) it is true that for finite sources we need to
> >>
> >> somehow
> >>
> >> not
> >>
> >> close
> >>
> >> the
> >>
> >> readers when the source/split discoverer finishes. The
> >> ContinuousFileReaderOperator has a work-around for
> >>
> >> that.
> >>
> >> It is
> >>
> >> not
> >>
> >> elegant,
> >>
> >> and checkpoints are not emitted after closing the
> >>
> >> source,
> >>
> >> but
> >>
> >> this, I
> >>
> >> believe, is a bigger problem which requires more
> >>
> >> changes
> >>
> >> than
> >>
> >> just
> >>
> >> refactoring the source interface.
> >>
> >> Cheers,
> >> Kostas
> >>
> >>
> >>
> >>
> >> --
> >> Best, Jingsong Lee
>
>

[Jingsong Li]

Hi Becket,

I also have some performance concerns too.

If I understand correctly, SourceOutput will emit data per record into the
queue? I'm worried about the multithreading performance of this queue.

> One example is some batched messaging systems which only have an offset
for the entire batch instead of individual messages in the batch.

As you said, there are some batched system source, like parquet/orc source.
Could we have the batch emit interface to improve performance? The queue of
per record may cause performance degradation.

Best,
Jingsong Lee

On Thu, Dec 12, 2019 at 9:15 AM Jark Wu <[hidden email]> wrote:

> Hi Becket,
>
> I think Dawid explained things clearly and makes a lot of sense.
> I'm also in favor of #2, because #1 doesn't work for our future unified
> envrionment.
>
> You can see the vision in this documentation [1]. In the future, we would
> like to
> drop the global streaming/batch mode in SQL (i.e.
> EnvironmentSettings#inStreamingMode/inBatchMode).
> A source is bounded or unbounded once defined, so queries can be inferred
> from source to run
> in streaming or batch or hybrid mode. However, in #1, we will lose this
> ability because the framework
> doesn't know whether the source is bounded or unbounded.
>
> Best,
> Jark
>
>
> [1]:
>
> https://docs.google.com/document/d/1yrKXEIRATfxHJJ0K3t6wUgXAtZq8D-XgvEnvl2uUcr0/edit#heading=h.v4ib17buma1p
>
> On Wed, 11 Dec 2019 at 20:52, Piotr Nowojski <[hidden email]> wrote:
>
> > Hi,
> >
> > Regarding the:
> >
> > Collection<E> getNextRecords()
> >
> > I’m pretty sure such design would unfortunately impact the performance
> > (accessing and potentially creating the collection on the hot path).
> >
> > Also the
> >
> > InputStatus emitNext(DataOutput<T> output) throws Exception;
> > or
> > Status pollNext(SourceOutput<T> sourceOutput) throws Exception;
> >
> > Gives us some opportunities in the future, to allow Source hot looping
> > inside, until it receives some signal “please exit because of some
> reasons”
> > (output collector could return such hint upon collecting the result). But
> > that’s another topic outside of this FLIP’s scope.
> >
> > Piotrek
> >
> > > On 11 Dec 2019, at 10:41, Till Rohrmann <[hidden email]> wrote:
> > >
> > > Hi Becket,
> > >
> > > quick clarification from my side because I think you misunderstood my
> > > question. I did not suggest to let the SourceReader return only a
> single
> > > record at a time when calling getNextRecords. As the return type
> > indicates,
> > > the method can return an arbitrary number of records.
> > >
> > > Cheers,
> > > Till
> > >
> > > On Wed, Dec 11, 2019 at 10:13 AM Dawid Wysakowicz <
> > [hidden email] <mailto:[hidden email]>>
> > > wrote:
> > >
> > >> Hi Becket,
> > >>
> > >> Issue #1 - Design of Source interface
> > >>
> > >> I mentioned the lack of a method like
> > Source#createEnumerator(Boundedness
> > >> boundedness, SplitEnumeratorContext context), because without the
> > current
> > >> proposal is not complete/does not work.
> > >>
> > >> If we say that boundedness is an intrinsic property of a source imo we
> > >> don't need the Source#createEnumerator(Boundedness boundedness,
> > >> SplitEnumeratorContext context) method.
> > >>
> > >> Assuming a source from my previous example:
> > >>
> > >> Source source = KafkaSource.builder()
> > >>  ...
> > >>  .untilTimestamp(...)
> > >>  .build()
> > >>
> > >> Would the enumerator differ if created like
> > >> source.createEnumerator(CONTINUOUS_UNBOUNDED, ...) vs source
> > >> .createEnumerator(BOUNDED, ...)? I know I am repeating myself, but
> this
> > is
> > >> the part that my opinion differ the most from the current proposal. I
> > >> really think it should always be the source that tells if it is
> bounded
> > or
> > >> not. In the current proposal methods continousSource/boundedSource
> > somewhat
> > >> reconfigure the source, which I think is misleading.
> > >>
> > >> I think a call like:
> > >>
> > >> Source source = KafkaSource.builder()
> > >>  ...
> > >>  .readContinously() / readUntilLatestOffset() / readUntilTimestamp /
> > readUntilOffsets / ...
> > >>  .build()
> > >>
> > >> is way cleaner (and expressive) than
> > >>
> > >> Source source = KafkaSource.builder()
> > >>  ...
> > >>  .build()
> > >>
> > >>
> > >> env.continousSource(source) // which actually underneath would call
> > createEnumerator(CONTINUOUS, ctx) which would be equivalent to
> > source.readContinously().createEnumerator(ctx)
> > >> // or
> > >> env.boundedSource(source) // which actually underneath would call
> > createEnumerator(BOUNDED, ctx) which would be equivalent to
> > source.readUntilLatestOffset().createEnumerator(ctx)
> > >>
> > >>
> > >> Sorry for the comparison, but to me it seems there is too much magic
> > >> happening underneath those two calls.
> > >>
> > >> I really believe the Source interface should have getBoundedness
> method
> > >> instead of (supportBoundedness) + createEnumerator(Boundedness, ...)
> > >>
> > >>
> > >> Issue #2 - Design of
> > >> ExecutionEnvironment#source()/continuousSource()/boundedSource()
> > >>
> > >> As you might have guessed I am slightly in favor of option #2
> modified.
> > >> Yes I am aware every step of the dag would have to be able to say if
> it
> > is
> > >> bounded or not. I have a feeling it would be easier to express cross
> > >> bounded/unbounded operations, but I must admit I have not thought it
> > >> through thoroughly, In the spirit of batch is just a special case of
> > >> streaming I thought BoundedStream would extend from DataStream.
> Correct
> > me
> > >> if I am wrong. In such a setup the cross bounded/unbounded operation
> > could
> > >> be expressed quite easily I think:
> > >>
> > >> DataStream {
> > >>  DataStream join(DataStream, ...); // we could not really tell if the
> > result is bounded or not, but because bounded stream is a special case of
> > unbounded the API object is correct, irrespective if the left or right
> side
> > of the join is bounded
> > >> }
> > >>
> > >> BoundedStream extends DataStream {
> > >>  BoundedStream join(BoundedStream, ...); // only if both sides are
> > bounded the result can be bounded as well. However we do have access to
> the
> > DataStream#join here, so you can still join with a DataStream
> > >> }
> > >>
> > >>
> > >> On the other hand I also see benefits of two completely disjointed
> APIs,
> > >> as we could prohibit some streaming calls in the bounded API. I can't
> > think
> > >> of any unbounded operators that could not be implemented for bounded
> > stream.
> > >>
> > >> Besides I think we both agree we don't like the method:
> > >>
> > >> DataStream boundedStream(Source)
> > >>
> > >> suggested in the current state of the FLIP. Do we ? :)
> > >>
> > >> Best,
> > >>
> > >> Dawid
> > >>
> > >> On 10/12/2019 18:57, Becket Qin wrote:
> > >>
> > >> Hi folks,
> > >>
> > >> Thanks for the discussion, great feedback. Also thanks Dawid for the
> > >> explanation, it is much clearer now.
> > >>
> > >> One thing that is indeed missing from the FLIP is how the boundedness
> is
> > >> passed to the Source implementation. So the API should be
> > >> Source#createEnumerator(Boundedness boundedness,
> SplitEnumeratorContext
> > >> context)
> > >> And we can probably remove the Source#supportBoundedness(Boundedness
> > >> boundedness) method.
> > >>
> > >> Assuming we have that, we are essentially choosing from one of the
> > >> following two options:
> > >>
> > >> Option 1:
> > >> // The source is continuous source, and only unbounded operations can
> be
> > >> performed.
> > >> DataStream<Type> datastream = env.continuousSource(someSource);
> > >>
> > >> // The source is bounded source, both bounded and unbounded operations
> > can
> > >> be performed.
> > >> BoundedDataStream<Type> boundedDataStream =
> > env.boundedSource(someSource);
> > >>
> > >>  - Pros:
> > >>       a) explicit boundary between bounded / unbounded streams, it is
> > >> quite simple and clear to the users.
> > >>  - Cons:
> > >>       a) For applications that do not involve bounded operations, they
> > >> still have to call different API to distinguish bounded / unbounded
> > streams.
> > >>       b) No support for bounded stream to run in a streaming runtime
> > >> setting, i.e. scheduling and operators behaviors.
> > >>
> > >>
> > >> Option 2:
> > >> // The source is either bounded or unbounded, but only unbounded
> > operations
> > >> could be performed on the returned DataStream.
> > >> DataStream<Type> dataStream = env.source(someSource);
> > >>
> > >> // The source must be a bounded source, otherwise exception is thrown.
> > >> BoundedDataStream<Type> boundedDataStream =
> > >> env.boundedSource(boundedSource);
> > >>
> > >> The pros and cons are exactly the opposite of option 1.
> > >>  - Pros:
> > >>       a) For applications that do not involve bounded operations, they
> > >> still have to call different API to distinguish bounded / unbounded
> > streams.
> > >>       b) Support for bounded stream to run in a streaming runtime
> > setting,
> > >> i.e. scheduling and operators behaviors.
> > >>  - Cons:
> > >>       a) Bounded / unbounded streams are kind of mixed, i.e. given a
> > >> DataStream, it is not clear whether it is bounded or not, unless you
> > have
> > >> the access to its source.
> > >>
> > >>
> > >> If we only think from the Source API perspective, option 2 seems a
> > better
> > >> choice because functionality wise it is a superset of option 1, at the
> > cost
> > >> of some seemingly acceptable ambiguity in the DataStream API.
> > >> But if we look at the DataStream API as a whole, option 1 seems a
> > clearer
> > >> choice. For example, some times a library may have to know whether a
> > >> certain task will finish or not. And it would be difficult to tell if
> > the
> > >> input is a DataStream, unless additional information is provided all
> the
> > >> way from the Source. One possible solution is to have a *modified
> > option 2*
> > >> which adds a method to the DataStream API to indicate boundedness,
> such
> > as
> > >> getBoundedness(). It would solve the problem with a potential
> confusion
> > of
> > >> what is difference between a DataStream with getBoundedness()=true
> and a
> > >> BoundedDataStream. But that seems not super difficult to explain.
> > >>
> > >> So from API's perspective, I don't have a strong opinion between
> > *option 1*
> > >> and *modified option 2. *I like the cleanness of option 1, but
> modified
> > >> option 2 would be more attractive if we have concrete use case for the
> > >> "Bounded stream with unbounded streaming runtime settings".
> > >>
> > >> Re: Till
> > >>
> > >>
> > >> Maybe this has already been asked before but I was wondering why the
> > >> SourceReader interface has the method pollNext which hands the
> > >> responsibility of outputting elements to the SourceReader
> > implementation?
> > >> Has this been done for backwards compatibility reasons with the old
> > source
> > >> interface? If not, then one could define a Collection<E>
> > getNextRecords()
> > >> method which returns the currently retrieved records and then the
> caller
> > >> emits them outside of the SourceReader. That way the interface would
> not
> > >> allow to implement an outputting loop where we never hand back control
> > to
> > >> the caller. At the moment, this contract can be easily broken and is
> > only
> > >> mentioned loosely in the JavaDocs.
> > >>
> > >>
> > >> The primary reason we handover the SourceOutput to the SourceReader is
> > >> because sometimes it is difficult for a SourceReader to emit one
> record
> > at
> > >> a time. One example is some batched messaging systems which only have
> an
> > >> offset for the entire batch instead of individual messages in the
> > batch. In
> > >> that case, returning one record at a time would leave the SourceReader
> > in
> > >> an uncheckpointable state because they can only checkpoint at the
> batch
> > >> boundaries.
> > >>
> > >> Thanks,
> > >>
> > >> Jiangjie (Becket) Qin
> > >>
> > >> On Tue, Dec 10, 2019 at 5:33 PM Till Rohrmann <[hidden email]
> > <mailto:[hidden email]>> <[hidden email] <mailto:
> > [hidden email]>> wrote:
> > >>
> > >>
> > >> Hi everyone,
> > >>
> > >> thanks for drafting this FLIP. It reads very well.
> > >>
> > >> Concerning Dawid's proposal, I tend to agree. The boundedness could
> come
> > >> from the source and tell the system how to treat the operator
> > (scheduling
> > >> wise). From a user's perspective it should be fine to get back a
> > DataStream
> > >> when calling env.source(boundedSource) if he does not need special
> > >> operations defined on a BoundedDataStream. If he needs this, then one
> > could
> > >> use the method BoundedDataStream env.boundedSource(boundedSource).
> > >>
> > >> If possible, we could enforce the proper usage of env.boundedSource()
> by
> > >> introducing a BoundedSource type so that one cannot pass an
> > >> unbounded source to it. That way users would not be able to shoot
> > >> themselves in the foot.
> > >>
> > >> Maybe this has already been asked before but I was wondering why the
> > >> SourceReader interface has the method pollNext which hands the
> > >> responsibility of outputting elements to the SourceReader
> > implementation?
> > >> Has this been done for backwards compatibility reasons with the old
> > source
> > >> interface? If not, then one could define a Collection<E>
> > getNextRecords()
> > >> method which returns the currently retrieved records and then the
> caller
> > >> emits them outside of the SourceReader. That way the interface would
> not
> > >> allow to implement an outputting loop where we never hand back control
> > to
> > >> the caller. At the moment, this contract can be easily broken and is
> > only
> > >> mentioned loosely in the JavaDocs.
> > >>
> > >> Cheers,
> > >> Till
> > >>
> > >> On Tue, Dec 10, 2019 at 7:49 AM Jingsong Li <[hidden email]
> > <mailto:[hidden email]>> <[hidden email] <mailto:
> > [hidden email]>>
> > >> wrote:
> > >>
> > >>
> > >> Hi all,
> > >>
> > >> I think current design is good.
> > >>
> > >> My understanding is:
> > >>
> > >> For execution mode: bounded mode and continuous mode, It's totally
> > >> different. I don't think we have the ability to integrate the two
> models
> > >>
> > >> at
> > >>
> > >> present. It's about scheduling, memory, algorithms, States, etc. we
> > >> shouldn't confuse them.
> > >>
> > >> For source capabilities: only bounded, only continuous, both bounded
> and
> > >> continuous.
> > >> I think Kafka is a source that can be ran both bounded
> > >> and continuous execution mode.
> > >> And Kafka with end offset should be ran both bounded
> > >> and continuous execution mode.  Using apache Beam with Flink runner, I
> > >>
> > >> used
> > >>
> > >> to run a "bounded" Kafka in streaming mode. For our previous
> DataStream,
> > >>
> > >> it
> > >>
> > >> is not necessarily required that the source cannot be bounded.
> > >>
> > >> So it is my thought for Dawid's question:
> > >> 1.pass a bounded source to continuousSource() +1
> > >> 2.pass a continuous source to boundedSource() -1, should throw
> > exception.
> > >>
> > >> In StreamExecutionEnvironment, continuousSource and boundedSource
> define
> > >> the execution mode. It defines a clear boundary of execution mode.
> > >>
> > >> Best,
> > >> Jingsong Lee
> > >>
> > >> On Tue, Dec 10, 2019 at 10:37 AM Jark Wu <[hidden email] <mailto:
> > [hidden email]>> <[hidden email] <mailto:[hidden email]>> wrote:
> > >>
> > >>
> > >> I agree with Dawid's point that the boundedness information should
> come
> > >> from the source itself (e.g. the end timestamp), not through
> > >> env.boundedSouce()/continuousSource().
> > >> I think if we want to support something like `env.source()` that
> derive
> > >>
> > >> the
> > >>
> > >> execution mode from source, `supportsBoundedness(Boundedness)`
> > >> method is not enough, because we don't know whether it is bounded or
> > >>
> > >> not.
> > >>
> > >> Best,
> > >> Jark
> > >>
> > >>
> > >> On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <[hidden email]
> > <mailto:[hidden email]>> <[hidden email] <mailto:
> > [hidden email]>>
> > >> wrote:
> > >>
> > >>
> > >> One more thing. In the current proposal, with the
> > >> supportsBoundedness(Boundedness) method and the boundedness coming
> > >>
> > >> from
> > >>
> > >> either continuousSource or boundedSource I could not find how this
> > >> information is fed back to the SplitEnumerator.
> > >>
> > >> Best,
> > >>
> > >> Dawid
> > >>
> > >> On 09/12/2019 13:52, Becket Qin wrote:
> > >>
> > >> Hi Dawid,
> > >>
> > >> Thanks for the comments. This actually brings another relevant
> > >>
> > >> question
> > >>
> > >> about what does a "bounded source" imply. I actually had the same
> > >> impression when I look at the Source API. Here is what I understand
> > >>
> > >> after
> > >>
> > >> some discussion with Stephan. The bounded source has the following
> > >>
> > >> impacts.
> > >>
> > >> 1. API validity.
> > >> - A bounded source generates a bounded stream so some operations
> > >>
> > >> that
> > >>
> > >> only
> > >>
> > >> works for bounded records would be performed, e.g. sort.
> > >> - To expose these bounded stream only APIs, there are two options:
> > >>     a. Add them to the DataStream API and throw exception if a
> > >>
> > >> method
> > >>
> > >> is
> > >>
> > >> called on an unbounded stream.
> > >>     b. Create a BoundedDataStream class which is returned from
> > >> env.boundedSource(), while DataStream is returned from
> > >>
> > >> env.continousSource().
> > >>
> > >> Note that this cannot be done by having single
> > >>
> > >> env.source(theSource)
> > >>
> > >> even
> > >>
> > >> the Source has a getBoundedness() method.
> > >>
> > >> 2. Scheduling
> > >> - A bounded source could be computed stage by stage without
> > >>
> > >> bringing
> > >>
> > >> up
> > >>
> > >> all
> > >>
> > >> the tasks at the same time.
> > >>
> > >> 3. Operator behaviors
> > >> - A bounded source indicates the records are finite so some
> > >>
> > >> operators
> > >>
> > >> can
> > >>
> > >> wait until it receives all the records before it starts the
> > >>
> > >> processing.
> > >>
> > >> In the above impact, only 1 is relevant to the API design. And the
> > >>
> > >> current
> > >>
> > >> proposal in FLIP-27 is following 1.b.
> > >>
> > >> // boundedness depends of source property, imo this should always
> > >>
> > >> be
> > >>
> > >> preferred
> > >>
> > >>
> > >> DataStream<MyType> stream = env.source(theSource);
> > >>
> > >>
> > >> In your proposal, does DataStream have bounded stream only methods?
> > >>
> > >> It
> > >>
> > >> looks it should have, otherwise passing a bounded Source to
> > >>
> > >> env.source()
> > >>
> > >> would be confusing. In that case, we will essentially do 1.a if an
> > >> unbounded Source is created from env.source(unboundedSource).
> > >>
> > >> If we have the methods only supported for bounded streams in
> > >>
> > >> DataStream,
> > >>
> > >> it
> > >>
> > >> seems a little weird to have a separate BoundedDataStream
> > >>
> > >> interface.
> > >>
> > >> Am I understand it correctly?
> > >>
> > >> Thanks,
> > >>
> > >> Jiangjie (Becket) Qin
> > >>
> > >>
> > >>
> > >> On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <
> > >>
> > >> [hidden email] <mailto:[hidden email]>>
> > >>
> > >> wrote:
> > >>
> > >>
> > >> Hi all,
> > >>
> > >> Really well written proposal and very important one. I must admit
> > >>
> > >> I
> > >>
> > >> have
> > >>
> > >> not understood all the intricacies of it yet.
> > >>
> > >> One question I have though is about where does the information
> > >>
> > >> about
> > >>
> > >> boundedness come from. I think in most cases it is a property of
> > >>
> > >> the
> > >>
> > >> source. As you described it might be e.g. end offset, a flag
> > >>
> > >> should
> > >>
> > >> it
> > >>
> > >> monitor new splits etc. I think it would be a really nice use case
> > >>
> > >> to
> > >>
> > >> be
> > >>
> > >> able to say:
> > >>
> > >> new KafkaSource().readUntil(long timestamp),
> > >>
> > >> which could work as an "end offset". Moreover I think all Bounded
> > >>
> > >> sources
> > >>
> > >> support continuous mode, but no intrinsically continuous source
> > >>
> > >> support
> > >>
> > >> the
> > >>
> > >> Bounded mode. If I understood the proposal correctly it suggest
> > >>
> > >> the
> > >>
> > >> boundedness sort of "comes" from the outside of the source, from
> > >>
> > >> the
> > >>
> > >> invokation of either boundedStream or continousSource.
> > >>
> > >> I am wondering if it would make sense to actually change the
> > >>
> > >> method
> > >>
> > >> boolean Source#supportsBoundedness(Boundedness)
> > >>
> > >> to
> > >>
> > >> Boundedness Source#getBoundedness().
> > >>
> > >> As for the methods #boundedSource, #continousSource, assuming the
> > >> boundedness is property of the source they do not affect how the
> > >>
> > >> enumerator
> > >>
> > >> works, but mostly how the dag is scheduled, right? I am not
> > >>
> > >> against
> > >>
> > >> those
> > >>
> > >> methods, but I think it is a very specific use case to actually
> > >>
> > >> override
> > >>
> > >> the property of the source. In general I would expect users to
> > >>
> > >> only
> > >>
> > >> call
> > >>
> > >> env.source(theSource), where the source tells if it is bounded or
> > >>
> > >> not. I
> > >>
> > >> would suggest considering following set of methods:
> > >>
> > >> // boundedness depends of source property, imo this should always
> > >>
> > >> be
> > >>
> > >> preferred
> > >>
> > >> DataStream<MyType> stream = env.source(theSource);
> > >>
> > >>
> > >> // always continous execution, whether bounded or unbounded source
> > >>
> > >> DataStream<MyType> boundedStream = env.continousSource(theSource);
> > >>
> > >> // imo this would make sense if the BoundedDataStream provides
> > >>
> > >> additional features unavailable for continous mode
> > >>
> > >> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
> > >>
> > >>
> > >> Best,
> > >>
> > >> Dawid
> > >>
> > >>
> > >> On 04/12/2019 11:25, Stephan Ewen wrote:
> > >>
> > >> Thanks, Becket, for updating this.
> > >>
> > >> I agree with moving the aspects you mentioned into separate FLIPs
> > >>
> > >> -
> > >>
> > >> this
> > >>
> > >> one way becoming unwieldy in size.
> > >>
> > >> +1 to the FLIP in its current state. Its a very detailed write-up,
> > >>
> > >> nicely
> > >>
> > >> done!
> > >>
> > >> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]
> > <mailto:[hidden email]>> <[hidden email] <mailto:
> > [hidden email]>>
> > >>
> > >> <
> > >>
> > >> [hidden email] <mailto:[hidden email]>> wrote:
> > >>
> > >> Hi all,
> > >>
> > >> Sorry for the long belated update. I have updated FLIP-27 wiki
> > >>
> > >> page
> > >>
> > >> with
> > >>
> > >> the latest proposals. Some noticeable changes include:
> > >> 1. A new generic communication mechanism between SplitEnumerator
> > >>
> > >> and
> > >>
> > >> SourceReader.
> > >> 2. Some detail API method signature changes.
> > >>
> > >> We left a few things out of this FLIP and will address them in
> > >>
> > >> separate
> > >>
> > >> FLIPs. Including:
> > >> 1. Per split event time.
> > >> 2. Event time alignment.
> > >> 3. Fine grained failover for SplitEnumerator failure.
> > >>
> > >> Please let us know if you have any question.
> > >>
> > >> Thanks,
> > >>
> > >> Jiangjie (Becket) Qin
> > >>
> > >> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]
> <mailto:
> > [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> > >>
> > >> [hidden email] <mailto:[hidden email]>> wrote:
> > >>
> > >> Hi  Łukasz!
> > >>
> > >> Becket and me are working hard on figuring out the last details
> > >>
> > >> and
> > >>
> > >> implementing the first PoC. We would update the FLIP hopefully
> > >>
> > >> next
> > >>
> > >> week.
> > >>
> > >> There is a fair chance that a first version of this will be in
> > >>
> > >> 1.10,
> > >>
> > >> but
> > >>
> > >> I
> > >>
> > >> think it will take another release to battle test it and migrate
> > >>
> > >> the
> > >>
> > >> connectors.
> > >>
> > >> Best,
> > >> Stephan
> > >>
> > >>
> > >>
> > >>
> > >> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <[hidden email]
> > <mailto:[hidden email]>
> > >>
> > >> <
> > >>
> > >> [hidden email] <mailto:[hidden email]>>
> > >>
> > >> wrote:
> > >>
> > >> Hi,
> > >>
> > >> This proposal looks very promising for us. Do you have any plans
> > >>
> > >> in
> > >>
> > >> which
> > >>
> > >> Flink release it is going to be released? We are thinking on
> > >>
> > >> using a
> > >>
> > >> Data
> > >>
> > >> Set API for our future use cases but on the other hand Data Set
> > >>
> > >> API
> > >>
> > >> is
> > >>
> > >> going to be deprecated so using proposed bounded data streams
> > >>
> > >> solution
> > >>
> > >> could be more viable in the long term.
> > >>
> > >> Thanks,
> > >> Łukasz
> > >>
> > >> On 2019/10/01 15:48:03, Thomas Weise <[hidden email] <mailto:
> > [hidden email]>> <[hidden email] <mailto:
> > [hidden email]>> <
> > >>
> > >> [hidden email] <mailto:[hidden email]>> wrote:
> > >>
> > >> Thanks for putting together this proposal!
> > >>
> > >> I see that the "Per Split Event Time" and "Event Time Alignment"
> > >>
> > >> sections
> > >>
> > >> are still TBD.
> > >>
> > >> It would probably be good to flesh those out a bit before
> > >>
> > >> proceeding
> > >>
> > >> too
> > >>
> > >> far
> > >>
> > >> as the event time alignment will probably influence the
> > >>
> > >> interaction
> > >>
> > >> with
> > >>
> > >> the split reader, specifically ReaderStatus
> > >>
> > >> emitNext(SourceOutput<E>
> > >>
> > >> output).
> > >>
> > >> We currently have only one implementation for event time alignment
> > >>
> > >> in
> > >>
> > >> the
> > >>
> > >> Kinesis consumer. The synchronization in that case takes place as
> > >>
> > >> the
> > >>
> > >> last
> > >>
> > >> step before records are emitted downstream (RecordEmitter). With
> > >>
> > >> the
> > >>
> > >> currently proposed interfaces, the equivalent can be implemented
> > >>
> > >> in
> > >>
> > >> the
> > >>
> > >> reader loop, although note that in the Kinesis consumer the per
> > >>
> > >> shard
> > >>
> > >> threads push records.
> > >>
> > >> Synchronization has not been implemented for the Kafka consumer
> > >>
> > >> yet.
> > >>
> > >> https://issues.apache.org/jira/browse/FLINK-12675 <
> > https://issues.apache.org/jira/browse/FLINK-12675>
> > >>
> > >> When I looked at it, I realized that the implementation will look
> > >>
> > >> quite
> > >>
> > >> different
> > >> from Kinesis because it needs to take place in the pull part,
> > >>
> > >> where
> > >>
> > >> records
> > >>
> > >> are taken from the Kafka client. Due to the multiplexing it cannot
> > >>
> > >> be
> > >>
> > >> done
> > >>
> > >> by blocking the split thread like it currently works for Kinesis.
> > >>
> > >> Reading
> > >>
> > >> from individual Kafka partitions needs to be controlled via
> > >>
> > >> pause/resume
> > >>
> > >> on the Kafka client.
> > >>
> > >> To take on that responsibility the split thread would need to be
> > >>
> > >> aware
> > >>
> > >> of
> > >>
> > >> the
> > >> watermarks or at least whether it should or should not continue to
> > >>
> > >> consume
> > >>
> > >> a given split and this may require a different SourceReader or
> > >>
> > >> SourceOutput
> > >>
> > >> interface.
> > >>
> > >> Thanks,
> > >> Thomas
> > >>
> > >>
> > >> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email] <mailto:
> > [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> > >>
> > >> [hidden email] <mailto:[hidden email]>> wrote:
> > >>
> > >> Hi Stephan,
> > >>
> > >> Thank you for feedback!
> > >> Will take a look at your branch before public discussing.
> > >>
> > >>
> > >> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]
> > <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]>>
> > >>
> > >> <
> > >>
> > >> [hidden email] <mailto:[hidden email]>>
> > >>
> > >> wrote:
> > >>
> > >> Hi Biao!
> > >>
> > >> Thanks for reviving this. I would like to join this discussion,
> > >>
> > >> but
> > >>
> > >> am
> > >>
> > >> quite occupied with the 1.9 release, so can we maybe pause this
> > >>
> > >> discussion
> > >>
> > >> for a week or so?
> > >>
> > >> In the meantime I can share some suggestion based on prior
> > >>
> > >> experiments:
> > >>
> > >> How to do watermarks / timestamp extractors in a simpler and more
> > >>
> > >> flexible
> > >>
> > >> way. I think that part is quite promising should be part of the
> > >>
> > >> new
> > >>
> > >> source
> > >>
> > >> interface.
> > >>
> > >>
> > >>
> > >>
> > >>
> > >>
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> > <
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> > >
> > >>
> > >>
> >
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> > <
> >
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> > >
> > >>
> > >> Some experiments on how to build the source reader and its
> > >>
> > >> library
> > >>
> > >> for
> > >>
> > >> common threading/split patterns:
> > >>
> > >>
> > >>
> > >>
> > >>
> > >>
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> > <
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> > >
> > >>
> > >> Best,
> > >> Stephan
> > >>
> > >>
> > >> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]
> <mailto:
> > [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> > >>
> > >> [hidden email] <mailto:[hidden email]>>
> > >>
> > >> wrote:
> > >>
> > >> Hi devs,
> > >>
> > >> Since 1.9 is nearly released, I think we could get back to
> > >>
> > >> FLIP-27.
> > >>
> > >> I
> > >>
> > >> believe it should be included in 1.10.
> > >>
> > >> There are so many things mentioned in document of FLIP-27. [1] I
> > >>
> > >> think
> > >>
> > >> we'd better discuss them separately. However the wiki is not a
> > >>
> > >> good
> > >>
> > >> place
> > >>
> > >> to discuss. I wrote google doc about SplitReader API which
> > >>
> > >> misses
> > >>
> > >> some
> > >>
> > >> details in the document. [2]
> > >>
> > >> 1.
> > >>
> > >>
> > >>
> > >>
> > >>
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> > <
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> > >
> > >>
> > >> 2.
> > >>
> > >>
> > >>
> > >>
> > >>
> >
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> > <
> >
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> > >
> > >>
> > >> CC Stephan, Aljoscha, Piotrek, Becket
> > >>
> > >>
> > >> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email] <mailto:
> > [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> > >>
> > >> [hidden email] <mailto:[hidden email]>>
> > >>
> > >> wrote:
> > >>
> > >> Hi Steven,
> > >> Thank you for the feedback. Please take a look at the document
> > >>
> > >> FLIP-27
> > >>
> > >> <
> > >>
> > >>
> > >>
> > >>
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> > <
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> > >
> > >>
> > >> which
> > >>
> > >> is updated recently. A lot of details of enumerator were added
> > >>
> > >> in
> > >>
> > >> this
> > >>
> > >> document. I think it would help.
> > >>
> > >> Steven Wu <[hidden email] <mailto:[hidden email]>> <
> > [hidden email] <mailto:[hidden email]>> <
> [hidden email]
> > <mailto:[hidden email]>> <[hidden email] <mailto:
> > [hidden email]>>
> > >>
> > >> 于2019年3月28日周四
> > >>
> > >> 下午12:52写道：
> > >>
> > >> This proposal mentioned that SplitEnumerator might run on the
> > >> JobManager or
> > >> in a single task on a TaskManager.
> > >>
> > >> if enumerator is a single task on a taskmanager, then the job
> > >>
> > >> DAG
> > >>
> > >> can
> > >>
> > >> never
> > >> been embarrassingly parallel anymore. That will nullify the
> > >>
> > >> leverage
> > >>
> > >> of
> > >>
> > >> fine-grained recovery for embarrassingly parallel jobs.
> > >>
> > >> It's not clear to me what's the implication of running
> > >>
> > >> enumerator
> > >>
> > >> on
> > >>
> > >> the
> > >>
> > >> jobmanager. So I will leave that out for now.
> > >>
> > >> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email] <mailto:
> > [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> > >>
> > >> [hidden email] <mailto:[hidden email]>>
> > >>
> > >> wrote:
> > >>
> > >> Hi Stephan & Piotrek,
> > >>
> > >> Thank you for feedback.
> > >>
> > >> It seems that there are a lot of things to do in community.
> > >>
> > >> I
> > >>
> > >> am
> > >>
> > >> just
> > >>
> > >> afraid that this discussion may be forgotten since there so
> > >>
> > >> many
> > >>
> > >> proposals
> > >>
> > >> recently.
> > >> Anyway, wish to see the split topics soon :)
> > >>
> > >> Piotr Nowojski <[hidden email] <mailto:[hidden email]>>
> <
> > [hidden email] <mailto:[hidden email]>> <
> > [hidden email] <mailto:[hidden email]>> <
> > [hidden email] <mailto:[hidden email]>>
> > >>
> > >> 于2019年1月24日周四
> > >>
> > >> 下午8:21写道：
> > >>
> > >> Hi Biao!
> > >>
> > >> This discussion was stalled because of preparations for
> > >>
> > >> the
> > >>
> > >> open
> > >>
> > >> sourcing
> > >>
> > >> & merging Blink. I think before creating the tickets we
> > >>
> > >> should
> > >>
> > >> split this
> > >>
> > >> discussion into topics/areas outlined by Stephan and
> > >>
> > >> create
> > >>
> > >> Flips
> > >>
> > >> for
> > >>
> > >> that.
> > >>
> > >> I think there is no chance for this to be completed in
> > >>
> > >> couple
> > >>
> > >> of
> > >>
> > >> remaining
> > >>
> > >> weeks/1 month before 1.8 feature freeze, however it would
> > >>
> > >> be
> > >>
> > >> good
> > >>
> > >> to aim
> > >>
> > >> with those changes for 1.9.
> > >>
> > >> Piotrek
> > >>
> > >>
> > >> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email] <mailto:
> > [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> > >>
> > >> [hidden email] <mailto:[hidden email]>>
> > >>
> > >> wrote:
> > >>
> > >> Hi community,
> > >> The summary of Stephan makes a lot sense to me. It is
> > >>
> > >> much
> > >>
> > >> clearer
> > >>
> > >> indeed
> > >>
> > >> after splitting the complex topic into small ones.
> > >> I was wondering is there any detail plan for next step?
> > >>
> > >> If
> > >>
> > >> not,
> > >>
> > >> I
> > >>
> > >> would
> > >>
> > >> like to push this thing forward by creating some JIRA
> > >>
> > >> issues.
> > >>
> > >> Another question is that should version 1.8 include
> > >>
> > >> these
> > >>
> > >> features?
> > >>
> > >> Stephan Ewen <[hidden email] <mailto:[hidden email]>> <
> > [hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:
> > [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> > 于2018年12月1日周六
> > >>
> > >> 上午4:20写道：
> > >>
> > >> Thanks everyone for the lively discussion. Let me try
> > >>
> > >> to
> > >>
> > >> summarize
> > >>
> > >> where I
> > >>
> > >> see convergence in the discussion and open issues.
> > >> I'll try to group this by design aspect of the source.
> > >>
> > >> Please
> > >>
> > >> let me
> > >>
> > >> know
> > >>
> > >> if I got things wrong or missed something crucial here.
> > >>
> > >> For issues 1-3, if the below reflects the state of the
> > >>
> > >> discussion, I
> > >>
> > >> would
> > >>
> > >> try and update the FLIP in the next days.
> > >> For the remaining ones we need more discussion.
> > >>
> > >> I would suggest to fork each of these aspects into a
> > >>
> > >> separate
> > >>
> > >> mail
> > >>
> > >> thread,
> > >>
> > >> or will loose sight of the individual aspects.
> > >>
> > >> *(1) Separation of Split Enumerator and Split Reader*
> > >>
> > >> - All seem to agree this is a good thing
> > >> - Split Enumerator could in the end live on JobManager
> > >>
> > >> (and
> > >>
> > >> assign
> > >>
> > >> splits
> > >>
> > >> via RPC) or in a task (and assign splits via data
> > >>
> > >> streams)
> > >>
> > >> - this discussion is orthogonal and should come later,
> > >>
> > >> when
> > >>
> > >> the
> > >>
> > >> interface
> > >>
> > >> is agreed upon.
> > >>
> > >> *(2) Split Readers for one or more splits*
> > >>
> > >> - Discussion seems to agree that we need to support
> > >>
> > >> one
> > >>
> > >> reader
> > >>
> > >> that
> > >>
> > >> possibly handles multiple splits concurrently.
> > >> - The requirement comes from sources where one
> > >>
> > >> poll()-style
> > >>
> > >> call
> > >>
> > >> fetches
> > >>
> > >> data from different splits / partitions
> > >>   --> example sources that require that would be for
> > >>
> > >> example
> > >>
> > >> Kafka,
> > >>
> > >> Pravega, Pulsar
> > >>
> > >> - Could have one split reader per source, or multiple
> > >>
> > >> split
> > >>
> > >> readers
> > >>
> > >> that
> > >>
> > >> share the "poll()" function
> > >> - To not make it too complicated, we can start with
> > >>
> > >> thinking
> > >>
> > >> about
> > >>
> > >> one
> > >>
> > >> split reader for all splits initially and see if that
> > >>
> > >> covers
> > >>
> > >> all
> > >>
> > >> requirements
> > >>
> > >> *(3) Threading model of the Split Reader*
> > >>
> > >> - Most active part of the discussion ;-)
> > >>
> > >> - A non-blocking way for Flink's task code to interact
> > >>
> > >> with
> > >>
> > >> the
> > >>
> > >> source
> > >>
> > >> is
> > >>
> > >> needed in order to a task runtime code based on a
> > >> single-threaded/actor-style task design
> > >>   --> I personally am a big proponent of that, it will
> > >>
> > >> help
> > >>
> > >> with
> > >>
> > >> well-behaved checkpoints, efficiency, and simpler yet
> > >>
> > >> more
> > >>
> > >> robust
> > >>
> > >> runtime
> > >>
> > >> code
> > >>
> > >> - Users care about simple abstraction, so as a
> > >>
> > >> subclass
> > >>
> > >> of
> > >>
> > >> SplitReader
> > >>
> > >> (non-blocking / async) we need to have a
> > >>
> > >> BlockingSplitReader
> > >>
> > >> which
> > >>
> > >> will
> > >>
> > >> form the basis of most source implementations.
> > >>
> > >> BlockingSplitReader
> > >>
> > >> lets
> > >>
> > >> users do blocking simple poll() calls.
> > >> - The BlockingSplitReader would spawn a thread (or
> > >>
> > >> more)
> > >>
> > >> and
> > >>
> > >> the
> > >>
> > >> thread(s) can make blocking calls and hand over data
> > >>
> > >> buffers
> > >>
> > >> via
> > >>
> > >> a
> > >>
> > >> blocking
> > >>
> > >> queue
> > >> - This should allow us to cover both, a fully async
> > >>
> > >> runtime,
> > >>
> > >> and a
> > >>
> > >> simple
> > >>
> > >> blocking interface for users.
> > >> - This is actually very similar to how the Kafka
> > >>
> > >> connectors
> > >>
> > >> work.
> > >>
> > >> Kafka
> > >>
> > >> 9+ with one thread, Kafka 8 with multiple threads
> > >>
> > >> - On the base SplitReader (the async one), the
> > >>
> > >> non-blocking
> > >>
> > >> method
> > >>
> > >> that
> > >>
> > >> gets the next chunk of data would signal data
> > >>
> > >> availability
> > >>
> > >> via
> > >>
> > >> a
> > >>
> > >> CompletableFuture, because that gives the best
> > >>
> > >> flexibility
> > >>
> > >> (can
> > >>
> > >> await
> > >>
> > >> completion or register notification handlers).
> > >> - The source task would register a "thenHandle()" (or
> > >>
> > >> similar)
> > >>
> > >> on the
> > >>
> > >> future to put a "take next data" task into the
> > >>
> > >> actor-style
> > >>
> > >> mailbox
> > >>
> > >> *(4) Split Enumeration and Assignment*
> > >>
> > >> - Splits may be generated lazily, both in cases where
> > >>
> > >> there
> > >>
> > >> is a
> > >>
> > >> limited
> > >>
> > >> number of splits (but very many), or splits are
> > >>
> > >> discovered
> > >>
> > >> over
> > >>
> > >> time
> > >>
> > >> - Assignment should also be lazy, to get better load
> > >>
> > >> balancing
> > >>
> > >> - Assignment needs support locality preferences
> > >>
> > >> - Possible design based on discussion so far:
> > >>
> > >>   --> SplitReader has a method "addSplits(SplitT...)"
> > >>
> > >> to
> > >>
> > >> add
> > >>
> > >> one or
> > >>
> > >> more
> > >>
> > >> splits. Some split readers might assume they have only
> > >>
> > >> one
> > >>
> > >> split
> > >>
> > >> ever,
> > >>
> > >> concurrently, others assume multiple splits. (Note:
> > >>
> > >> idea
> > >>
> > >> behind
> > >>
> > >> being
> > >>
> > >> able
> > >>
> > >> to add multiple splits at the same time is to ease
> > >>
> > >> startup
> > >>
> > >> where
> > >>
> > >> multiple
> > >>
> > >> splits may be assigned instantly.)
> > >>   --> SplitReader has a context object on which it can
> > >>
> > >> call
> > >>
> > >> indicate
> > >>
> > >> when
> > >>
> > >> splits are completed. The enumerator gets that
> > >>
> > >> notification and
> > >>
> > >> can
> > >>
> > >> use
> > >>
> > >> to
> > >>
> > >> decide when to assign new splits. This should help both
> > >>
> > >> in
> > >>
> > >> cases
> > >>
> > >> of
> > >>
> > >> sources
> > >>
> > >> that take splits lazily (file readers) and in case the
> > >>
> > >> source
> > >>
> > >> needs to
> > >>
> > >> preserve a partial order between splits (Kinesis,
> > >>
> > >> Pravega,
> > >>
> > >> Pulsar may
> > >>
> > >> need
> > >>
> > >> that).
> > >>   --> SplitEnumerator gets notification when
> > >>
> > >> SplitReaders
> > >>
> > >> start
> > >>
> > >> and
> > >>
> > >> when
> > >>
> > >> they finish splits. They can decide at that moment to
> > >>
> > >> push
> > >>
> > >> more
> > >>
> > >> splits
> > >>
> > >> to
> > >>
> > >> that reader
> > >>   --> The SplitEnumerator should probably be aware of
> > >>
> > >> the
> > >>
> > >> source
> > >>
> > >> parallelism, to build its initial distribution.
> > >>
> > >> - Open question: Should the source expose something
> > >>
> > >> like
> > >>
> > >> "host
> > >>
> > >> preferences", so that yarn/mesos/k8s can take this into
> > >>
> > >> account
> > >>
> > >> when
> > >>
> > >> selecting a node to start a TM on?
> > >>
> > >> *(5) Watermarks and event time alignment*
> > >>
> > >> - Watermark generation, as well as idleness, needs to
> > >>
> > >> be
> > >>
> > >> per
> > >>
> > >> split
> > >>
> > >> (like
> > >>
> > >> currently in the Kafka Source, per partition)
> > >> - It is desirable to support optional
> > >>
> > >> event-time-alignment,
> > >>
> > >> meaning
> > >>
> > >> that
> > >>
> > >> splits that are ahead are back-pressured or temporarily
> > >>
> > >> unsubscribed
> > >>
> > >> - I think i would be desirable to encapsulate
> > >>
> > >> watermark
> > >>
> > >> generation
> > >>
> > >> logic
> > >>
> > >> in watermark generators, for a separation of concerns.
> > >>
> > >> The
> > >>
> > >> watermark
> > >>
> > >> generators should run per split.
> > >> - Using watermark generators would also help with
> > >>
> > >> another
> > >>
> > >> problem of
> > >>
> > >> the
> > >>
> > >> suggested interface, namely supporting non-periodic
> > >>
> > >> watermarks
> > >>
> > >> efficiently.
> > >>
> > >> - Need a way to "dispatch" next record to different
> > >>
> > >> watermark
> > >>
> > >> generators
> > >>
> > >> - Need a way to tell SplitReader to "suspend" a split
> > >>
> > >> until a
> > >>
> > >> certain
> > >>
> > >> watermark is reached (event time backpressure)
> > >> - This would in fact be not needed (and thus simpler)
> > >>
> > >> if
> > >>
> > >> we
> > >>
> > >> had
> > >>
> > >> a
> > >>
> > >> SplitReader per split and may be a reason to re-open
> > >>
> > >> that
> > >>
> > >> discussion
> > >>
> > >> *(6) Watermarks across splits and in the Split
> > >>
> > >> Enumerator*
> > >>
> > >> - The split enumerator may need some watermark
> > >>
> > >> awareness,
> > >>
> > >> which
> > >>
> > >> should
> > >>
> > >> be
> > >>
> > >> purely based on split metadata (like create timestamp
> > >>
> > >> of
> > >>
> > >> file
> > >>
> > >> splits)
> > >>
> > >> - If there are still more splits with overlapping
> > >>
> > >> event
> > >>
> > >> time
> > >>
> > >> range
> > >>
> > >> for
> > >>
> > >> a
> > >>
> > >> split reader, then that split reader should not advance
> > >>
> > >> the
> > >>
> > >> watermark
> > >>
> > >> within the split beyond the overlap boundary. Otherwise
> > >>
> > >> future
> > >>
> > >> splits
> > >>
> > >> will
> > >>
> > >> produce late data.
> > >>
> > >> - One way to approach this could be that the split
> > >>
> > >> enumerator
> > >>
> > >> may
> > >>
> > >> send
> > >>
> > >> watermarks to the readers, and the readers cannot emit
> > >>
> > >> watermarks
> > >>
> > >> beyond
> > >>
> > >> that received watermark.
> > >> - Many split enumerators would simply immediately send
> > >>
> > >> Long.MAX
> > >>
> > >> out
> > >>
> > >> and
> > >>
> > >> leave the progress purely to the split readers.
> > >>
> > >> - For event-time alignment / split back pressure, this
> > >>
> > >> begs
> > >>
> > >> the
> > >>
> > >> question
> > >>
> > >> how we can avoid deadlocks that may arise when splits
> > >>
> > >> are
> > >>
> > >> suspended
> > >>
> > >> for
> > >>
> > >> event time back pressure,
> > >>
> > >> *(7) Batch and streaming Unification*
> > >>
> > >> - Functionality wise, the above design should support
> > >>
> > >> both
> > >>
> > >> - Batch often (mostly) does not care about reading "in
> > >>
> > >> order"
> > >>
> > >> and
> > >>
> > >> generating watermarks
> > >>   --> Might use different enumerator logic that is
> > >>
> > >> more
> > >>
> > >> locality
> > >>
> > >> aware
> > >>
> > >> and ignores event time order
> > >>   --> Does not generate watermarks
> > >> - Would be great if bounded sources could be
> > >>
> > >> identified
> > >>
> > >> at
> > >>
> > >> compile
> > >>
> > >> time,
> > >>
> > >> so that "env.addBoundedSource(...)" is type safe and
> > >>
> > >> can
> > >>
> > >> return a
> > >>
> > >> "BoundedDataStream".
> > >> - Possible to defer this discussion until later
> > >>
> > >> *Miscellaneous Comments*
> > >>
> > >> - Should the source have a TypeInformation for the
> > >>
> > >> produced
> > >>
> > >> type,
> > >>
> > >> instead
> > >>
> > >> of a serializer? We need a type information in the
> > >>
> > >> stream
> > >>
> > >> anyways, and
> > >>
> > >> can
> > >>
> > >> derive the serializer from that. Plus, creating the
> > >>
> > >> serializer
> > >>
> > >> should
> > >>
> > >> respect the ExecutionConfig.
> > >>
> > >> - The TypeSerializer interface is very powerful but
> > >>
> > >> also
> > >>
> > >> not
> > >>
> > >> easy to
> > >>
> > >> implement. Its purpose is to handle data super
> > >>
> > >> efficiently,
> > >>
> > >> support
> > >>
> > >> flexible ways of evolution, etc.
> > >> For metadata I would suggest to look at the
> > >>
> > >> SimpleVersionedSerializer
> > >>
> > >> instead, which is used for example for checkpoint
> > >>
> > >> master
> > >>
> > >> hooks,
> > >>
> > >> or for
> > >>
> > >> the
> > >>
> > >> streaming file sink. I think that is is a good match
> > >>
> > >> for
> > >>
> > >> cases
> > >>
> > >> where
> > >>
> > >> we
> > >>
> > >> do
> > >>
> > >> not need more than ser/deser (no copy, etc.) and don't
> > >>
> > >> need to
> > >>
> > >> push
> > >>
> > >> versioning out of the serialization paths for best
> > >>
> > >> performance
> > >>
> > >> (as in
> > >>
> > >> the
> > >>
> > >> TypeSerializer)
> > >>
> > >>
> > >> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
> > >>
> > >> [hidden email]>
> > >>
> > >> wrote:
> > >>
> > >>
> > >> Hi Biao,
> > >>
> > >> Thanks for the answer!
> > >>
> > >> So given the multi-threaded readers, now we have as
> > >>
> > >> open
> > >>
> > >> questions:
> > >>
> > >> 1) How do we let the checkpoints pass through our
> > >>
> > >> multi-threaded
> > >>
> > >> reader
> > >>
> > >> operator?
> > >>
> > >> 2) Do we have separate reader and source operators or
> > >>
> > >> not? In
> > >>
> > >> the
> > >>
> > >> strategy
> > >>
> > >> that has a separate source, the source operator has a
> > >>
> > >> parallelism of
> > >>
> > >> 1
> > >>
> > >> and
> > >>
> > >> is responsible for split recovery only.
> > >>
> > >> For the first one, given also the constraints
> > >>
> > >> (blocking,
> > >>
> > >> finite
> > >>
> > >> queues,
> > >>
> > >> etc), I do not have an answer yet.
> > >>
> > >> For the 2nd, I think that we should go with separate
> > >>
> > >> operators
> > >>
> > >> for
> > >>
> > >> the
> > >>
> > >> source and the readers, for the following reasons:
> > >>
> > >> 1) This is more aligned with a potential future
> > >>
> > >> improvement
> > >>
> > >> where the
> > >>
> > >> split
> > >>
> > >> discovery becomes a responsibility of the JobManager
> > >>
> > >> and
> > >>
> > >> readers are
> > >>
> > >> pooling more work from the JM.
> > >>
> > >> 2) The source is going to be the "single point of
> > >>
> > >> truth".
> > >>
> > >> It
> > >>
> > >> will
> > >>
> > >> know
> > >>
> > >> what
> > >>
> > >> has been processed and what not. If the source and the
> > >>
> > >> readers
> > >>
> > >> are a
> > >>
> > >> single
> > >>
> > >> operator with parallelism > 1, or in general, if the
> > >>
> > >> split
> > >>
> > >> discovery
> > >>
> > >> is
> > >>
> > >> done by each task individually, then:
> > >>  i) we have to have a deterministic scheme for each
> > >>
> > >> reader to
> > >>
> > >> assign
> > >>
> > >> splits to itself (e.g. mod subtaskId). This is not
> > >>
> > >> necessarily
> > >>
> > >> trivial
> > >>
> > >> for
> > >>
> > >> all sources.
> > >>  ii) each reader would have to keep a copy of all its
> > >>
> > >> processed
> > >>
> > >> slpits
> > >>
> > >>  iii) the state has to be a union state with a
> > >>
> > >> non-trivial
> > >>
> > >> merging
> > >>
> > >> logic
> > >>
> > >> in order to support rescaling.
> > >>
> > >> Two additional points that you raised above:
> > >>
> > >> i) The point that you raised that we need to keep all
> > >>
> > >> splits
> > >>
> > >> (processed
> > >>
> > >> and
> > >>
> > >> not-processed) I think is a bit of a strong
> > >>
> > >> requirement.
> > >>
> > >> This
> > >>
> > >> would
> > >>
> > >> imply
> > >>
> > >> that for infinite sources the state will grow
> > >>
> > >> indefinitely.
> > >>
> > >> This is
> > >>
> > >> problem
> > >>
> > >> is even more pronounced if we do not have a single
> > >>
> > >> source
> > >>
> > >> that
> > >>
> > >> assigns
> > >>
> > >> splits to readers, as each reader will have its own
> > >>
> > >> copy
> > >>
> > >> of
> > >>
> > >> the
> > >>
> > >> state.
> > >>
> > >> ii) it is true that for finite sources we need to
> > >>
> > >> somehow
> > >>
> > >> not
> > >>
> > >> close
> > >>
> > >> the
> > >>
> > >> readers when the source/split discoverer finishes. The
> > >> ContinuousFileReaderOperator has a work-around for
> > >>
> > >> that.
> > >>
> > >> It is
> > >>
> > >> not
> > >>
> > >> elegant,
> > >>
> > >> and checkpoints are not emitted after closing the
> > >>
> > >> source,
> > >>
> > >> but
> > >>
> > >> this, I
> > >>
> > >> believe, is a bigger problem which requires more
> > >>
> > >> changes
> > >>
> > >> than
> > >>
> > >> just
> > >>
> > >> refactoring the source interface.
> > >>
> > >> Cheers,
> > >> Kostas
> > >>
> > >>
> > >>
> > >>
> > >> --
> > >> Best, Jingsong Lee
> >
> >
>

--
Best, Jingsong Lee

[Becket Qin]

Hi Dawid and Jark,

I think the discussion ultimately boils down to the question that which one
of the following two final states do we want? Once we make this decision,
everything else can be naturally derived.

*Final state 1*: Separate API for bounded / unbounded DataStream & Table.
That means any code users write will be valid at the point when they write
the code. This is similar to having type safety check at programming time.
For example,

BoundedDataStream extends DataStream {
// Operations only available for bounded data.
BoundedDataStream sort(...);

// Interaction with another BoundedStream returns a Bounded stream.
BoundedJoinedDataStream join(BoundedDataStream other)

// Interaction with another unbounded stream returns an unbounded stream.
JoinedDataStream join(DataStream other)
}

BoundedTable extends Table {
  // Bounded only operation.
BoundedTable sort(...);

// Interaction with another BoundedTable returns a BoundedTable.
BoundedTable join(BoundedTable other)

// Interaction with another unbounded table returns an unbounded table.
Table join(Table other)
}

*Final state 2*: One unified API for bounded / unbounded DataStream /
Table.
That unified API may throw exception at DAG compilation time if an invalid
operation is tried. This is what Table API currently follows.

DataStream {
// Throws exception if the DataStream is unbounded.
DataStream sort();
// Get boundedness.
Boundedness getBoundedness();
}

Table {
// Throws exception if the table has infinite rows.
Table orderBy();

// Get boundedness.
Boundedness getBoundedness();
}

From what I understand, there is no consensus so far on this decision yet.
Whichever final state we choose, we need to make it consistent across the
entire project. We should avoid the case that Table follows one final state
while DataStream follows another. Some arguments I am aware of from both
sides so far are following:

Arguments for final state 1:
1a) Clean API with method safety check at programming time.
1b) (Counter 2b) Although SQL does not have programming time error check, SQL
is not really a "programming language" per se. So SQL can be different from
Table and DataStream.
1c)  Although final state 2 seems making it easier for SQL to use given it
is more "config based" than "parameter based", final state 1 can probably
also meet what SQL wants by wrapping the Source in TableSource /
TableSourceFactory API if needed.

Arguments for final state 2:
2a) The Source API itself seems already sort of following the unified API
pattern.
2b) There is no "programming time" method error check in SQL case, so we
cannot really achieve final state 1 across the board.
2c) It is an easier path given our current status, i.e. Table is already
following final state 2.
2d) Users can always explicitly check the boundedness if they want to.

As I mentioned earlier, my initial thought was also to have a
"configuration based" Source rather than a "parameter based" Source. So it
is completely possible that I missed some important consideration or design
principles that we want to enforce for the project. It would be good
if @Stephan
Ewen <[hidden email]> and @Aljoscha Krettek <[hidden email]> can
also provide more thoughts on this.


Re: Jingsong

As you said, there are some batched system source, like parquet/orc source.
> Could we have the batch emit interface to improve performance? The queue of
> per record may cause performance degradation.


The current interface does not necessarily cause performance problem in a
multi-threading case. In fact, the base implementation allows SplitReaders
to add a batch <E> of records<T> to the records queue<E>, so each element
in the records queue would be a batch <E>. In this case, when the main
thread polls records, it will take a batch <E> of records <T> from the
shared records queue and process the records <T> in a batch manner.

Thanks,

Jiangjie (Becket) Qin

On Thu, Dec 12, 2019 at 1:29 PM Jingsong Li <[hidden email]> wrote:

> Hi Becket,
>
> I also have some performance concerns too.
>
> If I understand correctly, SourceOutput will emit data per record into the
> queue? I'm worried about the multithreading performance of this queue.
>
> > One example is some batched messaging systems which only have an offset
> for the entire batch instead of individual messages in the batch.
>
> As you said, there are some batched system source, like parquet/orc source.
> Could we have the batch emit interface to improve performance? The queue of
> per record may cause performance degradation.
>
> Best,
> Jingsong Lee
>
> On Thu, Dec 12, 2019 at 9:15 AM Jark Wu <[hidden email]> wrote:
>
> > Hi Becket,
> >
> > I think Dawid explained things clearly and makes a lot of sense.
> > I'm also in favor of #2, because #1 doesn't work for our future unified
> > envrionment.
> >
> > You can see the vision in this documentation [1]. In the future, we would
> > like to
> > drop the global streaming/batch mode in SQL (i.e.
> > EnvironmentSettings#inStreamingMode/inBatchMode).
> > A source is bounded or unbounded once defined, so queries can be inferred
> > from source to run
> > in streaming or batch or hybrid mode. However, in #1, we will lose this
> > ability because the framework
> > doesn't know whether the source is bounded or unbounded.
> >
> > Best,
> > Jark
> >
> >
> > [1]:
> >
> >
> https://docs.google.com/document/d/1yrKXEIRATfxHJJ0K3t6wUgXAtZq8D-XgvEnvl2uUcr0/edit#heading=h.v4ib17buma1p
> >
> > On Wed, 11 Dec 2019 at 20:52, Piotr Nowojski <[hidden email]>
> wrote:
> >
> > > Hi,
> > >
> > > Regarding the:
> > >
> > > Collection<E> getNextRecords()
> > >
> > > I’m pretty sure such design would unfortunately impact the performance
> > > (accessing and potentially creating the collection on the hot path).
> > >
> > > Also the
> > >
> > > InputStatus emitNext(DataOutput<T> output) throws Exception;
> > > or
> > > Status pollNext(SourceOutput<T> sourceOutput) throws Exception;
> > >
> > > Gives us some opportunities in the future, to allow Source hot looping
> > > inside, until it receives some signal “please exit because of some
> > reasons”
> > > (output collector could return such hint upon collecting the result).
> But
> > > that’s another topic outside of this FLIP’s scope.
> > >
> > > Piotrek
> > >
> > > > On 11 Dec 2019, at 10:41, Till Rohrmann <[hidden email]>
> wrote:
> > > >
> > > > Hi Becket,
> > > >
> > > > quick clarification from my side because I think you misunderstood my
> > > > question. I did not suggest to let the SourceReader return only a
> > single
> > > > record at a time when calling getNextRecords. As the return type
> > > indicates,
> > > > the method can return an arbitrary number of records.
> > > >
> > > > Cheers,
> > > > Till
> > > >
> > > > On Wed, Dec 11, 2019 at 10:13 AM Dawid Wysakowicz <
> > > [hidden email] <mailto:[hidden email]>>
> > > > wrote:
> > > >
> > > >> Hi Becket,
> > > >>
> > > >> Issue #1 - Design of Source interface
> > > >>
> > > >> I mentioned the lack of a method like
> > > Source#createEnumerator(Boundedness
> > > >> boundedness, SplitEnumeratorContext context), because without the
> > > current
> > > >> proposal is not complete/does not work.
> > > >>
> > > >> If we say that boundedness is an intrinsic property of a source imo
> we
> > > >> don't need the Source#createEnumerator(Boundedness boundedness,
> > > >> SplitEnumeratorContext context) method.
> > > >>
> > > >> Assuming a source from my previous example:
> > > >>
> > > >> Source source = KafkaSource.builder()
> > > >>  ...
> > > >>  .untilTimestamp(...)
> > > >>  .build()
> > > >>
> > > >> Would the enumerator differ if created like
> > > >> source.createEnumerator(CONTINUOUS_UNBOUNDED, ...) vs source
> > > >> .createEnumerator(BOUNDED, ...)? I know I am repeating myself, but
> > this
> > > is
> > > >> the part that my opinion differ the most from the current proposal.
> I
> > > >> really think it should always be the source that tells if it is
> > bounded
> > > or
> > > >> not. In the current proposal methods continousSource/boundedSource
> > > somewhat
> > > >> reconfigure the source, which I think is misleading.
> > > >>
> > > >> I think a call like:
> > > >>
> > > >> Source source = KafkaSource.builder()
> > > >>  ...
> > > >>  .readContinously() / readUntilLatestOffset() / readUntilTimestamp /
> > > readUntilOffsets / ...
> > > >>  .build()
> > > >>
> > > >> is way cleaner (and expressive) than
> > > >>
> > > >> Source source = KafkaSource.builder()
> > > >>  ...
> > > >>  .build()
> > > >>
> > > >>
> > > >> env.continousSource(source) // which actually underneath would call
> > > createEnumerator(CONTINUOUS, ctx) which would be equivalent to
> > > source.readContinously().createEnumerator(ctx)
> > > >> // or
> > > >> env.boundedSource(source) // which actually underneath would call
> > > createEnumerator(BOUNDED, ctx) which would be equivalent to
> > > source.readUntilLatestOffset().createEnumerator(ctx)
> > > >>
> > > >>
> > > >> Sorry for the comparison, but to me it seems there is too much magic
> > > >> happening underneath those two calls.
> > > >>
> > > >> I really believe the Source interface should have getBoundedness
> > method
> > > >> instead of (supportBoundedness) + createEnumerator(Boundedness, ...)
> > > >>
> > > >>
> > > >> Issue #2 - Design of
> > > >> ExecutionEnvironment#source()/continuousSource()/boundedSource()
> > > >>
> > > >> As you might have guessed I am slightly in favor of option #2
> > modified.
> > > >> Yes I am aware every step of the dag would have to be able to say if
> > it
> > > is
> > > >> bounded or not. I have a feeling it would be easier to express cross
> > > >> bounded/unbounded operations, but I must admit I have not thought it
> > > >> through thoroughly, In the spirit of batch is just a special case of
> > > >> streaming I thought BoundedStream would extend from DataStream.
> > Correct
> > > me
> > > >> if I am wrong. In such a setup the cross bounded/unbounded operation
> > > could
> > > >> be expressed quite easily I think:
> > > >>
> > > >> DataStream {
> > > >>  DataStream join(DataStream, ...); // we could not really tell if
> the
> > > result is bounded or not, but because bounded stream is a special case
> of
> > > unbounded the API object is correct, irrespective if the left or right
> > side
> > > of the join is bounded
> > > >> }
> > > >>
> > > >> BoundedStream extends DataStream {
> > > >>  BoundedStream join(BoundedStream, ...); // only if both sides are
> > > bounded the result can be bounded as well. However we do have access to
> > the
> > > DataStream#join here, so you can still join with a DataStream
> > > >> }
> > > >>
> > > >>
> > > >> On the other hand I also see benefits of two completely disjointed
> > APIs,
> > > >> as we could prohibit some streaming calls in the bounded API. I
> can't
> > > think
> > > >> of any unbounded operators that could not be implemented for bounded
> > > stream.
> > > >>
> > > >> Besides I think we both agree we don't like the method:
> > > >>
> > > >> DataStream boundedStream(Source)
> > > >>
> > > >> suggested in the current state of the FLIP. Do we ? :)
> > > >>
> > > >> Best,
> > > >>
> > > >> Dawid
> > > >>
> > > >> On 10/12/2019 18:57, Becket Qin wrote:
> > > >>
> > > >> Hi folks,
> > > >>
> > > >> Thanks for the discussion, great feedback. Also thanks Dawid for the
> > > >> explanation, it is much clearer now.
> > > >>
> > > >> One thing that is indeed missing from the FLIP is how the
> boundedness
> > is
> > > >> passed to the Source implementation. So the API should be
> > > >> Source#createEnumerator(Boundedness boundedness,
> > SplitEnumeratorContext
> > > >> context)
> > > >> And we can probably remove the Source#supportBoundedness(Boundedness
> > > >> boundedness) method.
> > > >>
> > > >> Assuming we have that, we are essentially choosing from one of the
> > > >> following two options:
> > > >>
> > > >> Option 1:
> > > >> // The source is continuous source, and only unbounded operations
> can
> > be
> > > >> performed.
> > > >> DataStream<Type> datastream = env.continuousSource(someSource);
> > > >>
> > > >> // The source is bounded source, both bounded and unbounded
> operations
> > > can
> > > >> be performed.
> > > >> BoundedDataStream<Type> boundedDataStream =
> > > env.boundedSource(someSource);
> > > >>
> > > >>  - Pros:
> > > >>       a) explicit boundary between bounded / unbounded streams, it
> is
> > > >> quite simple and clear to the users.
> > > >>  - Cons:
> > > >>       a) For applications that do not involve bounded operations,
> they
> > > >> still have to call different API to distinguish bounded / unbounded
> > > streams.
> > > >>       b) No support for bounded stream to run in a streaming runtime
> > > >> setting, i.e. scheduling and operators behaviors.
> > > >>
> > > >>
> > > >> Option 2:
> > > >> // The source is either bounded or unbounded, but only unbounded
> > > operations
> > > >> could be performed on the returned DataStream.
> > > >> DataStream<Type> dataStream = env.source(someSource);
> > > >>
> > > >> // The source must be a bounded source, otherwise exception is
> thrown.
> > > >> BoundedDataStream<Type> boundedDataStream =
> > > >> env.boundedSource(boundedSource);
> > > >>
> > > >> The pros and cons are exactly the opposite of option 1.
> > > >>  - Pros:
> > > >>       a) For applications that do not involve bounded operations,
> they
> > > >> still have to call different API to distinguish bounded / unbounded
> > > streams.
> > > >>       b) Support for bounded stream to run in a streaming runtime
> > > setting,
> > > >> i.e. scheduling and operators behaviors.
> > > >>  - Cons:
> > > >>       a) Bounded / unbounded streams are kind of mixed, i.e. given a
> > > >> DataStream, it is not clear whether it is bounded or not, unless you
> > > have
> > > >> the access to its source.
> > > >>
> > > >>
> > > >> If we only think from the Source API perspective, option 2 seems a
> > > better
> > > >> choice because functionality wise it is a superset of option 1, at
> the
> > > cost
> > > >> of some seemingly acceptable ambiguity in the DataStream API.
> > > >> But if we look at the DataStream API as a whole, option 1 seems a
> > > clearer
> > > >> choice. For example, some times a library may have to know whether a
> > > >> certain task will finish or not. And it would be difficult to tell
> if
> > > the
> > > >> input is a DataStream, unless additional information is provided all
> > the
> > > >> way from the Source. One possible solution is to have a *modified
> > > option 2*
> > > >> which adds a method to the DataStream API to indicate boundedness,
> > such
> > > as
> > > >> getBoundedness(). It would solve the problem with a potential
> > confusion
> > > of
> > > >> what is difference between a DataStream with getBoundedness()=true
> > and a
> > > >> BoundedDataStream. But that seems not super difficult to explain.
> > > >>
> > > >> So from API's perspective, I don't have a strong opinion between
> > > *option 1*
> > > >> and *modified option 2. *I like the cleanness of option 1, but
> > modified
> > > >> option 2 would be more attractive if we have concrete use case for
> the
> > > >> "Bounded stream with unbounded streaming runtime settings".
> > > >>
> > > >> Re: Till
> > > >>
> > > >>
> > > >> Maybe this has already been asked before but I was wondering why the
> > > >> SourceReader interface has the method pollNext which hands the
> > > >> responsibility of outputting elements to the SourceReader
> > > implementation?
> > > >> Has this been done for backwards compatibility reasons with the old
> > > source
> > > >> interface? If not, then one could define a Collection<E>
> > > getNextRecords()
> > > >> method which returns the currently retrieved records and then the
> > caller
> > > >> emits them outside of the SourceReader. That way the interface would
> > not
> > > >> allow to implement an outputting loop where we never hand back
> control
> > > to
> > > >> the caller. At the moment, this contract can be easily broken and is
> > > only
> > > >> mentioned loosely in the JavaDocs.
> > > >>
> > > >>
> > > >> The primary reason we handover the SourceOutput to the SourceReader
> is
> > > >> because sometimes it is difficult for a SourceReader to emit one
> > record
> > > at
> > > >> a time. One example is some batched messaging systems which only
> have
> > an
> > > >> offset for the entire batch instead of individual messages in the
> > > batch. In
> > > >> that case, returning one record at a time would leave the
> SourceReader
> > > in
> > > >> an uncheckpointable state because they can only checkpoint at the
> > batch
> > > >> boundaries.
> > > >>
> > > >> Thanks,
> > > >>
> > > >> Jiangjie (Becket) Qin
> > > >>
> > > >> On Tue, Dec 10, 2019 at 5:33 PM Till Rohrmann <[hidden email]
> > > <mailto:[hidden email]>> <[hidden email] <mailto:
> > > [hidden email]>> wrote:
> > > >>
> > > >>
> > > >> Hi everyone,
> > > >>
> > > >> thanks for drafting this FLIP. It reads very well.
> > > >>
> > > >> Concerning Dawid's proposal, I tend to agree. The boundedness could
> > come
> > > >> from the source and tell the system how to treat the operator
> > > (scheduling
> > > >> wise). From a user's perspective it should be fine to get back a
> > > DataStream
> > > >> when calling env.source(boundedSource) if he does not need special
> > > >> operations defined on a BoundedDataStream. If he needs this, then
> one
> > > could
> > > >> use the method BoundedDataStream env.boundedSource(boundedSource).
> > > >>
> > > >> If possible, we could enforce the proper usage of
> env.boundedSource()
> > by
> > > >> introducing a BoundedSource type so that one cannot pass an
> > > >> unbounded source to it. That way users would not be able to shoot
> > > >> themselves in the foot.
> > > >>
> > > >> Maybe this has already been asked before but I was wondering why the
> > > >> SourceReader interface has the method pollNext which hands the
> > > >> responsibility of outputting elements to the SourceReader
> > > implementation?
> > > >> Has this been done for backwards compatibility reasons with the old
> > > source
> > > >> interface? If not, then one could define a Collection<E>
> > > getNextRecords()
> > > >> method which returns the currently retrieved records and then the
> > caller
> > > >> emits them outside of the SourceReader. That way the interface would
> > not
> > > >> allow to implement an outputting loop where we never hand back
> control
> > > to
> > > >> the caller. At the moment, this contract can be easily broken and is
> > > only
> > > >> mentioned loosely in the JavaDocs.
> > > >>
> > > >> Cheers,
> > > >> Till
> > > >>
> > > >> On Tue, Dec 10, 2019 at 7:49 AM Jingsong Li <[hidden email]
> > > <mailto:[hidden email]>> <[hidden email] <mailto:
> > > [hidden email]>>
> > > >> wrote:
> > > >>
> > > >>
> > > >> Hi all,
> > > >>
> > > >> I think current design is good.
> > > >>
> > > >> My understanding is:
> > > >>
> > > >> For execution mode: bounded mode and continuous mode, It's totally
> > > >> different. I don't think we have the ability to integrate the two
> > models
> > > >>
> > > >> at
> > > >>
> > > >> present. It's about scheduling, memory, algorithms, States, etc. we
> > > >> shouldn't confuse them.
> > > >>
> > > >> For source capabilities: only bounded, only continuous, both bounded
> > and
> > > >> continuous.
> > > >> I think Kafka is a source that can be ran both bounded
> > > >> and continuous execution mode.
> > > >> And Kafka with end offset should be ran both bounded
> > > >> and continuous execution mode.  Using apache Beam with Flink
> runner, I
> > > >>
> > > >> used
> > > >>
> > > >> to run a "bounded" Kafka in streaming mode. For our previous
> > DataStream,
> > > >>
> > > >> it
> > > >>
> > > >> is not necessarily required that the source cannot be bounded.
> > > >>
> > > >> So it is my thought for Dawid's question:
> > > >> 1.pass a bounded source to continuousSource() +1
> > > >> 2.pass a continuous source to boundedSource() -1, should throw
> > > exception.
> > > >>
> > > >> In StreamExecutionEnvironment, continuousSource and boundedSource
> > define
> > > >> the execution mode. It defines a clear boundary of execution mode.
> > > >>
> > > >> Best,
> > > >> Jingsong Lee
> > > >>
> > > >> On Tue, Dec 10, 2019 at 10:37 AM Jark Wu <[hidden email] <mailto:
> > > [hidden email]>> <[hidden email] <mailto:[hidden email]>> wrote:
> > > >>
> > > >>
> > > >> I agree with Dawid's point that the boundedness information should
> > come
> > > >> from the source itself (e.g. the end timestamp), not through
> > > >> env.boundedSouce()/continuousSource().
> > > >> I think if we want to support something like `env.source()` that
> > derive
> > > >>
> > > >> the
> > > >>
> > > >> execution mode from source, `supportsBoundedness(Boundedness)`
> > > >> method is not enough, because we don't know whether it is bounded or
> > > >>
> > > >> not.
> > > >>
> > > >> Best,
> > > >> Jark
> > > >>
> > > >>
> > > >> On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <
> [hidden email]
> > > <mailto:[hidden email]>> <[hidden email] <mailto:
> > > [hidden email]>>
> > > >> wrote:
> > > >>
> > > >>
> > > >> One more thing. In the current proposal, with the
> > > >> supportsBoundedness(Boundedness) method and the boundedness coming
> > > >>
> > > >> from
> > > >>
> > > >> either continuousSource or boundedSource I could not find how this
> > > >> information is fed back to the SplitEnumerator.
> > > >>
> > > >> Best,
> > > >>
> > > >> Dawid
> > > >>
> > > >> On 09/12/2019 13:52, Becket Qin wrote:
> > > >>
> > > >> Hi Dawid,
> > > >>
> > > >> Thanks for the comments. This actually brings another relevant
> > > >>
> > > >> question
> > > >>
> > > >> about what does a "bounded source" imply. I actually had the same
> > > >> impression when I look at the Source API. Here is what I understand
> > > >>
> > > >> after
> > > >>
> > > >> some discussion with Stephan. The bounded source has the following
> > > >>
> > > >> impacts.
> > > >>
> > > >> 1. API validity.
> > > >> - A bounded source generates a bounded stream so some operations
> > > >>
> > > >> that
> > > >>
> > > >> only
> > > >>
> > > >> works for bounded records would be performed, e.g. sort.
> > > >> - To expose these bounded stream only APIs, there are two options:
> > > >>     a. Add them to the DataStream API and throw exception if a
> > > >>
> > > >> method
> > > >>
> > > >> is
> > > >>
> > > >> called on an unbounded stream.
> > > >>     b. Create a BoundedDataStream class which is returned from
> > > >> env.boundedSource(), while DataStream is returned from
> > > >>
> > > >> env.continousSource().
> > > >>
> > > >> Note that this cannot be done by having single
> > > >>
> > > >> env.source(theSource)
> > > >>
> > > >> even
> > > >>
> > > >> the Source has a getBoundedness() method.
> > > >>
> > > >> 2. Scheduling
> > > >> - A bounded source could be computed stage by stage without
> > > >>
> > > >> bringing
> > > >>
> > > >> up
> > > >>
> > > >> all
> > > >>
> > > >> the tasks at the same time.
> > > >>
> > > >> 3. Operator behaviors
> > > >> - A bounded source indicates the records are finite so some
> > > >>
> > > >> operators
> > > >>
> > > >> can
> > > >>
> > > >> wait until it receives all the records before it starts the
> > > >>
> > > >> processing.
> > > >>
> > > >> In the above impact, only 1 is relevant to the API design. And the
> > > >>
> > > >> current
> > > >>
> > > >> proposal in FLIP-27 is following 1.b.
> > > >>
> > > >> // boundedness depends of source property, imo this should always
> > > >>
> > > >> be
> > > >>
> > > >> preferred
> > > >>
> > > >>
> > > >> DataStream<MyType> stream = env.source(theSource);
> > > >>
> > > >>
> > > >> In your proposal, does DataStream have bounded stream only methods?
> > > >>
> > > >> It
> > > >>
> > > >> looks it should have, otherwise passing a bounded Source to
> > > >>
> > > >> env.source()
> > > >>
> > > >> would be confusing. In that case, we will essentially do 1.a if an
> > > >> unbounded Source is created from env.source(unboundedSource).
> > > >>
> > > >> If we have the methods only supported for bounded streams in
> > > >>
> > > >> DataStream,
> > > >>
> > > >> it
> > > >>
> > > >> seems a little weird to have a separate BoundedDataStream
> > > >>
> > > >> interface.
> > > >>
> > > >> Am I understand it correctly?
> > > >>
> > > >> Thanks,
> > > >>
> > > >> Jiangjie (Becket) Qin
> > > >>
> > > >>
> > > >>
> > > >> On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <
> > > >>
> > > >> [hidden email] <mailto:[hidden email]>>
> > > >>
> > > >> wrote:
> > > >>
> > > >>
> > > >> Hi all,
> > > >>
> > > >> Really well written proposal and very important one. I must admit
> > > >>
> > > >> I
> > > >>
> > > >> have
> > > >>
> > > >> not understood all the intricacies of it yet.
> > > >>
> > > >> One question I have though is about where does the information
> > > >>
> > > >> about
> > > >>
> > > >> boundedness come from. I think in most cases it is a property of
> > > >>
> > > >> the
> > > >>
> > > >> source. As you described it might be e.g. end offset, a flag
> > > >>
> > > >> should
> > > >>
> > > >> it
> > > >>
> > > >> monitor new splits etc. I think it would be a really nice use case
> > > >>
> > > >> to
> > > >>
> > > >> be
> > > >>
> > > >> able to say:
> > > >>
> > > >> new KafkaSource().readUntil(long timestamp),
> > > >>
> > > >> which could work as an "end offset". Moreover I think all Bounded
> > > >>
> > > >> sources
> > > >>
> > > >> support continuous mode, but no intrinsically continuous source
> > > >>
> > > >> support
> > > >>
> > > >> the
> > > >>
> > > >> Bounded mode. If I understood the proposal correctly it suggest
> > > >>
> > > >> the
> > > >>
> > > >> boundedness sort of "comes" from the outside of the source, from
> > > >>
> > > >> the
> > > >>
> > > >> invokation of either boundedStream or continousSource.
> > > >>
> > > >> I am wondering if it would make sense to actually change the
> > > >>
> > > >> method
> > > >>
> > > >> boolean Source#supportsBoundedness(Boundedness)
> > > >>
> > > >> to
> > > >>
> > > >> Boundedness Source#getBoundedness().
> > > >>
> > > >> As for the methods #boundedSource, #continousSource, assuming the
> > > >> boundedness is property of the source they do not affect how the
> > > >>
> > > >> enumerator
> > > >>
> > > >> works, but mostly how the dag is scheduled, right? I am not
> > > >>
> > > >> against
> > > >>
> > > >> those
> > > >>
> > > >> methods, but I think it is a very specific use case to actually
> > > >>
> > > >> override
> > > >>
> > > >> the property of the source. In general I would expect users to
> > > >>
> > > >> only
> > > >>
> > > >> call
> > > >>
> > > >> env.source(theSource), where the source tells if it is bounded or
> > > >>
> > > >> not. I
> > > >>
> > > >> would suggest considering following set of methods:
> > > >>
> > > >> // boundedness depends of source property, imo this should always
> > > >>
> > > >> be
> > > >>
> > > >> preferred
> > > >>
> > > >> DataStream<MyType> stream = env.source(theSource);
> > > >>
> > > >>
> > > >> // always continous execution, whether bounded or unbounded source
> > > >>
> > > >> DataStream<MyType> boundedStream = env.continousSource(theSource);
> > > >>
> > > >> // imo this would make sense if the BoundedDataStream provides
> > > >>
> > > >> additional features unavailable for continous mode
> > > >>
> > > >> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
> > > >>
> > > >>
> > > >> Best,
> > > >>
> > > >> Dawid
> > > >>
> > > >>
> > > >> On 04/12/2019 11:25, Stephan Ewen wrote:
> > > >>
> > > >> Thanks, Becket, for updating this.
> > > >>
> > > >> I agree with moving the aspects you mentioned into separate FLIPs
> > > >>
> > > >> -
> > > >>
> > > >> this
> > > >>
> > > >> one way becoming unwieldy in size.
> > > >>
> > > >> +1 to the FLIP in its current state. Its a very detailed write-up,
> > > >>
> > > >> nicely
> > > >>
> > > >> done!
> > > >>
> > > >> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]
> > > <mailto:[hidden email]>> <[hidden email] <mailto:
> > > [hidden email]>>
> > > >>
> > > >> <
> > > >>
> > > >> [hidden email] <mailto:[hidden email]>> wrote:
> > > >>
> > > >> Hi all,
> > > >>
> > > >> Sorry for the long belated update. I have updated FLIP-27 wiki
> > > >>
> > > >> page
> > > >>
> > > >> with
> > > >>
> > > >> the latest proposals. Some noticeable changes include:
> > > >> 1. A new generic communication mechanism between SplitEnumerator
> > > >>
> > > >> and
> > > >>
> > > >> SourceReader.
> > > >> 2. Some detail API method signature changes.
> > > >>
> > > >> We left a few things out of this FLIP and will address them in
> > > >>
> > > >> separate
> > > >>
> > > >> FLIPs. Including:
> > > >> 1. Per split event time.
> > > >> 2. Event time alignment.
> > > >> 3. Fine grained failover for SplitEnumerator failure.
> > > >>
> > > >> Please let us know if you have any question.
> > > >>
> > > >> Thanks,
> > > >>
> > > >> Jiangjie (Becket) Qin
> > > >>
> > > >> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]
> > <mailto:
> > > [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> > > >>
> > > >> [hidden email] <mailto:[hidden email]>> wrote:
> > > >>
> > > >> Hi  Łukasz!
> > > >>
> > > >> Becket and me are working hard on figuring out the last details
> > > >>
> > > >> and
> > > >>
> > > >> implementing the first PoC. We would update the FLIP hopefully
> > > >>
> > > >> next
> > > >>
> > > >> week.
> > > >>
> > > >> There is a fair chance that a first version of this will be in
> > > >>
> > > >> 1.10,
> > > >>
> > > >> but
> > > >>
> > > >> I
> > > >>
> > > >> think it will take another release to battle test it and migrate
> > > >>
> > > >> the
> > > >>
> > > >> connectors.
> > > >>
> > > >> Best,
> > > >> Stephan
> > > >>
> > > >>
> > > >>
> > > >>
> > > >> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <[hidden email]
> > > <mailto:[hidden email]>
> > > >>
> > > >> <
> > > >>
> > > >> [hidden email] <mailto:[hidden email]>>
> > > >>
> > > >> wrote:
> > > >>
> > > >> Hi,
> > > >>
> > > >> This proposal looks very promising for us. Do you have any plans
> > > >>
> > > >> in
> > > >>
> > > >> which
> > > >>
> > > >> Flink release it is going to be released? We are thinking on
> > > >>
> > > >> using a
> > > >>
> > > >> Data
> > > >>
> > > >> Set API for our future use cases but on the other hand Data Set
> > > >>
> > > >> API
> > > >>
> > > >> is
> > > >>
> > > >> going to be deprecated so using proposed bounded data streams
> > > >>
> > > >> solution
> > > >>
> > > >> could be more viable in the long term.
> > > >>
> > > >> Thanks,
> > > >> Łukasz
> > > >>
> > > >> On 2019/10/01 15:48:03, Thomas Weise <[hidden email]
> <mailto:
> > > [hidden email]>> <[hidden email] <mailto:
> > > [hidden email]>> <
> > > >>
> > > >> [hidden email] <mailto:[hidden email]>> wrote:
> > > >>
> > > >> Thanks for putting together this proposal!
> > > >>
> > > >> I see that the "Per Split Event Time" and "Event Time Alignment"
> > > >>
> > > >> sections
> > > >>
> > > >> are still TBD.
> > > >>
> > > >> It would probably be good to flesh those out a bit before
> > > >>
> > > >> proceeding
> > > >>
> > > >> too
> > > >>
> > > >> far
> > > >>
> > > >> as the event time alignment will probably influence the
> > > >>
> > > >> interaction
> > > >>
> > > >> with
> > > >>
> > > >> the split reader, specifically ReaderStatus
> > > >>
> > > >> emitNext(SourceOutput<E>
> > > >>
> > > >> output).
> > > >>
> > > >> We currently have only one implementation for event time alignment
> > > >>
> > > >> in
> > > >>
> > > >> the
> > > >>
> > > >> Kinesis consumer. The synchronization in that case takes place as
> > > >>
> > > >> the
> > > >>
> > > >> last
> > > >>
> > > >> step before records are emitted downstream (RecordEmitter). With
> > > >>
> > > >> the
> > > >>
> > > >> currently proposed interfaces, the equivalent can be implemented
> > > >>
> > > >> in
> > > >>
> > > >> the
> > > >>
> > > >> reader loop, although note that in the Kinesis consumer the per
> > > >>
> > > >> shard
> > > >>
> > > >> threads push records.
> > > >>
> > > >> Synchronization has not been implemented for the Kafka consumer
> > > >>
> > > >> yet.
> > > >>
> > > >> https://issues.apache.org/jira/browse/FLINK-12675 <
> > > https://issues.apache.org/jira/browse/FLINK-12675>
> > > >>
> > > >> When I looked at it, I realized that the implementation will look
> > > >>
> > > >> quite
> > > >>
> > > >> different
> > > >> from Kinesis because it needs to take place in the pull part,
> > > >>
> > > >> where
> > > >>
> > > >> records
> > > >>
> > > >> are taken from the Kafka client. Due to the multiplexing it cannot
> > > >>
> > > >> be
> > > >>
> > > >> done
> > > >>
> > > >> by blocking the split thread like it currently works for Kinesis.
> > > >>
> > > >> Reading
> > > >>
> > > >> from individual Kafka partitions needs to be controlled via
> > > >>
> > > >> pause/resume
> > > >>
> > > >> on the Kafka client.
> > > >>
> > > >> To take on that responsibility the split thread would need to be
> > > >>
> > > >> aware
> > > >>
> > > >> of
> > > >>
> > > >> the
> > > >> watermarks or at least whether it should or should not continue to
> > > >>
> > > >> consume
> > > >>
> > > >> a given split and this may require a different SourceReader or
> > > >>
> > > >> SourceOutput
> > > >>
> > > >> interface.
> > > >>
> > > >> Thanks,
> > > >> Thomas
> > > >>
> > > >>
> > > >> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email]
> <mailto:
> > > [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> <
> > > >>
> > > >> [hidden email] <mailto:[hidden email]>> wrote:
> > > >>
> > > >> Hi Stephan,
> > > >>
> > > >> Thank you for feedback!
> > > >> Will take a look at your branch before public discussing.
> > > >>
> > > >>
> > > >> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]
> > > <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]
> >>
> > > >>
> > > >> <
> > > >>
> > > >> [hidden email] <mailto:[hidden email]>>
> > > >>
> > > >> wrote:
> > > >>
> > > >> Hi Biao!
> > > >>
> > > >> Thanks for reviving this. I would like to join this discussion,
> > > >>
> > > >> but
> > > >>
> > > >> am
> > > >>
> > > >> quite occupied with the 1.9 release, so can we maybe pause this
> > > >>
> > > >> discussion
> > > >>
> > > >> for a week or so?
> > > >>
> > > >> In the meantime I can share some suggestion based on prior
> > > >>
> > > >> experiments:
> > > >>
> > > >> How to do watermarks / timestamp extractors in a simpler and more
> > > >>
> > > >> flexible
> > > >>
> > > >> way. I think that part is quite promising should be part of the
> > > >>
> > > >> new
> > > >>
> > > >> source
> > > >>
> > > >> interface.
> > > >>
> > > >>
> > > >>
> > > >>
> > > >>
> > > >>
> > >
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> > > <
> > >
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> > > >
> > > >>
> > > >>
> > >
> >
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> > > <
> > >
> >
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> > > >
> > > >>
> > > >> Some experiments on how to build the source reader and its
> > > >>
> > > >> library
> > > >>
> > > >> for
> > > >>
> > > >> common threading/split patterns:
> > > >>
> > > >>
> > > >>
> > > >>
> > > >>
> > > >>
> > >
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> > > <
> > >
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> > > >
> > > >>
> > > >> Best,
> > > >> Stephan
> > > >>
> > > >>
> > > >> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]
> > <mailto:
> > > [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> <
> > > >>
> > > >> [hidden email] <mailto:[hidden email]>>
> > > >>
> > > >> wrote:
> > > >>
> > > >> Hi devs,
> > > >>
> > > >> Since 1.9 is nearly released, I think we could get back to
> > > >>
> > > >> FLIP-27.
> > > >>
> > > >> I
> > > >>
> > > >> believe it should be included in 1.10.
> > > >>
> > > >> There are so many things mentioned in document of FLIP-27. [1] I
> > > >>
> > > >> think
> > > >>
> > > >> we'd better discuss them separately. However the wiki is not a
> > > >>
> > > >> good
> > > >>
> > > >> place
> > > >>
> > > >> to discuss. I wrote google doc about SplitReader API which
> > > >>
> > > >> misses
> > > >>
> > > >> some
> > > >>
> > > >> details in the document. [2]
> > > >>
> > > >> 1.
> > > >>
> > > >>
> > > >>
> > > >>
> > > >>
> > >
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> > > <
> > >
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> > > >
> > > >>
> > > >> 2.
> > > >>
> > > >>
> > > >>
> > > >>
> > > >>
> > >
> >
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> > > <
> > >
> >
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> > > >
> > > >>
> > > >> CC Stephan, Aljoscha, Piotrek, Becket
> > > >>
> > > >>
> > > >> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email]
> <mailto:
> > > [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> <
> > > >>
> > > >> [hidden email] <mailto:[hidden email]>>
> > > >>
> > > >> wrote:
> > > >>
> > > >> Hi Steven,
> > > >> Thank you for the feedback. Please take a look at the document
> > > >>
> > > >> FLIP-27
> > > >>
> > > >> <
> > > >>
> > > >>
> > > >>
> > > >>
> > >
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> > > <
> > >
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> > > >
> > > >>
> > > >> which
> > > >>
> > > >> is updated recently. A lot of details of enumerator were added
> > > >>
> > > >> in
> > > >>
> > > >> this
> > > >>
> > > >> document. I think it would help.
> > > >>
> > > >> Steven Wu <[hidden email] <mailto:[hidden email]>> <
> > > [hidden email] <mailto:[hidden email]>> <
> > [hidden email]
> > > <mailto:[hidden email]>> <[hidden email] <mailto:
> > > [hidden email]>>
> > > >>
> > > >> 于2019年3月28日周四
> > > >>
> > > >> 下午12:52写道：
> > > >>
> > > >> This proposal mentioned that SplitEnumerator might run on the
> > > >> JobManager or
> > > >> in a single task on a TaskManager.
> > > >>
> > > >> if enumerator is a single task on a taskmanager, then the job
> > > >>
> > > >> DAG
> > > >>
> > > >> can
> > > >>
> > > >> never
> > > >> been embarrassingly parallel anymore. That will nullify the
> > > >>
> > > >> leverage
> > > >>
> > > >> of
> > > >>
> > > >> fine-grained recovery for embarrassingly parallel jobs.
> > > >>
> > > >> It's not clear to me what's the implication of running
> > > >>
> > > >> enumerator
> > > >>
> > > >> on
> > > >>
> > > >> the
> > > >>
> > > >> jobmanager. So I will leave that out for now.
> > > >>
> > > >> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email]
> <mailto:
> > > [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> <
> > > >>
> > > >> [hidden email] <mailto:[hidden email]>>
> > > >>
> > > >> wrote:
> > > >>
> > > >> Hi Stephan & Piotrek,
> > > >>
> > > >> Thank you for feedback.
> > > >>
> > > >> It seems that there are a lot of things to do in community.
> > > >>
> > > >> I
> > > >>
> > > >> am
> > > >>
> > > >> just
> > > >>
> > > >> afraid that this discussion may be forgotten since there so
> > > >>
> > > >> many
> > > >>
> > > >> proposals
> > > >>
> > > >> recently.
> > > >> Anyway, wish to see the split topics soon :)
> > > >>
> > > >> Piotr Nowojski <[hidden email] <mailto:[hidden email]
> >>
> > <
> > > [hidden email] <mailto:[hidden email]>> <
> > > [hidden email] <mailto:[hidden email]>> <
> > > [hidden email] <mailto:[hidden email]>>
> > > >>
> > > >> 于2019年1月24日周四
> > > >>
> > > >> 下午8:21写道：
> > > >>
> > > >> Hi Biao!
> > > >>
> > > >> This discussion was stalled because of preparations for
> > > >>
> > > >> the
> > > >>
> > > >> open
> > > >>
> > > >> sourcing
> > > >>
> > > >> & merging Blink. I think before creating the tickets we
> > > >>
> > > >> should
> > > >>
> > > >> split this
> > > >>
> > > >> discussion into topics/areas outlined by Stephan and
> > > >>
> > > >> create
> > > >>
> > > >> Flips
> > > >>
> > > >> for
> > > >>
> > > >> that.
> > > >>
> > > >> I think there is no chance for this to be completed in
> > > >>
> > > >> couple
> > > >>
> > > >> of
> > > >>
> > > >> remaining
> > > >>
> > > >> weeks/1 month before 1.8 feature freeze, however it would
> > > >>
> > > >> be
> > > >>
> > > >> good
> > > >>
> > > >> to aim
> > > >>
> > > >> with those changes for 1.9.
> > > >>
> > > >> Piotrek
> > > >>
> > > >>
> > > >> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email] <mailto:
> > > [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> <
> > > >>
> > > >> [hidden email] <mailto:[hidden email]>>
> > > >>
> > > >> wrote:
> > > >>
> > > >> Hi community,
> > > >> The summary of Stephan makes a lot sense to me. It is
> > > >>
> > > >> much
> > > >>
> > > >> clearer
> > > >>
> > > >> indeed
> > > >>
> > > >> after splitting the complex topic into small ones.
> > > >> I was wondering is there any detail plan for next step?
> > > >>
> > > >> If
> > > >>
> > > >> not,
> > > >>
> > > >> I
> > > >>
> > > >> would
> > > >>
> > > >> like to push this thing forward by creating some JIRA
> > > >>
> > > >> issues.
> > > >>
> > > >> Another question is that should version 1.8 include
> > > >>
> > > >> these
> > > >>
> > > >> features?
> > > >>
> > > >> Stephan Ewen <[hidden email] <mailto:[hidden email]>> <
> > > [hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:
> > > [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> > > 于2018年12月1日周六
> > > >>
> > > >> 上午4:20写道：
> > > >>
> > > >> Thanks everyone for the lively discussion. Let me try
> > > >>
> > > >> to
> > > >>
> > > >> summarize
> > > >>
> > > >> where I
> > > >>
> > > >> see convergence in the discussion and open issues.
> > > >> I'll try to group this by design aspect of the source.
> > > >>
> > > >> Please
> > > >>
> > > >> let me
> > > >>
> > > >> know
> > > >>
> > > >> if I got things wrong or missed something crucial here.
> > > >>
> > > >> For issues 1-3, if the below reflects the state of the
> > > >>
> > > >> discussion, I
> > > >>
> > > >> would
> > > >>
> > > >> try and update the FLIP in the next days.
> > > >> For the remaining ones we need more discussion.
> > > >>
> > > >> I would suggest to fork each of these aspects into a
> > > >>
> > > >> separate
> > > >>
> > > >> mail
> > > >>
> > > >> thread,
> > > >>
> > > >> or will loose sight of the individual aspects.
> > > >>
> > > >> *(1) Separation of Split Enumerator and Split Reader*
> > > >>
> > > >> - All seem to agree this is a good thing
> > > >> - Split Enumerator could in the end live on JobManager
> > > >>
> > > >> (and
> > > >>
> > > >> assign
> > > >>
> > > >> splits
> > > >>
> > > >> via RPC) or in a task (and assign splits via data
> > > >>
> > > >> streams)
> > > >>
> > > >> - this discussion is orthogonal and should come later,
> > > >>
> > > >> when
> > > >>
> > > >> the
> > > >>
> > > >> interface
> > > >>
> > > >> is agreed upon.
> > > >>
> > > >> *(2) Split Readers for one or more splits*
> > > >>
> > > >> - Discussion seems to agree that we need to support
> > > >>
> > > >> one
> > > >>
> > > >> reader
> > > >>
> > > >> that
> > > >>
> > > >> possibly handles multiple splits concurrently.
> > > >> - The requirement comes from sources where one
> > > >>
> > > >> poll()-style
> > > >>
> > > >> call
> > > >>
> > > >> fetches
> > > >>
> > > >> data from different splits / partitions
> > > >>   --> example sources that require that would be for
> > > >>
> > > >> example
> > > >>
> > > >> Kafka,
> > > >>
> > > >> Pravega, Pulsar
> > > >>
> > > >> - Could have one split reader per source, or multiple
> > > >>
> > > >> split
> > > >>
> > > >> readers
> > > >>
> > > >> that
> > > >>
> > > >> share the "poll()" function
> > > >> - To not make it too complicated, we can start with
> > > >>
> > > >> thinking
> > > >>
> > > >> about
> > > >>
> > > >> one
> > > >>
> > > >> split reader for all splits initially and see if that
> > > >>
> > > >> covers
> > > >>
> > > >> all
> > > >>
> > > >> requirements
> > > >>
> > > >> *(3) Threading model of the Split Reader*
> > > >>
> > > >> - Most active part of the discussion ;-)
> > > >>
> > > >> - A non-blocking way for Flink's task code to interact
> > > >>
> > > >> with
> > > >>
> > > >> the
> > > >>
> > > >> source
> > > >>
> > > >> is
> > > >>
> > > >> needed in order to a task runtime code based on a
> > > >> single-threaded/actor-style task design
> > > >>   --> I personally am a big proponent of that, it will
> > > >>
> > > >> help
> > > >>
> > > >> with
> > > >>
> > > >> well-behaved checkpoints, efficiency, and simpler yet
> > > >>
> > > >> more
> > > >>
> > > >> robust
> > > >>
> > > >> runtime
> > > >>
> > > >> code
> > > >>
> > > >> - Users care about simple abstraction, so as a
> > > >>
> > > >> subclass
> > > >>
> > > >> of
> > > >>
> > > >> SplitReader
> > > >>
> > > >> (non-blocking / async) we need to have a
> > > >>
> > > >> BlockingSplitReader
> > > >>
> > > >> which
> > > >>
> > > >> will
> > > >>
> > > >> form the basis of most source implementations.
> > > >>
> > > >> BlockingSplitReader
> > > >>
> > > >> lets
> > > >>
> > > >> users do blocking simple poll() calls.
> > > >> - The BlockingSplitReader would spawn a thread (or
> > > >>
> > > >> more)
> > > >>
> > > >> and
> > > >>
> > > >> the
> > > >>
> > > >> thread(s) can make blocking calls and hand over data
> > > >>
> > > >> buffers
> > > >>
> > > >> via
> > > >>
> > > >> a
> > > >>
> > > >> blocking
> > > >>
> > > >> queue
> > > >> - This should allow us to cover both, a fully async
> > > >>
> > > >> runtime,
> > > >>
> > > >> and a
> > > >>
> > > >> simple
> > > >>
> > > >> blocking interface for users.
> > > >> - This is actually very similar to how the Kafka
> > > >>
> > > >> connectors
> > > >>
> > > >> work.
> > > >>
> > > >> Kafka
> > > >>
> > > >> 9+ with one thread, Kafka 8 with multiple threads
> > > >>
> > > >> - On the base SplitReader (the async one), the
> > > >>
> > > >> non-blocking
> > > >>
> > > >> method
> > > >>
> > > >> that
> > > >>
> > > >> gets the next chunk of data would signal data
> > > >>
> > > >> availability
> > > >>
> > > >> via
> > > >>
> > > >> a
> > > >>
> > > >> CompletableFuture, because that gives the best
> > > >>
> > > >> flexibility
> > > >>
> > > >> (can
> > > >>
> > > >> await
> > > >>
> > > >> completion or register notification handlers).
> > > >> - The source task would register a "thenHandle()" (or
> > > >>
> > > >> similar)
> > > >>
> > > >> on the
> > > >>
> > > >> future to put a "take next data" task into the
> > > >>
> > > >> actor-style
> > > >>
> > > >> mailbox
> > > >>
> > > >> *(4) Split Enumeration and Assignment*
> > > >>
> > > >> - Splits may be generated lazily, both in cases where
> > > >>
> > > >> there
> > > >>
> > > >> is a
> > > >>
> > > >> limited
> > > >>
> > > >> number of splits (but very many), or splits are
> > > >>
> > > >> discovered
> > > >>
> > > >> over
> > > >>
> > > >> time
> > > >>
> > > >> - Assignment should also be lazy, to get better load
> > > >>
> > > >> balancing
> > > >>
> > > >> - Assignment needs support locality preferences
> > > >>
> > > >> - Possible design based on discussion so far:
> > > >>
> > > >>   --> SplitReader has a method "addSplits(SplitT...)"
> > > >>
> > > >> to
> > > >>
> > > >> add
> > > >>
> > > >> one or
> > > >>
> > > >> more
> > > >>
> > > >> splits. Some split readers might assume they have only
> > > >>
> > > >> one
> > > >>
> > > >> split
> > > >>
> > > >> ever,
> > > >>
> > > >> concurrently, others assume multiple splits. (Note:
> > > >>
> > > >> idea
> > > >>
> > > >> behind
> > > >>
> > > >> being
> > > >>
> > > >> able
> > > >>
> > > >> to add multiple splits at the same time is to ease
> > > >>
> > > >> startup
> > > >>
> > > >> where
> > > >>
> > > >> multiple
> > > >>
> > > >> splits may be assigned instantly.)
> > > >>   --> SplitReader has a context object on which it can
> > > >>
> > > >> call
> > > >>
> > > >> indicate
> > > >>
> > > >> when
> > > >>
> > > >> splits are completed. The enumerator gets that
> > > >>
> > > >> notification and
> > > >>
> > > >> can
> > > >>
> > > >> use
> > > >>
> > > >> to
> > > >>
> > > >> decide when to assign new splits. This should help both
> > > >>
> > > >> in
> > > >>
> > > >> cases
> > > >>
> > > >> of
> > > >>
> > > >> sources
> > > >>
> > > >> that take splits lazily (file readers) and in case the
> > > >>
> > > >> source
> > > >>
> > > >> needs to
> > > >>
> > > >> preserve a partial order between splits (Kinesis,
> > > >>
> > > >> Pravega,
> > > >>
> > > >> Pulsar may
> > > >>
> > > >> need
> > > >>
> > > >> that).
> > > >>   --> SplitEnumerator gets notification when
> > > >>
> > > >> SplitReaders
> > > >>
> > > >> start
> > > >>
> > > >> and
> > > >>
> > > >> when
> > > >>
> > > >> they finish splits. They can decide at that moment to
> > > >>
> > > >> push
> > > >>
> > > >> more
> > > >>
> > > >> splits
> > > >>
> > > >> to
> > > >>
> > > >> that reader
> > > >>   --> The SplitEnumerator should probably be aware of
> > > >>
> > > >> the
> > > >>
> > > >> source
> > > >>
> > > >> parallelism, to build its initial distribution.
> > > >>
> > > >> - Open question: Should the source expose something
> > > >>
> > > >> like
> > > >>
> > > >> "host
> > > >>
> > > >> preferences", so that yarn/mesos/k8s can take this into
> > > >>
> > > >> account
> > > >>
> > > >> when
> > > >>
> > > >> selecting a node to start a TM on?
> > > >>
> > > >> *(5) Watermarks and event time alignment*
> > > >>
> > > >> - Watermark generation, as well as idleness, needs to
> > > >>
> > > >> be
> > > >>
> > > >> per
> > > >>
> > > >> split
> > > >>
> > > >> (like
> > > >>
> > > >> currently in the Kafka Source, per partition)
> > > >> - It is desirable to support optional
> > > >>
> > > >> event-time-alignment,
> > > >>
> > > >> meaning
> > > >>
> > > >> that
> > > >>
> > > >> splits that are ahead are back-pressured or temporarily
> > > >>
> > > >> unsubscribed
> > > >>
> > > >> - I think i would be desirable to encapsulate
> > > >>
> > > >> watermark
> > > >>
> > > >> generation
> > > >>
> > > >> logic
> > > >>
> > > >> in watermark generators, for a separation of concerns.
> > > >>
> > > >> The
> > > >>
> > > >> watermark
> > > >>
> > > >> generators should run per split.
> > > >> - Using watermark generators would also help with
> > > >>
> > > >> another
> > > >>
> > > >> problem of
> > > >>
> > > >> the
> > > >>
> > > >> suggested interface, namely supporting non-periodic
> > > >>
> > > >> watermarks
> > > >>
> > > >> efficiently.
> > > >>
> > > >> - Need a way to "dispatch" next record to different
> > > >>
> > > >> watermark
> > > >>
> > > >> generators
> > > >>
> > > >> - Need a way to tell SplitReader to "suspend" a split
> > > >>
> > > >> until a
> > > >>
> > > >> certain
> > > >>
> > > >> watermark is reached (event time backpressure)
> > > >> - This would in fact be not needed (and thus simpler)
> > > >>
> > > >> if
> > > >>
> > > >> we
> > > >>
> > > >> had
> > > >>
> > > >> a
> > > >>
> > > >> SplitReader per split and may be a reason to re-open
> > > >>
> > > >> that
> > > >>
> > > >> discussion
> > > >>
> > > >> *(6) Watermarks across splits and in the Split
> > > >>
> > > >> Enumerator*
> > > >>
> > > >> - The split enumerator may need some watermark
> > > >>
> > > >> awareness,
> > > >>
> > > >> which
> > > >>
> > > >> should
> > > >>
> > > >> be
> > > >>
> > > >> purely based on split metadata (like create timestamp
> > > >>
> > > >> of
> > > >>
> > > >> file
> > > >>
> > > >> splits)
> > > >>
> > > >> - If there are still more splits with overlapping
> > > >>
> > > >> event
> > > >>
> > > >> time
> > > >>
> > > >> range
> > > >>
> > > >> for
> > > >>
> > > >> a
> > > >>
> > > >> split reader, then that split reader should not advance
> > > >>
> > > >> the
> > > >>
> > > >> watermark
> > > >>
> > > >> within the split beyond the overlap boundary. Otherwise
> > > >>
> > > >> future
> > > >>
> > > >> splits
> > > >>
> > > >> will
> > > >>
> > > >> produce late data.
> > > >>
> > > >> - One way to approach this could be that the split
> > > >>
> > > >> enumerator
> > > >>
> > > >> may
> > > >>
> > > >> send
> > > >>
> > > >> watermarks to the readers, and the readers cannot emit
> > > >>
> > > >> watermarks
> > > >>
> > > >> beyond
> > > >>
> > > >> that received watermark.
> > > >> - Many split enumerators would simply immediately send
> > > >>
> > > >> Long.MAX
> > > >>
> > > >> out
> > > >>
> > > >> and
> > > >>
> > > >> leave the progress purely to the split readers.
> > > >>
> > > >> - For event-time alignment / split back pressure, this
> > > >>
> > > >> begs
> > > >>
> > > >> the
> > > >>
> > > >> question
> > > >>
> > > >> how we can avoid deadlocks that may arise when splits
> > > >>
> > > >> are
> > > >>
> > > >> suspended
> > > >>
> > > >> for
> > > >>
> > > >> event time back pressure,
> > > >>
> > > >> *(7) Batch and streaming Unification*
> > > >>
> > > >> - Functionality wise, the above design should support
> > > >>
> > > >> both
> > > >>
> > > >> - Batch often (mostly) does not care about reading "in
> > > >>
> > > >> order"
> > > >>
> > > >> and
> > > >>
> > > >> generating watermarks
> > > >>   --> Might use different enumerator logic that is
> > > >>
> > > >> more
> > > >>
> > > >> locality
> > > >>
> > > >> aware
> > > >>
> > > >> and ignores event time order
> > > >>   --> Does not generate watermarks
> > > >> - Would be great if bounded sources could be
> > > >>
> > > >> identified
> > > >>
> > > >> at
> > > >>
> > > >> compile
> > > >>
> > > >> time,
> > > >>
> > > >> so that "env.addBoundedSource(...)" is type safe and
> > > >>
> > > >> can
> > > >>
> > > >> return a
> > > >>
> > > >> "BoundedDataStream".
> > > >> - Possible to defer this discussion until later
> > > >>
> > > >> *Miscellaneous Comments*
> > > >>
> > > >> - Should the source have a TypeInformation for the
> > > >>
> > > >> produced
> > > >>
> > > >> type,
> > > >>
> > > >> instead
> > > >>
> > > >> of a serializer? We need a type information in the
> > > >>
> > > >> stream
> > > >>
> > > >> anyways, and
> > > >>
> > > >> can
> > > >>
> > > >> derive the serializer from that. Plus, creating the
> > > >>
> > > >> serializer
> > > >>
> > > >> should
> > > >>
> > > >> respect the ExecutionConfig.
> > > >>
> > > >> - The TypeSerializer interface is very powerful but
> > > >>
> > > >> also
> > > >>
> > > >> not
> > > >>
> > > >> easy to
> > > >>
> > > >> implement. Its purpose is to handle data super
> > > >>
> > > >> efficiently,
> > > >>
> > > >> support
> > > >>
> > > >> flexible ways of evolution, etc.
> > > >> For metadata I would suggest to look at the
> > > >>
> > > >> SimpleVersionedSerializer
> > > >>
> > > >> instead, which is used for example for checkpoint
> > > >>
> > > >> master
> > > >>
> > > >> hooks,
> > > >>
> > > >> or for
> > > >>
> > > >> the
> > > >>
> > > >> streaming file sink. I think that is is a good match
> > > >>
> > > >> for
> > > >>
> > > >> cases
> > > >>
> > > >> where
> > > >>
> > > >> we
> > > >>
> > > >> do
> > > >>
> > > >> not need more than ser/deser (no copy, etc.) and don't
> > > >>
> > > >> need to
> > > >>
> > > >> push
> > > >>
> > > >> versioning out of the serialization paths for best
> > > >>
> > > >> performance
> > > >>
> > > >> (as in
> > > >>
> > > >> the
> > > >>
> > > >> TypeSerializer)
> > > >>
> > > >>
> > > >> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
> > > >>
> > > >> [hidden email]>
> > > >>
> > > >> wrote:
> > > >>
> > > >>
> > > >> Hi Biao,
> > > >>
> > > >> Thanks for the answer!
> > > >>
> > > >> So given the multi-threaded readers, now we have as
> > > >>
> > > >> open
> > > >>
> > > >> questions:
> > > >>
> > > >> 1) How do we let the checkpoints pass through our
> > > >>
> > > >> multi-threaded
> > > >>
> > > >> reader
> > > >>
> > > >> operator?
> > > >>
> > > >> 2) Do we have separate reader and source operators or
> > > >>
> > > >> not? In
> > > >>
> > > >> the
> > > >>
> > > >> strategy
> > > >>
> > > >> that has a separate source, the source operator has a
> > > >>
> > > >> parallelism of
> > > >>
> > > >> 1
> > > >>
> > > >> and
> > > >>
> > > >> is responsible for split recovery only.
> > > >>
> > > >> For the first one, given also the constraints
> > > >>
> > > >> (blocking,
> > > >>
> > > >> finite
> > > >>
> > > >> queues,
> > > >>
> > > >> etc), I do not have an answer yet.
> > > >>
> > > >> For the 2nd, I think that we should go with separate
> > > >>
> > > >> operators
> > > >>
> > > >> for
> > > >>
> > > >> the
> > > >>
> > > >> source and the readers, for the following reasons:
> > > >>
> > > >> 1) This is more aligned with a potential future
> > > >>
> > > >> improvement
> > > >>
> > > >> where the
> > > >>
> > > >> split
> > > >>
> > > >> discovery becomes a responsibility of the JobManager
> > > >>
> > > >> and
> > > >>
> > > >> readers are
> > > >>
> > > >> pooling more work from the JM.
> > > >>
> > > >> 2) The source is going to be the "single point of
> > > >>
> > > >> truth".
> > > >>
> > > >> It
> > > >>
> > > >> will
> > > >>
> > > >> know
> > > >>
> > > >> what
> > > >>
> > > >> has been processed and what not. If the source and the
> > > >>
> > > >> readers
> > > >>
> > > >> are a
> > > >>
> > > >> single
> > > >>
> > > >> operator with parallelism > 1, or in general, if the
> > > >>
> > > >> split
> > > >>
> > > >> discovery
> > > >>
> > > >> is
> > > >>
> > > >> done by each task individually, then:
> > > >>  i) we have to have a deterministic scheme for each
> > > >>
> > > >> reader to
> > > >>
> > > >> assign
> > > >>
> > > >> splits to itself (e.g. mod subtaskId). This is not
> > > >>
> > > >> necessarily
> > > >>
> > > >> trivial
> > > >>
> > > >> for
> > > >>
> > > >> all sources.
> > > >>  ii) each reader would have to keep a copy of all its
> > > >>
> > > >> processed
> > > >>
> > > >> slpits
> > > >>
> > > >>  iii) the state has to be a union state with a
> > > >>
> > > >> non-trivial
> > > >>
> > > >> merging
> > > >>
> > > >> logic
> > > >>
> > > >> in order to support rescaling.
> > > >>
> > > >> Two additional points that you raised above:
> > > >>
> > > >> i) The point that you raised that we need to keep all
> > > >>
> > > >> splits
> > > >>
> > > >> (processed
> > > >>
> > > >> and
> > > >>
> > > >> not-processed) I think is a bit of a strong
> > > >>
> > > >> requirement.
> > > >>
> > > >> This
> > > >>
> > > >> would
> > > >>
> > > >> imply
> > > >>
> > > >> that for infinite sources the state will grow
> > > >>
> > > >> indefinitely.
> > > >>
> > > >> This is
> > > >>
> > > >> problem
> > > >>
> > > >> is even more pronounced if we do not have a single
> > > >>
> > > >> source
> > > >>
> > > >> that
> > > >>
> > > >> assigns
> > > >>
> > > >> splits to readers, as each reader will have its own
> > > >>
> > > >> copy
> > > >>
> > > >> of
> > > >>
> > > >> the
> > > >>
> > > >> state.
> > > >>
> > > >> ii) it is true that for finite sources we need to
> > > >>
> > > >> somehow
> > > >>
> > > >> not
> > > >>
> > > >> close
> > > >>
> > > >> the
> > > >>
> > > >> readers when the source/split discoverer finishes. The
> > > >> ContinuousFileReaderOperator has a work-around for
> > > >>
> > > >> that.
> > > >>
> > > >> It is
> > > >>
> > > >> not
> > > >>
> > > >> elegant,
> > > >>
> > > >> and checkpoints are not emitted after closing the
> > > >>
> > > >> source,
> > > >>
> > > >> but
> > > >>
> > > >> this, I
> > > >>
> > > >> believe, is a bigger problem which requires more
> > > >>
> > > >> changes
> > > >>
> > > >> than
> > > >>
> > > >> just
> > > >>
> > > >> refactoring the source interface.
> > > >>
> > > >> Cheers,
> > > >> Kostas
> > > >>
> > > >>
> > > >>
> > > >>
> > > >> --
> > > >> Best, Jingsong Lee
> > >
> > >
> >
>
>
> --
> Best, Jingsong Lee
>

[Timo Walther-2]

Hi Becket,

I completely agree with Dawid's suggestion. The information about the
boundedness should come out of the source. Because most of the streaming
sources can be made bounded based on some connector specific criterion.
In Kafka, it would be an end offset or end timestamp but in any case
having just a env.boundedSource() is not enough because parameters for
making the source bounded are missing.

I suggest to have a simple `isBounded(): Boolean` flag in every source
that might be influenced by a connector builder as Dawid mentioned.

For type safety during programming, we can still go with *Final state
1*. By having a env.source() vs env.boundedSource(). The latter would
just enforce that the boolean flag is set to `true` and could make
bounded operations available (if we need that actually).

However, I don't think that we should start making a unified Table API
ununified again. Boundedness is an optimization property. Every bounded
operation can also executed in an unbounded way using updates/retraction
or watermarks.

Regards,
Timo


On 15.12.19 14:22, Becket Qin wrote:

> Hi Dawid and Jark,
>
> I think the discussion ultimately boils down to the question that which one
> of the following two final states do we want? Once we make this decision,
> everything else can be naturally derived.
>
> *Final state 1*: Separate API for bounded / unbounded DataStream & Table.
> That means any code users write will be valid at the point when they write
> the code. This is similar to having type safety check at programming time.
> For example,
>
> BoundedDataStream extends DataStream {
> // Operations only available for bounded data.
> BoundedDataStream sort(...);
>
> // Interaction with another BoundedStream returns a Bounded stream.
> BoundedJoinedDataStream join(BoundedDataStream other)
>
> // Interaction with another unbounded stream returns an unbounded stream.
> JoinedDataStream join(DataStream other)
> }
>
> BoundedTable extends Table {
>    // Bounded only operation.
> BoundedTable sort(...);
>
> // Interaction with another BoundedTable returns a BoundedTable.
> BoundedTable join(BoundedTable other)
>
> // Interaction with another unbounded table returns an unbounded table.
> Table join(Table other)
> }
>
> *Final state 2*: One unified API for bounded / unbounded DataStream /
> Table.
> That unified API may throw exception at DAG compilation time if an invalid
> operation is tried. This is what Table API currently follows.
>
> DataStream {
> // Throws exception if the DataStream is unbounded.
> DataStream sort();
> // Get boundedness.
> Boundedness getBoundedness();
> }
>
> Table {
> // Throws exception if the table has infinite rows.
> Table orderBy();
>
> // Get boundedness.
> Boundedness getBoundedness();
> }
>
>>From what I understand, there is no consensus so far on this decision yet.
> Whichever final state we choose, we need to make it consistent across the
> entire project. We should avoid the case that Table follows one final state
> while DataStream follows another. Some arguments I am aware of from both
> sides so far are following:
>
> Arguments for final state 1:
> 1a) Clean API with method safety check at programming time.
> 1b) (Counter 2b) Although SQL does not have programming time error check, SQL
> is not really a "programming language" per se. So SQL can be different from
> Table and DataStream.
> 1c)  Although final state 2 seems making it easier for SQL to use given it
> is more "config based" than "parameter based", final state 1 can probably
> also meet what SQL wants by wrapping the Source in TableSource /
> TableSourceFactory API if needed.
>
> Arguments for final state 2:
> 2a) The Source API itself seems already sort of following the unified API
> pattern.
> 2b) There is no "programming time" method error check in SQL case, so we
> cannot really achieve final state 1 across the board.
> 2c) It is an easier path given our current status, i.e. Table is already
> following final state 2.
> 2d) Users can always explicitly check the boundedness if they want to.
>
> As I mentioned earlier, my initial thought was also to have a
> "configuration based" Source rather than a "parameter based" Source. So it
> is completely possible that I missed some important consideration or design
> principles that we want to enforce for the project. It would be good
> if @Stephan
> Ewen <[hidden email]> and @Aljoscha Krettek <[hidden email]> can
> also provide more thoughts on this.
>
>
> Re: Jingsong
>
> As you said, there are some batched system source, like parquet/orc source.
>> Could we have the batch emit interface to improve performance? The queue of
>> per record may cause performance degradation.
>
>
> The current interface does not necessarily cause performance problem in a
> multi-threading case. In fact, the base implementation allows SplitReaders
> to add a batch <E> of records<T> to the records queue<E>, so each element
> in the records queue would be a batch <E>. In this case, when the main
> thread polls records, it will take a batch <E> of records <T> from the
> shared records queue and process the records <T> in a batch manner.
>
> Thanks,
>
> Jiangjie (Becket) Qin
>
> On Thu, Dec 12, 2019 at 1:29 PM Jingsong Li <[hidden email]> wrote:
>
>> Hi Becket,
>>
>> I also have some performance concerns too.
>>
>> If I understand correctly, SourceOutput will emit data per record into the
>> queue? I'm worried about the multithreading performance of this queue.
>>
>>> One example is some batched messaging systems which only have an offset
>> for the entire batch instead of individual messages in the batch.
>>
>> As you said, there are some batched system source, like parquet/orc source.
>> Could we have the batch emit interface to improve performance? The queue of
>> per record may cause performance degradation.
>>
>> Best,
>> Jingsong Lee
>>
>> On Thu, Dec 12, 2019 at 9:15 AM Jark Wu <[hidden email]> wrote:
>>
>>> Hi Becket,
>>>
>>> I think Dawid explained things clearly and makes a lot of sense.
>>> I'm also in favor of #2, because #1 doesn't work for our future unified
>>> envrionment.
>>>
>>> You can see the vision in this documentation [1]. In the future, we would
>>> like to
>>> drop the global streaming/batch mode in SQL (i.e.
>>> EnvironmentSettings#inStreamingMode/inBatchMode).
>>> A source is bounded or unbounded once defined, so queries can be inferred
>>> from source to run
>>> in streaming or batch or hybrid mode. However, in #1, we will lose this
>>> ability because the framework
>>> doesn't know whether the source is bounded or unbounded.
>>>
>>> Best,
>>> Jark
>>>
>>>
>>> [1]:
>>>
>>>
>> https://docs.google.com/document/d/1yrKXEIRATfxHJJ0K3t6wUgXAtZq8D-XgvEnvl2uUcr0/edit#heading=h.v4ib17buma1p
>>>
>>> On Wed, 11 Dec 2019 at 20:52, Piotr Nowojski <[hidden email]>
>> wrote:
>>>
>>>> Hi,
>>>>
>>>> Regarding the:
>>>>
>>>> Collection<E> getNextRecords()
>>>>
>>>> I’m pretty sure such design would unfortunately impact the performance
>>>> (accessing and potentially creating the collection on the hot path).
>>>>
>>>> Also the
>>>>
>>>> InputStatus emitNext(DataOutput<T> output) throws Exception;
>>>> or
>>>> Status pollNext(SourceOutput<T> sourceOutput) throws Exception;
>>>>
>>>> Gives us some opportunities in the future, to allow Source hot looping
>>>> inside, until it receives some signal “please exit because of some
>>> reasons”
>>>> (output collector could return such hint upon collecting the result).
>> But
>>>> that’s another topic outside of this FLIP’s scope.
>>>>
>>>> Piotrek
>>>>
>>>>> On 11 Dec 2019, at 10:41, Till Rohrmann <[hidden email]>
>> wrote:
>>>>>
>>>>> Hi Becket,
>>>>>
>>>>> quick clarification from my side because I think you misunderstood my
>>>>> question. I did not suggest to let the SourceReader return only a
>>> single
>>>>> record at a time when calling getNextRecords. As the return type
>>>> indicates,
>>>>> the method can return an arbitrary number of records.
>>>>>
>>>>> Cheers,
>>>>> Till
>>>>>
>>>>> On Wed, Dec 11, 2019 at 10:13 AM Dawid Wysakowicz <
>>>> [hidden email] <mailto:[hidden email]>>
>>>>> wrote:
>>>>>
>>>>>> Hi Becket,
>>>>>>
>>>>>> Issue #1 - Design of Source interface
>>>>>>
>>>>>> I mentioned the lack of a method like
>>>> Source#createEnumerator(Boundedness
>>>>>> boundedness, SplitEnumeratorContext context), because without the
>>>> current
>>>>>> proposal is not complete/does not work.
>>>>>>
>>>>>> If we say that boundedness is an intrinsic property of a source imo
>> we
>>>>>> don't need the Source#createEnumerator(Boundedness boundedness,
>>>>>> SplitEnumeratorContext context) method.
>>>>>>
>>>>>> Assuming a source from my previous example:
>>>>>>
>>>>>> Source source = KafkaSource.builder()
>>>>>>   ...
>>>>>>   .untilTimestamp(...)
>>>>>>   .build()
>>>>>>
>>>>>> Would the enumerator differ if created like
>>>>>> source.createEnumerator(CONTINUOUS_UNBOUNDED, ...) vs source
>>>>>> .createEnumerator(BOUNDED, ...)? I know I am repeating myself, but
>>> this
>>>> is
>>>>>> the part that my opinion differ the most from the current proposal.
>> I
>>>>>> really think it should always be the source that tells if it is
>>> bounded
>>>> or
>>>>>> not. In the current proposal methods continousSource/boundedSource
>>>> somewhat
>>>>>> reconfigure the source, which I think is misleading.
>>>>>>
>>>>>> I think a call like:
>>>>>>
>>>>>> Source source = KafkaSource.builder()
>>>>>>   ...
>>>>>>   .readContinously() / readUntilLatestOffset() / readUntilTimestamp /
>>>> readUntilOffsets / ...
>>>>>>   .build()
>>>>>>
>>>>>> is way cleaner (and expressive) than
>>>>>>
>>>>>> Source source = KafkaSource.builder()
>>>>>>   ...
>>>>>>   .build()
>>>>>>
>>>>>>
>>>>>> env.continousSource(source) // which actually underneath would call
>>>> createEnumerator(CONTINUOUS, ctx) which would be equivalent to
>>>> source.readContinously().createEnumerator(ctx)
>>>>>> // or
>>>>>> env.boundedSource(source) // which actually underneath would call
>>>> createEnumerator(BOUNDED, ctx) which would be equivalent to
>>>> source.readUntilLatestOffset().createEnumerator(ctx)
>>>>>>
>>>>>>
>>>>>> Sorry for the comparison, but to me it seems there is too much magic
>>>>>> happening underneath those two calls.
>>>>>>
>>>>>> I really believe the Source interface should have getBoundedness
>>> method
>>>>>> instead of (supportBoundedness) + createEnumerator(Boundedness, ...)
>>>>>>
>>>>>>
>>>>>> Issue #2 - Design of
>>>>>> ExecutionEnvironment#source()/continuousSource()/boundedSource()
>>>>>>
>>>>>> As you might have guessed I am slightly in favor of option #2
>>> modified.
>>>>>> Yes I am aware every step of the dag would have to be able to say if
>>> it
>>>> is
>>>>>> bounded or not. I have a feeling it would be easier to express cross
>>>>>> bounded/unbounded operations, but I must admit I have not thought it
>>>>>> through thoroughly, In the spirit of batch is just a special case of
>>>>>> streaming I thought BoundedStream would extend from DataStream.
>>> Correct
>>>> me
>>>>>> if I am wrong. In such a setup the cross bounded/unbounded operation
>>>> could
>>>>>> be expressed quite easily I think:
>>>>>>
>>>>>> DataStream {
>>>>>>   DataStream join(DataStream, ...); // we could not really tell if
>> the
>>>> result is bounded or not, but because bounded stream is a special case
>> of
>>>> unbounded the API object is correct, irrespective if the left or right
>>> side
>>>> of the join is bounded
>>>>>> }
>>>>>>
>>>>>> BoundedStream extends DataStream {
>>>>>>   BoundedStream join(BoundedStream, ...); // only if both sides are
>>>> bounded the result can be bounded as well. However we do have access to
>>> the
>>>> DataStream#join here, so you can still join with a DataStream
>>>>>> }
>>>>>>
>>>>>>
>>>>>> On the other hand I also see benefits of two completely disjointed
>>> APIs,
>>>>>> as we could prohibit some streaming calls in the bounded API. I
>> can't
>>>> think
>>>>>> of any unbounded operators that could not be implemented for bounded
>>>> stream.
>>>>>>
>>>>>> Besides I think we both agree we don't like the method:
>>>>>>
>>>>>> DataStream boundedStream(Source)
>>>>>>
>>>>>> suggested in the current state of the FLIP. Do we ? :)
>>>>>>
>>>>>> Best,
>>>>>>
>>>>>> Dawid
>>>>>>
>>>>>> On 10/12/2019 18:57, Becket Qin wrote:
>>>>>>
>>>>>> Hi folks,
>>>>>>
>>>>>> Thanks for the discussion, great feedback. Also thanks Dawid for the
>>>>>> explanation, it is much clearer now.
>>>>>>
>>>>>> One thing that is indeed missing from the FLIP is how the
>> boundedness
>>> is
>>>>>> passed to the Source implementation. So the API should be
>>>>>> Source#createEnumerator(Boundedness boundedness,
>>> SplitEnumeratorContext
>>>>>> context)
>>>>>> And we can probably remove the Source#supportBoundedness(Boundedness
>>>>>> boundedness) method.
>>>>>>
>>>>>> Assuming we have that, we are essentially choosing from one of the
>>>>>> following two options:
>>>>>>
>>>>>> Option 1:
>>>>>> // The source is continuous source, and only unbounded operations
>> can
>>> be
>>>>>> performed.
>>>>>> DataStream<Type> datastream = env.continuousSource(someSource);
>>>>>>
>>>>>> // The source is bounded source, both bounded and unbounded
>> operations
>>>> can
>>>>>> be performed.
>>>>>> BoundedDataStream<Type> boundedDataStream =
>>>> env.boundedSource(someSource);
>>>>>>
>>>>>>   - Pros:
>>>>>>        a) explicit boundary between bounded / unbounded streams, it
>> is
>>>>>> quite simple and clear to the users.
>>>>>>   - Cons:
>>>>>>        a) For applications that do not involve bounded operations,
>> they
>>>>>> still have to call different API to distinguish bounded / unbounded
>>>> streams.
>>>>>>        b) No support for bounded stream to run in a streaming runtime
>>>>>> setting, i.e. scheduling and operators behaviors.
>>>>>>
>>>>>>
>>>>>> Option 2:
>>>>>> // The source is either bounded or unbounded, but only unbounded
>>>> operations
>>>>>> could be performed on the returned DataStream.
>>>>>> DataStream<Type> dataStream = env.source(someSource);
>>>>>>
>>>>>> // The source must be a bounded source, otherwise exception is
>> thrown.
>>>>>> BoundedDataStream<Type> boundedDataStream =
>>>>>> env.boundedSource(boundedSource);
>>>>>>
>>>>>> The pros and cons are exactly the opposite of option 1.
>>>>>>   - Pros:
>>>>>>        a) For applications that do not involve bounded operations,
>> they
>>>>>> still have to call different API to distinguish bounded / unbounded
>>>> streams.
>>>>>>        b) Support for bounded stream to run in a streaming runtime
>>>> setting,
>>>>>> i.e. scheduling and operators behaviors.
>>>>>>   - Cons:
>>>>>>        a) Bounded / unbounded streams are kind of mixed, i.e. given a
>>>>>> DataStream, it is not clear whether it is bounded or not, unless you
>>>> have
>>>>>> the access to its source.
>>>>>>
>>>>>>
>>>>>> If we only think from the Source API perspective, option 2 seems a
>>>> better
>>>>>> choice because functionality wise it is a superset of option 1, at
>> the
>>>> cost
>>>>>> of some seemingly acceptable ambiguity in the DataStream API.
>>>>>> But if we look at the DataStream API as a whole, option 1 seems a
>>>> clearer
>>>>>> choice. For example, some times a library may have to know whether a
>>>>>> certain task will finish or not. And it would be difficult to tell
>> if
>>>> the
>>>>>> input is a DataStream, unless additional information is provided all
>>> the
>>>>>> way from the Source. One possible solution is to have a *modified
>>>> option 2*
>>>>>> which adds a method to the DataStream API to indicate boundedness,
>>> such
>>>> as
>>>>>> getBoundedness(). It would solve the problem with a potential
>>> confusion
>>>> of
>>>>>> what is difference between a DataStream with getBoundedness()=true
>>> and a
>>>>>> BoundedDataStream. But that seems not super difficult to explain.
>>>>>>
>>>>>> So from API's perspective, I don't have a strong opinion between
>>>> *option 1*
>>>>>> and *modified option 2. *I like the cleanness of option 1, but
>>> modified
>>>>>> option 2 would be more attractive if we have concrete use case for
>> the
>>>>>> "Bounded stream with unbounded streaming runtime settings".
>>>>>>
>>>>>> Re: Till
>>>>>>
>>>>>>
>>>>>> Maybe this has already been asked before but I was wondering why the
>>>>>> SourceReader interface has the method pollNext which hands the
>>>>>> responsibility of outputting elements to the SourceReader
>>>> implementation?
>>>>>> Has this been done for backwards compatibility reasons with the old
>>>> source
>>>>>> interface? If not, then one could define a Collection<E>
>>>> getNextRecords()
>>>>>> method which returns the currently retrieved records and then the
>>> caller
>>>>>> emits them outside of the SourceReader. That way the interface would
>>> not
>>>>>> allow to implement an outputting loop where we never hand back
>> control
>>>> to
>>>>>> the caller. At the moment, this contract can be easily broken and is
>>>> only
>>>>>> mentioned loosely in the JavaDocs.
>>>>>>
>>>>>>
>>>>>> The primary reason we handover the SourceOutput to the SourceReader
>> is
>>>>>> because sometimes it is difficult for a SourceReader to emit one
>>> record
>>>> at
>>>>>> a time. One example is some batched messaging systems which only
>> have
>>> an
>>>>>> offset for the entire batch instead of individual messages in the
>>>> batch. In
>>>>>> that case, returning one record at a time would leave the
>> SourceReader
>>>> in
>>>>>> an uncheckpointable state because they can only checkpoint at the
>>> batch
>>>>>> boundaries.
>>>>>>
>>>>>> Thanks,
>>>>>>
>>>>>> Jiangjie (Becket) Qin
>>>>>>
>>>>>> On Tue, Dec 10, 2019 at 5:33 PM Till Rohrmann <[hidden email]
>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
>>>> [hidden email]>> wrote:
>>>>>>
>>>>>>
>>>>>> Hi everyone,
>>>>>>
>>>>>> thanks for drafting this FLIP. It reads very well.
>>>>>>
>>>>>> Concerning Dawid's proposal, I tend to agree. The boundedness could
>>> come
>>>>>> from the source and tell the system how to treat the operator
>>>> (scheduling
>>>>>> wise). From a user's perspective it should be fine to get back a
>>>> DataStream
>>>>>> when calling env.source(boundedSource) if he does not need special
>>>>>> operations defined on a BoundedDataStream. If he needs this, then
>> one
>>>> could
>>>>>> use the method BoundedDataStream env.boundedSource(boundedSource).
>>>>>>
>>>>>> If possible, we could enforce the proper usage of
>> env.boundedSource()
>>> by
>>>>>> introducing a BoundedSource type so that one cannot pass an
>>>>>> unbounded source to it. That way users would not be able to shoot
>>>>>> themselves in the foot.
>>>>>>
>>>>>> Maybe this has already been asked before but I was wondering why the
>>>>>> SourceReader interface has the method pollNext which hands the
>>>>>> responsibility of outputting elements to the SourceReader
>>>> implementation?
>>>>>> Has this been done for backwards compatibility reasons with the old
>>>> source
>>>>>> interface? If not, then one could define a Collection<E>
>>>> getNextRecords()
>>>>>> method which returns the currently retrieved records and then the
>>> caller
>>>>>> emits them outside of the SourceReader. That way the interface would
>>> not
>>>>>> allow to implement an outputting loop where we never hand back
>> control
>>>> to
>>>>>> the caller. At the moment, this contract can be easily broken and is
>>>> only
>>>>>> mentioned loosely in the JavaDocs.
>>>>>>
>>>>>> Cheers,
>>>>>> Till
>>>>>>
>>>>>> On Tue, Dec 10, 2019 at 7:49 AM Jingsong Li <[hidden email]
>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
>>>> [hidden email]>>
>>>>>> wrote:
>>>>>>
>>>>>>
>>>>>> Hi all,
>>>>>>
>>>>>> I think current design is good.
>>>>>>
>>>>>> My understanding is:
>>>>>>
>>>>>> For execution mode: bounded mode and continuous mode, It's totally
>>>>>> different. I don't think we have the ability to integrate the two
>>> models
>>>>>>
>>>>>> at
>>>>>>
>>>>>> present. It's about scheduling, memory, algorithms, States, etc. we
>>>>>> shouldn't confuse them.
>>>>>>
>>>>>> For source capabilities: only bounded, only continuous, both bounded
>>> and
>>>>>> continuous.
>>>>>> I think Kafka is a source that can be ran both bounded
>>>>>> and continuous execution mode.
>>>>>> And Kafka with end offset should be ran both bounded
>>>>>> and continuous execution mode.  Using apache Beam with Flink
>> runner, I
>>>>>>
>>>>>> used
>>>>>>
>>>>>> to run a "bounded" Kafka in streaming mode. For our previous
>>> DataStream,
>>>>>>
>>>>>> it
>>>>>>
>>>>>> is not necessarily required that the source cannot be bounded.
>>>>>>
>>>>>> So it is my thought for Dawid's question:
>>>>>> 1.pass a bounded source to continuousSource() +1
>>>>>> 2.pass a continuous source to boundedSource() -1, should throw
>>>> exception.
>>>>>>
>>>>>> In StreamExecutionEnvironment, continuousSource and boundedSource
>>> define
>>>>>> the execution mode. It defines a clear boundary of execution mode.
>>>>>>
>>>>>> Best,
>>>>>> Jingsong Lee
>>>>>>
>>>>>> On Tue, Dec 10, 2019 at 10:37 AM Jark Wu <[hidden email] <mailto:
>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>> wrote:
>>>>>>
>>>>>>
>>>>>> I agree with Dawid's point that the boundedness information should
>>> come
>>>>>> from the source itself (e.g. the end timestamp), not through
>>>>>> env.boundedSouce()/continuousSource().
>>>>>> I think if we want to support something like `env.source()` that
>>> derive
>>>>>>
>>>>>> the
>>>>>>
>>>>>> execution mode from source, `supportsBoundedness(Boundedness)`
>>>>>> method is not enough, because we don't know whether it is bounded or
>>>>>>
>>>>>> not.
>>>>>>
>>>>>> Best,
>>>>>> Jark
>>>>>>
>>>>>>
>>>>>> On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <
>> [hidden email]
>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
>>>> [hidden email]>>
>>>>>> wrote:
>>>>>>
>>>>>>
>>>>>> One more thing. In the current proposal, with the
>>>>>> supportsBoundedness(Boundedness) method and the boundedness coming
>>>>>>
>>>>>> from
>>>>>>
>>>>>> either continuousSource or boundedSource I could not find how this
>>>>>> information is fed back to the SplitEnumerator.
>>>>>>
>>>>>> Best,
>>>>>>
>>>>>> Dawid
>>>>>>
>>>>>> On 09/12/2019 13:52, Becket Qin wrote:
>>>>>>
>>>>>> Hi Dawid,
>>>>>>
>>>>>> Thanks for the comments. This actually brings another relevant
>>>>>>
>>>>>> question
>>>>>>
>>>>>> about what does a "bounded source" imply. I actually had the same
>>>>>> impression when I look at the Source API. Here is what I understand
>>>>>>
>>>>>> after
>>>>>>
>>>>>> some discussion with Stephan. The bounded source has the following
>>>>>>
>>>>>> impacts.
>>>>>>
>>>>>> 1. API validity.
>>>>>> - A bounded source generates a bounded stream so some operations
>>>>>>
>>>>>> that
>>>>>>
>>>>>> only
>>>>>>
>>>>>> works for bounded records would be performed, e.g. sort.
>>>>>> - To expose these bounded stream only APIs, there are two options:
>>>>>>      a. Add them to the DataStream API and throw exception if a
>>>>>>
>>>>>> method
>>>>>>
>>>>>> is
>>>>>>
>>>>>> called on an unbounded stream.
>>>>>>      b. Create a BoundedDataStream class which is returned from
>>>>>> env.boundedSource(), while DataStream is returned from
>>>>>>
>>>>>> env.continousSource().
>>>>>>
>>>>>> Note that this cannot be done by having single
>>>>>>
>>>>>> env.source(theSource)
>>>>>>
>>>>>> even
>>>>>>
>>>>>> the Source has a getBoundedness() method.
>>>>>>
>>>>>> 2. Scheduling
>>>>>> - A bounded source could be computed stage by stage without
>>>>>>
>>>>>> bringing
>>>>>>
>>>>>> up
>>>>>>
>>>>>> all
>>>>>>
>>>>>> the tasks at the same time.
>>>>>>
>>>>>> 3. Operator behaviors
>>>>>> - A bounded source indicates the records are finite so some
>>>>>>
>>>>>> operators
>>>>>>
>>>>>> can
>>>>>>
>>>>>> wait until it receives all the records before it starts the
>>>>>>
>>>>>> processing.
>>>>>>
>>>>>> In the above impact, only 1 is relevant to the API design. And the
>>>>>>
>>>>>> current
>>>>>>
>>>>>> proposal in FLIP-27 is following 1.b.
>>>>>>
>>>>>> // boundedness depends of source property, imo this should always
>>>>>>
>>>>>> be
>>>>>>
>>>>>> preferred
>>>>>>
>>>>>>
>>>>>> DataStream<MyType> stream = env.source(theSource);
>>>>>>
>>>>>>
>>>>>> In your proposal, does DataStream have bounded stream only methods?
>>>>>>
>>>>>> It
>>>>>>
>>>>>> looks it should have, otherwise passing a bounded Source to
>>>>>>
>>>>>> env.source()
>>>>>>
>>>>>> would be confusing. In that case, we will essentially do 1.a if an
>>>>>> unbounded Source is created from env.source(unboundedSource).
>>>>>>
>>>>>> If we have the methods only supported for bounded streams in
>>>>>>
>>>>>> DataStream,
>>>>>>
>>>>>> it
>>>>>>
>>>>>> seems a little weird to have a separate BoundedDataStream
>>>>>>
>>>>>> interface.
>>>>>>
>>>>>> Am I understand it correctly?
>>>>>>
>>>>>> Thanks,
>>>>>>
>>>>>> Jiangjie (Becket) Qin
>>>>>>
>>>>>>
>>>>>>
>>>>>> On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <
>>>>>>
>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>
>>>>>> wrote:
>>>>>>
>>>>>>
>>>>>> Hi all,
>>>>>>
>>>>>> Really well written proposal and very important one. I must admit
>>>>>>
>>>>>> I
>>>>>>
>>>>>> have
>>>>>>
>>>>>> not understood all the intricacies of it yet.
>>>>>>
>>>>>> One question I have though is about where does the information
>>>>>>
>>>>>> about
>>>>>>
>>>>>> boundedness come from. I think in most cases it is a property of
>>>>>>
>>>>>> the
>>>>>>
>>>>>> source. As you described it might be e.g. end offset, a flag
>>>>>>
>>>>>> should
>>>>>>
>>>>>> it
>>>>>>
>>>>>> monitor new splits etc. I think it would be a really nice use case
>>>>>>
>>>>>> to
>>>>>>
>>>>>> be
>>>>>>
>>>>>> able to say:
>>>>>>
>>>>>> new KafkaSource().readUntil(long timestamp),
>>>>>>
>>>>>> which could work as an "end offset". Moreover I think all Bounded
>>>>>>
>>>>>> sources
>>>>>>
>>>>>> support continuous mode, but no intrinsically continuous source
>>>>>>
>>>>>> support
>>>>>>
>>>>>> the
>>>>>>
>>>>>> Bounded mode. If I understood the proposal correctly it suggest
>>>>>>
>>>>>> the
>>>>>>
>>>>>> boundedness sort of "comes" from the outside of the source, from
>>>>>>
>>>>>> the
>>>>>>
>>>>>> invokation of either boundedStream or continousSource.
>>>>>>
>>>>>> I am wondering if it would make sense to actually change the
>>>>>>
>>>>>> method
>>>>>>
>>>>>> boolean Source#supportsBoundedness(Boundedness)
>>>>>>
>>>>>> to
>>>>>>
>>>>>> Boundedness Source#getBoundedness().
>>>>>>
>>>>>> As for the methods #boundedSource, #continousSource, assuming the
>>>>>> boundedness is property of the source they do not affect how the
>>>>>>
>>>>>> enumerator
>>>>>>
>>>>>> works, but mostly how the dag is scheduled, right? I am not
>>>>>>
>>>>>> against
>>>>>>
>>>>>> those
>>>>>>
>>>>>> methods, but I think it is a very specific use case to actually
>>>>>>
>>>>>> override
>>>>>>
>>>>>> the property of the source. In general I would expect users to
>>>>>>
>>>>>> only
>>>>>>
>>>>>> call
>>>>>>
>>>>>> env.source(theSource), where the source tells if it is bounded or
>>>>>>
>>>>>> not. I
>>>>>>
>>>>>> would suggest considering following set of methods:
>>>>>>
>>>>>> // boundedness depends of source property, imo this should always
>>>>>>
>>>>>> be
>>>>>>
>>>>>> preferred
>>>>>>
>>>>>> DataStream<MyType> stream = env.source(theSource);
>>>>>>
>>>>>>
>>>>>> // always continous execution, whether bounded or unbounded source
>>>>>>
>>>>>> DataStream<MyType> boundedStream = env.continousSource(theSource);
>>>>>>
>>>>>> // imo this would make sense if the BoundedDataStream provides
>>>>>>
>>>>>> additional features unavailable for continous mode
>>>>>>
>>>>>> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
>>>>>>
>>>>>>
>>>>>> Best,
>>>>>>
>>>>>> Dawid
>>>>>>
>>>>>>
>>>>>> On 04/12/2019 11:25, Stephan Ewen wrote:
>>>>>>
>>>>>> Thanks, Becket, for updating this.
>>>>>>
>>>>>> I agree with moving the aspects you mentioned into separate FLIPs
>>>>>>
>>>>>> -
>>>>>>
>>>>>> this
>>>>>>
>>>>>> one way becoming unwieldy in size.
>>>>>>
>>>>>> +1 to the FLIP in its current state. Its a very detailed write-up,
>>>>>>
>>>>>> nicely
>>>>>>
>>>>>> done!
>>>>>>
>>>>>> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]
>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
>>>> [hidden email]>>
>>>>>>
>>>>>> <
>>>>>>
>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
>>>>>>
>>>>>> Hi all,
>>>>>>
>>>>>> Sorry for the long belated update. I have updated FLIP-27 wiki
>>>>>>
>>>>>> page
>>>>>>
>>>>>> with
>>>>>>
>>>>>> the latest proposals. Some noticeable changes include:
>>>>>> 1. A new generic communication mechanism between SplitEnumerator
>>>>>>
>>>>>> and
>>>>>>
>>>>>> SourceReader.
>>>>>> 2. Some detail API method signature changes.
>>>>>>
>>>>>> We left a few things out of this FLIP and will address them in
>>>>>>
>>>>>> separate
>>>>>>
>>>>>> FLIPs. Including:
>>>>>> 1. Per split event time.
>>>>>> 2. Event time alignment.
>>>>>> 3. Fine grained failover for SplitEnumerator failure.
>>>>>>
>>>>>> Please let us know if you have any question.
>>>>>>
>>>>>> Thanks,
>>>>>>
>>>>>> Jiangjie (Becket) Qin
>>>>>>
>>>>>> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]
>>> <mailto:
>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
>>>>>>
>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
>>>>>>
>>>>>> Hi  Łukasz!
>>>>>>
>>>>>> Becket and me are working hard on figuring out the last details
>>>>>>
>>>>>> and
>>>>>>
>>>>>> implementing the first PoC. We would update the FLIP hopefully
>>>>>>
>>>>>> next
>>>>>>
>>>>>> week.
>>>>>>
>>>>>> There is a fair chance that a first version of this will be in
>>>>>>
>>>>>> 1.10,
>>>>>>
>>>>>> but
>>>>>>
>>>>>> I
>>>>>>
>>>>>> think it will take another release to battle test it and migrate
>>>>>>
>>>>>> the
>>>>>>
>>>>>> connectors.
>>>>>>
>>>>>> Best,
>>>>>> Stephan
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <[hidden email]
>>>> <mailto:[hidden email]>
>>>>>>
>>>>>> <
>>>>>>
>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>
>>>>>> wrote:
>>>>>>
>>>>>> Hi,
>>>>>>
>>>>>> This proposal looks very promising for us. Do you have any plans
>>>>>>
>>>>>> in
>>>>>>
>>>>>> which
>>>>>>
>>>>>> Flink release it is going to be released? We are thinking on
>>>>>>
>>>>>> using a
>>>>>>
>>>>>> Data
>>>>>>
>>>>>> Set API for our future use cases but on the other hand Data Set
>>>>>>
>>>>>> API
>>>>>>
>>>>>> is
>>>>>>
>>>>>> going to be deprecated so using proposed bounded data streams
>>>>>>
>>>>>> solution
>>>>>>
>>>>>> could be more viable in the long term.
>>>>>>
>>>>>> Thanks,
>>>>>> Łukasz
>>>>>>
>>>>>> On 2019/10/01 15:48:03, Thomas Weise <[hidden email]
>> <mailto:
>>>> [hidden email]>> <[hidden email] <mailto:
>>>> [hidden email]>> <
>>>>>>
>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
>>>>>>
>>>>>> Thanks for putting together this proposal!
>>>>>>
>>>>>> I see that the "Per Split Event Time" and "Event Time Alignment"
>>>>>>
>>>>>> sections
>>>>>>
>>>>>> are still TBD.
>>>>>>
>>>>>> It would probably be good to flesh those out a bit before
>>>>>>
>>>>>> proceeding
>>>>>>
>>>>>> too
>>>>>>
>>>>>> far
>>>>>>
>>>>>> as the event time alignment will probably influence the
>>>>>>
>>>>>> interaction
>>>>>>
>>>>>> with
>>>>>>
>>>>>> the split reader, specifically ReaderStatus
>>>>>>
>>>>>> emitNext(SourceOutput<E>
>>>>>>
>>>>>> output).
>>>>>>
>>>>>> We currently have only one implementation for event time alignment
>>>>>>
>>>>>> in
>>>>>>
>>>>>> the
>>>>>>
>>>>>> Kinesis consumer. The synchronization in that case takes place as
>>>>>>
>>>>>> the
>>>>>>
>>>>>> last
>>>>>>
>>>>>> step before records are emitted downstream (RecordEmitter). With
>>>>>>
>>>>>> the
>>>>>>
>>>>>> currently proposed interfaces, the equivalent can be implemented
>>>>>>
>>>>>> in
>>>>>>
>>>>>> the
>>>>>>
>>>>>> reader loop, although note that in the Kinesis consumer the per
>>>>>>
>>>>>> shard
>>>>>>
>>>>>> threads push records.
>>>>>>
>>>>>> Synchronization has not been implemented for the Kafka consumer
>>>>>>
>>>>>> yet.
>>>>>>
>>>>>> https://issues.apache.org/jira/browse/FLINK-12675 <
>>>> https://issues.apache.org/jira/browse/FLINK-12675>
>>>>>>
>>>>>> When I looked at it, I realized that the implementation will look
>>>>>>
>>>>>> quite
>>>>>>
>>>>>> different
>>>>>> from Kinesis because it needs to take place in the pull part,
>>>>>>
>>>>>> where
>>>>>>
>>>>>> records
>>>>>>
>>>>>> are taken from the Kafka client. Due to the multiplexing it cannot
>>>>>>
>>>>>> be
>>>>>>
>>>>>> done
>>>>>>
>>>>>> by blocking the split thread like it currently works for Kinesis.
>>>>>>
>>>>>> Reading
>>>>>>
>>>>>> from individual Kafka partitions needs to be controlled via
>>>>>>
>>>>>> pause/resume
>>>>>>
>>>>>> on the Kafka client.
>>>>>>
>>>>>> To take on that responsibility the split thread would need to be
>>>>>>
>>>>>> aware
>>>>>>
>>>>>> of
>>>>>>
>>>>>> the
>>>>>> watermarks or at least whether it should or should not continue to
>>>>>>
>>>>>> consume
>>>>>>
>>>>>> a given split and this may require a different SourceReader or
>>>>>>
>>>>>> SourceOutput
>>>>>>
>>>>>> interface.
>>>>>>
>>>>>> Thanks,
>>>>>> Thomas
>>>>>>
>>>>>>
>>>>>> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email]
>> <mailto:
>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
>> <
>>>>>>
>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
>>>>>>
>>>>>> Hi Stephan,
>>>>>>
>>>>>> Thank you for feedback!
>>>>>> Will take a look at your branch before public discussing.
>>>>>>
>>>>>>
>>>>>> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]
>>>> <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]
>>>>
>>>>>>
>>>>>> <
>>>>>>
>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>
>>>>>> wrote:
>>>>>>
>>>>>> Hi Biao!
>>>>>>
>>>>>> Thanks for reviving this. I would like to join this discussion,
>>>>>>
>>>>>> but
>>>>>>
>>>>>> am
>>>>>>
>>>>>> quite occupied with the 1.9 release, so can we maybe pause this
>>>>>>
>>>>>> discussion
>>>>>>
>>>>>> for a week or so?
>>>>>>
>>>>>> In the meantime I can share some suggestion based on prior
>>>>>>
>>>>>> experiments:
>>>>>>
>>>>>> How to do watermarks / timestamp extractors in a simpler and more
>>>>>>
>>>>>> flexible
>>>>>>
>>>>>> way. I think that part is quite promising should be part of the
>>>>>>
>>>>>> new
>>>>>>
>>>>>> source
>>>>>>
>>>>>> interface.
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>
>>>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
>>>> <
>>>>
>>>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
>>>>>
>>>>>>
>>>>>>
>>>>
>>>
>> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
>>>> <
>>>>
>>>
>> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
>>>>>
>>>>>>
>>>>>> Some experiments on how to build the source reader and its
>>>>>>
>>>>>> library
>>>>>>
>>>>>> for
>>>>>>
>>>>>> common threading/split patterns:
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>
>>>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
>>>> <
>>>>
>>>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
>>>>>
>>>>>>
>>>>>> Best,
>>>>>> Stephan
>>>>>>
>>>>>>
>>>>>> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]
>>> <mailto:
>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
>> <
>>>>>>
>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>
>>>>>> wrote:
>>>>>>
>>>>>> Hi devs,
>>>>>>
>>>>>> Since 1.9 is nearly released, I think we could get back to
>>>>>>
>>>>>> FLIP-27.
>>>>>>
>>>>>> I
>>>>>>
>>>>>> believe it should be included in 1.10.
>>>>>>
>>>>>> There are so many things mentioned in document of FLIP-27. [1] I
>>>>>>
>>>>>> think
>>>>>>
>>>>>> we'd better discuss them separately. However the wiki is not a
>>>>>>
>>>>>> good
>>>>>>
>>>>>> place
>>>>>>
>>>>>> to discuss. I wrote google doc about SplitReader API which
>>>>>>
>>>>>> misses
>>>>>>
>>>>>> some
>>>>>>
>>>>>> details in the document. [2]
>>>>>>
>>>>>> 1.
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>
>>>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
>>>> <
>>>>
>>>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
>>>>>
>>>>>>
>>>>>> 2.
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>
>>>
>> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
>>>> <
>>>>
>>>
>> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
>>>>>
>>>>>>
>>>>>> CC Stephan, Aljoscha, Piotrek, Becket
>>>>>>
>>>>>>
>>>>>> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email]
>> <mailto:
>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
>> <
>>>>>>
>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>
>>>>>> wrote:
>>>>>>
>>>>>> Hi Steven,
>>>>>> Thank you for the feedback. Please take a look at the document
>>>>>>
>>>>>> FLIP-27
>>>>>>
>>>>>> <
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>
>>>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
>>>> <
>>>>
>>>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
>>>>>
>>>>>>
>>>>>> which
>>>>>>
>>>>>> is updated recently. A lot of details of enumerator were added
>>>>>>
>>>>>> in
>>>>>>
>>>>>> this
>>>>>>
>>>>>> document. I think it would help.
>>>>>>
>>>>>> Steven Wu <[hidden email] <mailto:[hidden email]>> <
>>>> [hidden email] <mailto:[hidden email]>> <
>>> [hidden email]
>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
>>>> [hidden email]>>
>>>>>>
>>>>>> 于2019年3月28日周四
>>>>>>
>>>>>> 下午12:52写道：
>>>>>>
>>>>>> This proposal mentioned that SplitEnumerator might run on the
>>>>>> JobManager or
>>>>>> in a single task on a TaskManager.
>>>>>>
>>>>>> if enumerator is a single task on a taskmanager, then the job
>>>>>>
>>>>>> DAG
>>>>>>
>>>>>> can
>>>>>>
>>>>>> never
>>>>>> been embarrassingly parallel anymore. That will nullify the
>>>>>>
>>>>>> leverage
>>>>>>
>>>>>> of
>>>>>>
>>>>>> fine-grained recovery for embarrassingly parallel jobs.
>>>>>>
>>>>>> It's not clear to me what's the implication of running
>>>>>>
>>>>>> enumerator
>>>>>>
>>>>>> on
>>>>>>
>>>>>> the
>>>>>>
>>>>>> jobmanager. So I will leave that out for now.
>>>>>>
>>>>>> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email]
>> <mailto:
>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
>> <
>>>>>>
>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>
>>>>>> wrote:
>>>>>>
>>>>>> Hi Stephan & Piotrek,
>>>>>>
>>>>>> Thank you for feedback.
>>>>>>
>>>>>> It seems that there are a lot of things to do in community.
>>>>>>
>>>>>> I
>>>>>>
>>>>>> am
>>>>>>
>>>>>> just
>>>>>>
>>>>>> afraid that this discussion may be forgotten since there so
>>>>>>
>>>>>> many
>>>>>>
>>>>>> proposals
>>>>>>
>>>>>> recently.
>>>>>> Anyway, wish to see the split topics soon :)
>>>>>>
>>>>>> Piotr Nowojski <[hidden email] <mailto:[hidden email]
>>>>
>>> <
>>>> [hidden email] <mailto:[hidden email]>> <
>>>> [hidden email] <mailto:[hidden email]>> <
>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>
>>>>>> 于2019年1月24日周四
>>>>>>
>>>>>> 下午8:21写道：
>>>>>>
>>>>>> Hi Biao!
>>>>>>
>>>>>> This discussion was stalled because of preparations for
>>>>>>
>>>>>> the
>>>>>>
>>>>>> open
>>>>>>
>>>>>> sourcing
>>>>>>
>>>>>> & merging Blink. I think before creating the tickets we
>>>>>>
>>>>>> should
>>>>>>
>>>>>> split this
>>>>>>
>>>>>> discussion into topics/areas outlined by Stephan and
>>>>>>
>>>>>> create
>>>>>>
>>>>>> Flips
>>>>>>
>>>>>> for
>>>>>>
>>>>>> that.
>>>>>>
>>>>>> I think there is no chance for this to be completed in
>>>>>>
>>>>>> couple
>>>>>>
>>>>>> of
>>>>>>
>>>>>> remaining
>>>>>>
>>>>>> weeks/1 month before 1.8 feature freeze, however it would
>>>>>>
>>>>>> be
>>>>>>
>>>>>> good
>>>>>>
>>>>>> to aim
>>>>>>
>>>>>> with those changes for 1.9.
>>>>>>
>>>>>> Piotrek
>>>>>>
>>>>>>
>>>>>> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email] <mailto:
>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
>> <
>>>>>>
>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>
>>>>>> wrote:
>>>>>>
>>>>>> Hi community,
>>>>>> The summary of Stephan makes a lot sense to me. It is
>>>>>>
>>>>>> much
>>>>>>
>>>>>> clearer
>>>>>>
>>>>>> indeed
>>>>>>
>>>>>> after splitting the complex topic into small ones.
>>>>>> I was wondering is there any detail plan for next step?
>>>>>>
>>>>>> If
>>>>>>
>>>>>> not,
>>>>>>
>>>>>> I
>>>>>>
>>>>>> would
>>>>>>
>>>>>> like to push this thing forward by creating some JIRA
>>>>>>
>>>>>> issues.
>>>>>>
>>>>>> Another question is that should version 1.8 include
>>>>>>
>>>>>> these
>>>>>>
>>>>>> features?
>>>>>>
>>>>>> Stephan Ewen <[hidden email] <mailto:[hidden email]>> <
>>>> [hidden email] <mailto:[hidden email]>> <[hidden email] <mailto:
>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
>>>> 于2018年12月1日周六
>>>>>>
>>>>>> 上午4:20写道：
>>>>>>
>>>>>> Thanks everyone for the lively discussion. Let me try
>>>>>>
>>>>>> to
>>>>>>
>>>>>> summarize
>>>>>>
>>>>>> where I
>>>>>>
>>>>>> see convergence in the discussion and open issues.
>>>>>> I'll try to group this by design aspect of the source.
>>>>>>
>>>>>> Please
>>>>>>
>>>>>> let me
>>>>>>
>>>>>> know
>>>>>>
>>>>>> if I got things wrong or missed something crucial here.
>>>>>>
>>>>>> For issues 1-3, if the below reflects the state of the
>>>>>>
>>>>>> discussion, I
>>>>>>
>>>>>> would
>>>>>>
>>>>>> try and update the FLIP in the next days.
>>>>>> For the remaining ones we need more discussion.
>>>>>>
>>>>>> I would suggest to fork each of these aspects into a
>>>>>>
>>>>>> separate
>>>>>>
>>>>>> mail
>>>>>>
>>>>>> thread,
>>>>>>
>>>>>> or will loose sight of the individual aspects.
>>>>>>
>>>>>> *(1) Separation of Split Enumerator and Split Reader*
>>>>>>
>>>>>> - All seem to agree this is a good thing
>>>>>> - Split Enumerator could in the end live on JobManager
>>>>>>
>>>>>> (and
>>>>>>
>>>>>> assign
>>>>>>
>>>>>> splits
>>>>>>
>>>>>> via RPC) or in a task (and assign splits via data
>>>>>>
>>>>>> streams)
>>>>>>
>>>>>> - this discussion is orthogonal and should come later,
>>>>>>
>>>>>> when
>>>>>>
>>>>>> the
>>>>>>
>>>>>> interface
>>>>>>
>>>>>> is agreed upon.
>>>>>>
>>>>>> *(2) Split Readers for one or more splits*
>>>>>>
>>>>>> - Discussion seems to agree that we need to support
>>>>>>
>>>>>> one
>>>>>>
>>>>>> reader
>>>>>>
>>>>>> that
>>>>>>
>>>>>> possibly handles multiple splits concurrently.
>>>>>> - The requirement comes from sources where one
>>>>>>
>>>>>> poll()-style
>>>>>>
>>>>>> call
>>>>>>
>>>>>> fetches
>>>>>>
>>>>>> data from different splits / partitions
>>>>>>    --> example sources that require that would be for
>>>>>>
>>>>>> example
>>>>>>
>>>>>> Kafka,
>>>>>>
>>>>>> Pravega, Pulsar
>>>>>>
>>>>>> - Could have one split reader per source, or multiple
>>>>>>
>>>>>> split
>>>>>>
>>>>>> readers
>>>>>>
>>>>>> that
>>>>>>
>>>>>> share the "poll()" function
>>>>>> - To not make it too complicated, we can start with
>>>>>>
>>>>>> thinking
>>>>>>
>>>>>> about
>>>>>>
>>>>>> one
>>>>>>
>>>>>> split reader for all splits initially and see if that
>>>>>>
>>>>>> covers
>>>>>>
>>>>>> all
>>>>>>
>>>>>> requirements
>>>>>>
>>>>>> *(3) Threading model of the Split Reader*
>>>>>>
>>>>>> - Most active part of the discussion ;-)
>>>>>>
>>>>>> - A non-blocking way for Flink's task code to interact
>>>>>>
>>>>>> with
>>>>>>
>>>>>> the
>>>>>>
>>>>>> source
>>>>>>
>>>>>> is
>>>>>>
>>>>>> needed in order to a task runtime code based on a
>>>>>> single-threaded/actor-style task design
>>>>>>    --> I personally am a big proponent of that, it will
>>>>>>
>>>>>> help
>>>>>>
>>>>>> with
>>>>>>
>>>>>> well-behaved checkpoints, efficiency, and simpler yet
>>>>>>
>>>>>> more
>>>>>>
>>>>>> robust
>>>>>>
>>>>>> runtime
>>>>>>
>>>>>> code
>>>>>>
>>>>>> - Users care about simple abstraction, so as a
>>>>>>
>>>>>> subclass
>>>>>>
>>>>>> of
>>>>>>
>>>>>> SplitReader
>>>>>>
>>>>>> (non-blocking / async) we need to have a
>>>>>>
>>>>>> BlockingSplitReader
>>>>>>
>>>>>> which
>>>>>>
>>>>>> will
>>>>>>
>>>>>> form the basis of most source implementations.
>>>>>>
>>>>>> BlockingSplitReader
>>>>>>
>>>>>> lets
>>>>>>
>>>>>> users do blocking simple poll() calls.
>>>>>> - The BlockingSplitReader would spawn a thread (or
>>>>>>
>>>>>> more)
>>>>>>
>>>>>> and
>>>>>>
>>>>>> the
>>>>>>
>>>>>> thread(s) can make blocking calls and hand over data
>>>>>>
>>>>>> buffers
>>>>>>
>>>>>> via
>>>>>>
>>>>>> a
>>>>>>
>>>>>> blocking
>>>>>>
>>>>>> queue
>>>>>> - This should allow us to cover both, a fully async
>>>>>>
>>>>>> runtime,
>>>>>>
>>>>>> and a
>>>>>>
>>>>>> simple
>>>>>>
>>>>>> blocking interface for users.
>>>>>> - This is actually very similar to how the Kafka
>>>>>>
>>>>>> connectors
>>>>>>
>>>>>> work.
>>>>>>
>>>>>> Kafka
>>>>>>
>>>>>> 9+ with one thread, Kafka 8 with multiple threads
>>>>>>
>>>>>> - On the base SplitReader (the async one), the
>>>>>>
>>>>>> non-blocking
>>>>>>
>>>>>> method
>>>>>>
>>>>>> that
>>>>>>
>>>>>> gets the next chunk of data would signal data
>>>>>>
>>>>>> availability
>>>>>>
>>>>>> via
>>>>>>
>>>>>> a
>>>>>>
>>>>>> CompletableFuture, because that gives the best
>>>>>>
>>>>>> flexibility
>>>>>>
>>>>>> (can
>>>>>>
>>>>>> await
>>>>>>
>>>>>> completion or register notification handlers).
>>>>>> - The source task would register a "thenHandle()" (or
>>>>>>
>>>>>> similar)
>>>>>>
>>>>>> on the
>>>>>>
>>>>>> future to put a "take next data" task into the
>>>>>>
>>>>>> actor-style
>>>>>>
>>>>>> mailbox
>>>>>>
>>>>>> *(4) Split Enumeration and Assignment*
>>>>>>
>>>>>> - Splits may be generated lazily, both in cases where
>>>>>>
>>>>>> there
>>>>>>
>>>>>> is a
>>>>>>
>>>>>> limited
>>>>>>
>>>>>> number of splits (but very many), or splits are
>>>>>>
>>>>>> discovered
>>>>>>
>>>>>> over
>>>>>>
>>>>>> time
>>>>>>
>>>>>> - Assignment should also be lazy, to get better load
>>>>>>
>>>>>> balancing
>>>>>>
>>>>>> - Assignment needs support locality preferences
>>>>>>
>>>>>> - Possible design based on discussion so far:
>>>>>>
>>>>>>    --> SplitReader has a method "addSplits(SplitT...)"
>>>>>>
>>>>>> to
>>>>>>
>>>>>> add
>>>>>>
>>>>>> one or
>>>>>>
>>>>>> more
>>>>>>
>>>>>> splits. Some split readers might assume they have only
>>>>>>
>>>>>> one
>>>>>>
>>>>>> split
>>>>>>
>>>>>> ever,
>>>>>>
>>>>>> concurrently, others assume multiple splits. (Note:
>>>>>>
>>>>>> idea
>>>>>>
>>>>>> behind
>>>>>>
>>>>>> being
>>>>>>
>>>>>> able
>>>>>>
>>>>>> to add multiple splits at the same time is to ease
>>>>>>
>>>>>> startup
>>>>>>
>>>>>> where
>>>>>>
>>>>>> multiple
>>>>>>
>>>>>> splits may be assigned instantly.)
>>>>>>    --> SplitReader has a context object on which it can
>>>>>>
>>>>>> call
>>>>>>
>>>>>> indicate
>>>>>>
>>>>>> when
>>>>>>
>>>>>> splits are completed. The enumerator gets that
>>>>>>
>>>>>> notification and
>>>>>>
>>>>>> can
>>>>>>
>>>>>> use
>>>>>>
>>>>>> to
>>>>>>
>>>>>> decide when to assign new splits. This should help both
>>>>>>
>>>>>> in
>>>>>>
>>>>>> cases
>>>>>>
>>>>>> of
>>>>>>
>>>>>> sources
>>>>>>
>>>>>> that take splits lazily (file readers) and in case the
>>>>>>
>>>>>> source
>>>>>>
>>>>>> needs to
>>>>>>
>>>>>> preserve a partial order between splits (Kinesis,
>>>>>>
>>>>>> Pravega,
>>>>>>
>>>>>> Pulsar may
>>>>>>
>>>>>> need
>>>>>>
>>>>>> that).
>>>>>>    --> SplitEnumerator gets notification when
>>>>>>
>>>>>> SplitReaders
>>>>>>
>>>>>> start
>>>>>>
>>>>>> and
>>>>>>
>>>>>> when
>>>>>>
>>>>>> they finish splits. They can decide at that moment to
>>>>>>
>>>>>> push
>>>>>>
>>>>>> more
>>>>>>
>>>>>> splits
>>>>>>
>>>>>> to
>>>>>>
>>>>>> that reader
>>>>>>    --> The SplitEnumerator should probably be aware of
>>>>>>
>>>>>> the
>>>>>>
>>>>>> source
>>>>>>
>>>>>> parallelism, to build its initial distribution.
>>>>>>
>>>>>> - Open question: Should the source expose something
>>>>>>
>>>>>> like
>>>>>>
>>>>>> "host
>>>>>>
>>>>>> preferences", so that yarn/mesos/k8s can take this into
>>>>>>
>>>>>> account
>>>>>>
>>>>>> when
>>>>>>
>>>>>> selecting a node to start a TM on?
>>>>>>
>>>>>> *(5) Watermarks and event time alignment*
>>>>>>
>>>>>> - Watermark generation, as well as idleness, needs to
>>>>>>
>>>>>> be
>>>>>>
>>>>>> per
>>>>>>
>>>>>> split
>>>>>>
>>>>>> (like
>>>>>>
>>>>>> currently in the Kafka Source, per partition)
>>>>>> - It is desirable to support optional
>>>>>>
>>>>>> event-time-alignment,
>>>>>>
>>>>>> meaning
>>>>>>
>>>>>> that
>>>>>>
>>>>>> splits that are ahead are back-pressured or temporarily
>>>>>>
>>>>>> unsubscribed
>>>>>>
>>>>>> - I think i would be desirable to encapsulate
>>>>>>
>>>>>> watermark
>>>>>>
>>>>>> generation
>>>>>>
>>>>>> logic
>>>>>>
>>>>>> in watermark generators, for a separation of concerns.
>>>>>>
>>>>>> The
>>>>>>
>>>>>> watermark
>>>>>>
>>>>>> generators should run per split.
>>>>>> - Using watermark generators would also help with
>>>>>>
>>>>>> another
>>>>>>
>>>>>> problem of
>>>>>>
>>>>>> the
>>>>>>
>>>>>> suggested interface, namely supporting non-periodic
>>>>>>
>>>>>> watermarks
>>>>>>
>>>>>> efficiently.
>>>>>>
>>>>>> - Need a way to "dispatch" next record to different
>>>>>>
>>>>>> watermark
>>>>>>
>>>>>> generators
>>>>>>
>>>>>> - Need a way to tell SplitReader to "suspend" a split
>>>>>>
>>>>>> until a
>>>>>>
>>>>>> certain
>>>>>>
>>>>>> watermark is reached (event time backpressure)
>>>>>> - This would in fact be not needed (and thus simpler)
>>>>>>
>>>>>> if
>>>>>>
>>>>>> we
>>>>>>
>>>>>> had
>>>>>>
>>>>>> a
>>>>>>
>>>>>> SplitReader per split and may be a reason to re-open
>>>>>>
>>>>>> that
>>>>>>
>>>>>> discussion
>>>>>>
>>>>>> *(6) Watermarks across splits and in the Split
>>>>>>
>>>>>> Enumerator*
>>>>>>
>>>>>> - The split enumerator may need some watermark
>>>>>>
>>>>>> awareness,
>>>>>>
>>>>>> which
>>>>>>
>>>>>> should
>>>>>>
>>>>>> be
>>>>>>
>>>>>> purely based on split metadata (like create timestamp
>>>>>>
>>>>>> of
>>>>>>
>>>>>> file
>>>>>>
>>>>>> splits)
>>>>>>
>>>>>> - If there are still more splits with overlapping
>>>>>>
>>>>>> event
>>>>>>
>>>>>> time
>>>>>>
>>>>>> range
>>>>>>
>>>>>> for
>>>>>>
>>>>>> a
>>>>>>
>>>>>> split reader, then that split reader should not advance
>>>>>>
>>>>>> the
>>>>>>
>>>>>> watermark
>>>>>>
>>>>>> within the split beyond the overlap boundary. Otherwise
>>>>>>
>>>>>> future
>>>>>>
>>>>>> splits
>>>>>>
>>>>>> will
>>>>>>
>>>>>> produce late data.
>>>>>>
>>>>>> - One way to approach this could be that the split
>>>>>>
>>>>>> enumerator
>>>>>>
>>>>>> may
>>>>>>
>>>>>> send
>>>>>>
>>>>>> watermarks to the readers, and the readers cannot emit
>>>>>>
>>>>>> watermarks
>>>>>>
>>>>>> beyond
>>>>>>
>>>>>> that received watermark.
>>>>>> - Many split enumerators would simply immediately send
>>>>>>
>>>>>> Long.MAX
>>>>>>
>>>>>> out
>>>>>>
>>>>>> and
>>>>>>
>>>>>> leave the progress purely to the split readers.
>>>>>>
>>>>>> - For event-time alignment / split back pressure, this
>>>>>>
>>>>>> begs
>>>>>>
>>>>>> the
>>>>>>
>>>>>> question
>>>>>>
>>>>>> how we can avoid deadlocks that may arise when splits
>>>>>>
>>>>>> are
>>>>>>
>>>>>> suspended
>>>>>>
>>>>>> for
>>>>>>
>>>>>> event time back pressure,
>>>>>>
>>>>>> *(7) Batch and streaming Unification*
>>>>>>
>>>>>> - Functionality wise, the above design should support
>>>>>>
>>>>>> both
>>>>>>
>>>>>> - Batch often (mostly) does not care about reading "in
>>>>>>
>>>>>> order"
>>>>>>
>>>>>> and
>>>>>>
>>>>>> generating watermarks
>>>>>>    --> Might use different enumerator logic that is
>>>>>>
>>>>>> more
>>>>>>
>>>>>> locality
>>>>>>
>>>>>> aware
>>>>>>
>>>>>> and ignores event time order
>>>>>>    --> Does not generate watermarks
>>>>>> - Would be great if bounded sources could be
>>>>>>
>>>>>> identified
>>>>>>
>>>>>> at
>>>>>>
>>>>>> compile
>>>>>>
>>>>>> time,
>>>>>>
>>>>>> so that "env.addBoundedSource(...)" is type safe and
>>>>>>
>>>>>> can
>>>>>>
>>>>>> return a
>>>>>>
>>>>>> "BoundedDataStream".
>>>>>> - Possible to defer this discussion until later
>>>>>>
>>>>>> *Miscellaneous Comments*
>>>>>>
>>>>>> - Should the source have a TypeInformation for the
>>>>>>
>>>>>> produced
>>>>>>
>>>>>> type,
>>>>>>
>>>>>> instead
>>>>>>
>>>>>> of a serializer? We need a type information in the
>>>>>>
>>>>>> stream
>>>>>>
>>>>>> anyways, and
>>>>>>
>>>>>> can
>>>>>>
>>>>>> derive the serializer from that. Plus, creating the
>>>>>>
>>>>>> serializer
>>>>>>
>>>>>> should
>>>>>>
>>>>>> respect the ExecutionConfig.
>>>>>>
>>>>>> - The TypeSerializer interface is very powerful but
>>>>>>
>>>>>> also
>>>>>>
>>>>>> not
>>>>>>
>>>>>> easy to
>>>>>>
>>>>>> implement. Its purpose is to handle data super
>>>>>>
>>>>>> efficiently,
>>>>>>
>>>>>> support
>>>>>>
>>>>>> flexible ways of evolution, etc.
>>>>>> For metadata I would suggest to look at the
>>>>>>
>>>>>> SimpleVersionedSerializer
>>>>>>
>>>>>> instead, which is used for example for checkpoint
>>>>>>
>>>>>> master
>>>>>>
>>>>>> hooks,
>>>>>>
>>>>>> or for
>>>>>>
>>>>>> the
>>>>>>
>>>>>> streaming file sink. I think that is is a good match
>>>>>>
>>>>>> for
>>>>>>
>>>>>> cases
>>>>>>
>>>>>> where
>>>>>>
>>>>>> we
>>>>>>
>>>>>> do
>>>>>>
>>>>>> not need more than ser/deser (no copy, etc.) and don't
>>>>>>
>>>>>> need to
>>>>>>
>>>>>> push
>>>>>>
>>>>>> versioning out of the serialization paths for best
>>>>>>
>>>>>> performance
>>>>>>
>>>>>> (as in
>>>>>>
>>>>>> the
>>>>>>
>>>>>> TypeSerializer)
>>>>>>
>>>>>>
>>>>>> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
>>>>>>
>>>>>> [hidden email]>
>>>>>>
>>>>>> wrote:
>>>>>>
>>>>>>
>>>>>> Hi Biao,
>>>>>>
>>>>>> Thanks for the answer!
>>>>>>
>>>>>> So given the multi-threaded readers, now we have as
>>>>>>
>>>>>> open
>>>>>>
>>>>>> questions:
>>>>>>
>>>>>> 1) How do we let the checkpoints pass through our
>>>>>>
>>>>>> multi-threaded
>>>>>>
>>>>>> reader
>>>>>>
>>>>>> operator?
>>>>>>
>>>>>> 2) Do we have separate reader and source operators or
>>>>>>
>>>>>> not? In
>>>>>>
>>>>>> the
>>>>>>
>>>>>> strategy
>>>>>>
>>>>>> that has a separate source, the source operator has a
>>>>>>
>>>>>> parallelism of
>>>>>>
>>>>>> 1
>>>>>>
>>>>>> and
>>>>>>
>>>>>> is responsible for split recovery only.
>>>>>>
>>>>>> For the first one, given also the constraints
>>>>>>
>>>>>> (blocking,
>>>>>>
>>>>>> finite
>>>>>>
>>>>>> queues,
>>>>>>
>>>>>> etc), I do not have an answer yet.
>>>>>>
>>>>>> For the 2nd, I think that we should go with separate
>>>>>>
>>>>>> operators
>>>>>>
>>>>>> for
>>>>>>
>>>>>> the
>>>>>>
>>>>>> source and the readers, for the following reasons:
>>>>>>
>>>>>> 1) This is more aligned with a potential future
>>>>>>
>>>>>> improvement
>>>>>>
>>>>>> where the
>>>>>>
>>>>>> split
>>>>>>
>>>>>> discovery becomes a responsibility of the JobManager
>>>>>>
>>>>>> and
>>>>>>
>>>>>> readers are
>>>>>>
>>>>>> pooling more work from the JM.
>>>>>>
>>>>>> 2) The source is going to be the "single point of
>>>>>>
>>>>>> truth".
>>>>>>
>>>>>> It
>>>>>>
>>>>>> will
>>>>>>
>>>>>> know
>>>>>>
>>>>>> what
>>>>>>
>>>>>> has been processed and what not. If the source and the
>>>>>>
>>>>>> readers
>>>>>>
>>>>>> are a
>>>>>>
>>>>>> single
>>>>>>
>>>>>> operator with parallelism > 1, or in general, if the
>>>>>>
>>>>>> split
>>>>>>
>>>>>> discovery
>>>>>>
>>>>>> is
>>>>>>
>>>>>> done by each task individually, then:
>>>>>>   i) we have to have a deterministic scheme for each
>>>>>>
>>>>>> reader to
>>>>>>
>>>>>> assign
>>>>>>
>>>>>> splits to itself (e.g. mod subtaskId). This is not
>>>>>>
>>>>>> necessarily
>>>>>>
>>>>>> trivial
>>>>>>
>>>>>> for
>>>>>>
>>>>>> all sources.
>>>>>>   ii) each reader would have to keep a copy of all its
>>>>>>
>>>>>> processed
>>>>>>
>>>>>> slpits
>>>>>>
>>>>>>   iii) the state has to be a union state with a
>>>>>>
>>>>>> non-trivial
>>>>>>
>>>>>> merging
>>>>>>
>>>>>> logic
>>>>>>
>>>>>> in order to support rescaling.
>>>>>>
>>>>>> Two additional points that you raised above:
>>>>>>
>>>>>> i) The point that you raised that we need to keep all
>>>>>>
>>>>>> splits
>>>>>>
>>>>>> (processed
>>>>>>
>>>>>> and
>>>>>>
>>>>>> not-processed) I think is a bit of a strong
>>>>>>
>>>>>> requirement.
>>>>>>
>>>>>> This
>>>>>>
>>>>>> would
>>>>>>
>>>>>> imply
>>>>>>
>>>>>> that for infinite sources the state will grow
>>>>>>
>>>>>> indefinitely.
>>>>>>
>>>>>> This is
>>>>>>
>>>>>> problem
>>>>>>
>>>>>> is even more pronounced if we do not have a single
>>>>>>
>>>>>> source
>>>>>>
>>>>>> that
>>>>>>
>>>>>> assigns
>>>>>>
>>>>>> splits to readers, as each reader will have its own
>>>>>>
>>>>>> copy
>>>>>>
>>>>>> of
>>>>>>
>>>>>> the
>>>>>>
>>>>>> state.
>>>>>>
>>>>>> ii) it is true that for finite sources we need to
>>>>>>
>>>>>> somehow
>>>>>>
>>>>>> not
>>>>>>
>>>>>> close
>>>>>>
>>>>>> the
>>>>>>
>>>>>> readers when the source/split discoverer finishes. The
>>>>>> ContinuousFileReaderOperator has a work-around for
>>>>>>
>>>>>> that.
>>>>>>
>>>>>> It is
>>>>>>
>>>>>> not
>>>>>>
>>>>>> elegant,
>>>>>>
>>>>>> and checkpoints are not emitted after closing the
>>>>>>
>>>>>> source,
>>>>>>
>>>>>> but
>>>>>>
>>>>>> this, I
>>>>>>
>>>>>> believe, is a bigger problem which requires more
>>>>>>
>>>>>> changes
>>>>>>
>>>>>> than
>>>>>>
>>>>>> just
>>>>>>
>>>>>> refactoring the source interface.
>>>>>>
>>>>>> Cheers,
>>>>>> Kostas
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>> --
>>>>>> Best, Jingsong Lee
>>>>
>>>>
>>>
>>
>>
>> --
>> Best, Jingsong Lee
>>
>

[Becket Qin]

Hi folks,

Thanks for the comments. I am convinced that the Source API should not take
boundedness as a parameter after it is constructed. What Timo and Dawid
suggested sounds a reasonable solution to me. So the Source API would
become:

Source {
    Boundedness getBoundedness();
}

Assuming the above Source API, in addition to the two options mentioned in
earlier emails, I am thinking of another option:

*Option 3:*
// MySource must be unbounded, otherwise throws exception.
DataStream<Type> dataStream = env.source(mySource);

// MySource must be bounded, otherwise throws exception.
BoundedDataStream<Type> boundedDataStream = env.boundedSource(mySource);

The pros of this API are:
   a) It fits the requirements from Table / SQL well.
   b) DataStream users still have type safety (option 2 only has partial
type safety).
   c) Cristal clear boundedness from the API which makes DataStream join /
connect easy to reason about.
The caveats I see,
   a) It is inconsistent with Table since Table has one unified interface.
   b) No streaming mode for bounded source.

@Stephan Ewen <[hidden email]> @Aljoscha Krettek
<[hidden email]> what do you think of the approach?


Orthogonal to the above API, I am wondering whether boundedness is the only
dimension needed to describe the characteristic of the Source behavior. We
may also need to have another dimension of *record order*.

For example, when a file source is reading from a directory with bounded
records, it may have two ways to read.
1. Read files in parallel.
2. Read files in the chronological order.
In both cases, the file source is a Bounded Source. However, the processing
requirement for downstream may be different. In the first case, the
record processing and result emitting order does not matter, e.g. word
count. In the second case, the records may have to be processed in the
order they were read, e.g. change log processing.

If the Source only has a getBoundedness() method, the downstream processors
would not know whether the records emitted from the Source should be
processed in order or not. So combining the boundedness and record order,
we will have four scenarios:

*Bounded-StrictOrder*:     A segment of change log.
*Bounded-Random*:          Batch Word Count.
*Unbounded-StrictOrder*: An infinite change log.
*Unbounded-Random*:     Streaming Word Count.

Option 2 mentioned in the previous email was kind of trying to handle the
Bounded-StrictOrder case by creating a DataStream from a bounded source,
which actually does not work.
It looks that we do not have strict order support in some operators at this
point, e.g. join. But we may still want to add the semantic to the Source
first so later on we don't need to change all the source implementations,
especially given that many of them will be implemented by 3rd party.

Given that, we need another dimension of *Record Order* in the Source. More
specifically, the API would become:

Source {
    Boundedness getBoundedness();
    RecordOrder getRecordOrder();
}

public enum RecordOrder {
    /** The record in the DataStream must be processed in its strict order
for correctness. */
    STRICT,
    /** The record in the DataStream can be processed in arbitrary order. */
    RANDOM;
}

Any thoughts?

Thanks,

Jiangjie (Becket) Qin

On Tue, Dec 17, 2019 at 3:44 PM Timo Walther <[hidden email]> wrote:

> Hi Becket,
>
> I completely agree with Dawid's suggestion. The information about the
> boundedness should come out of the source. Because most of the streaming
> sources can be made bounded based on some connector specific criterion.
> In Kafka, it would be an end offset or end timestamp but in any case
> having just a env.boundedSource() is not enough because parameters for
> making the source bounded are missing.
>
> I suggest to have a simple `isBounded(): Boolean` flag in every source
> that might be influenced by a connector builder as Dawid mentioned.
>
> For type safety during programming, we can still go with *Final state
> 1*. By having a env.source() vs env.boundedSource(). The latter would
> just enforce that the boolean flag is set to `true` and could make
> bounded operations available (if we need that actually).
>
> However, I don't think that we should start making a unified Table API
> ununified again. Boundedness is an optimization property. Every bounded
> operation can also executed in an unbounded way using updates/retraction
> or watermarks.
>
> Regards,
> Timo
>
>
> On 15.12.19 14:22, Becket Qin wrote:
> > Hi Dawid and Jark,
> >
> > I think the discussion ultimately boils down to the question that which
> one
> > of the following two final states do we want? Once we make this decision,
> > everything else can be naturally derived.
> >
> > *Final state 1*: Separate API for bounded / unbounded DataStream & Table.
> > That means any code users write will be valid at the point when they
> write
> > the code. This is similar to having type safety check at programming
> time.
> > For example,
> >
> > BoundedDataStream extends DataStream {
> > // Operations only available for bounded data.
> > BoundedDataStream sort(...);
> >
> > // Interaction with another BoundedStream returns a Bounded stream.
> > BoundedJoinedDataStream join(BoundedDataStream other)
> >
> > // Interaction with another unbounded stream returns an unbounded stream.
> > JoinedDataStream join(DataStream other)
> > }
> >
> > BoundedTable extends Table {
> >    // Bounded only operation.
> > BoundedTable sort(...);
> >
> > // Interaction with another BoundedTable returns a BoundedTable.
> > BoundedTable join(BoundedTable other)
> >
> > // Interaction with another unbounded table returns an unbounded table.
> > Table join(Table other)
> > }
> >
> > *Final state 2*: One unified API for bounded / unbounded DataStream /
> > Table.
> > That unified API may throw exception at DAG compilation time if an
> invalid
> > operation is tried. This is what Table API currently follows.
> >
> > DataStream {
> > // Throws exception if the DataStream is unbounded.
> > DataStream sort();
> > // Get boundedness.
> > Boundedness getBoundedness();
> > }
> >
> > Table {
> > // Throws exception if the table has infinite rows.
> > Table orderBy();
> >
> > // Get boundedness.
> > Boundedness getBoundedness();
> > }
> >
> >>From what I understand, there is no consensus so far on this decision
> yet.
> > Whichever final state we choose, we need to make it consistent across the
> > entire project. We should avoid the case that Table follows one final
> state
> > while DataStream follows another. Some arguments I am aware of from both
> > sides so far are following:
> >
> > Arguments for final state 1:
> > 1a) Clean API with method safety check at programming time.
> > 1b) (Counter 2b) Although SQL does not have programming time error
> check, SQL
> > is not really a "programming language" per se. So SQL can be different
> from
> > Table and DataStream.
> > 1c)  Although final state 2 seems making it easier for SQL to use given
> it
> > is more "config based" than "parameter based", final state 1 can probably
> > also meet what SQL wants by wrapping the Source in TableSource /
> > TableSourceFactory API if needed.
> >
> > Arguments for final state 2:
> > 2a) The Source API itself seems already sort of following the unified API
> > pattern.
> > 2b) There is no "programming time" method error check in SQL case, so we
> > cannot really achieve final state 1 across the board.
> > 2c) It is an easier path given our current status, i.e. Table is already
> > following final state 2.
> > 2d) Users can always explicitly check the boundedness if they want to.
> >
> > As I mentioned earlier, my initial thought was also to have a
> > "configuration based" Source rather than a "parameter based" Source. So
> it
> > is completely possible that I missed some important consideration or
> design
> > principles that we want to enforce for the project. It would be good
> > if @Stephan
> > Ewen <[hidden email]> and @Aljoscha Krettek <
> [hidden email]> can
> > also provide more thoughts on this.
> >
> >
> > Re: Jingsong
> >
> > As you said, there are some batched system source, like parquet/orc
> source.
> >> Could we have the batch emit interface to improve performance? The
> queue of
> >> per record may cause performance degradation.
> >
> >
> > The current interface does not necessarily cause performance problem in a
> > multi-threading case. In fact, the base implementation allows
> SplitReaders
> > to add a batch <E> of records<T> to the records queue<E>, so each element
> > in the records queue would be a batch <E>. In this case, when the main
> > thread polls records, it will take a batch <E> of records <T> from the
> > shared records queue and process the records <T> in a batch manner.
> >
> > Thanks,
> >
> > Jiangjie (Becket) Qin
> >
> > On Thu, Dec 12, 2019 at 1:29 PM Jingsong Li <[hidden email]>
> wrote:
> >
> >> Hi Becket,
> >>
> >> I also have some performance concerns too.
> >>
> >> If I understand correctly, SourceOutput will emit data per record into
> the
> >> queue? I'm worried about the multithreading performance of this queue.
> >>
> >>> One example is some batched messaging systems which only have an offset
> >> for the entire batch instead of individual messages in the batch.
> >>
> >> As you said, there are some batched system source, like parquet/orc
> source.
> >> Could we have the batch emit interface to improve performance? The
> queue of
> >> per record may cause performance degradation.
> >>
> >> Best,
> >> Jingsong Lee
> >>
> >> On Thu, Dec 12, 2019 at 9:15 AM Jark Wu <[hidden email]> wrote:
> >>
> >>> Hi Becket,
> >>>
> >>> I think Dawid explained things clearly and makes a lot of sense.
> >>> I'm also in favor of #2, because #1 doesn't work for our future unified
> >>> envrionment.
> >>>
> >>> You can see the vision in this documentation [1]. In the future, we
> would
> >>> like to
> >>> drop the global streaming/batch mode in SQL (i.e.
> >>> EnvironmentSettings#inStreamingMode/inBatchMode).
> >>> A source is bounded or unbounded once defined, so queries can be
> inferred
> >>> from source to run
> >>> in streaming or batch or hybrid mode. However, in #1, we will lose this
> >>> ability because the framework
> >>> doesn't know whether the source is bounded or unbounded.
> >>>
> >>> Best,
> >>> Jark
> >>>
> >>>
> >>> [1]:
> >>>
> >>>
> >>
> https://docs.google.com/document/d/1yrKXEIRATfxHJJ0K3t6wUgXAtZq8D-XgvEnvl2uUcr0/edit#heading=h.v4ib17buma1p
> >>>
> >>> On Wed, 11 Dec 2019 at 20:52, Piotr Nowojski <[hidden email]>
> >> wrote:
> >>>
> >>>> Hi,
> >>>>
> >>>> Regarding the:
> >>>>
> >>>> Collection<E> getNextRecords()
> >>>>
> >>>> I’m pretty sure such design would unfortunately impact the performance
> >>>> (accessing and potentially creating the collection on the hot path).
> >>>>
> >>>> Also the
> >>>>
> >>>> InputStatus emitNext(DataOutput<T> output) throws Exception;
> >>>> or
> >>>> Status pollNext(SourceOutput<T> sourceOutput) throws Exception;
> >>>>
> >>>> Gives us some opportunities in the future, to allow Source hot looping
> >>>> inside, until it receives some signal “please exit because of some
> >>> reasons”
> >>>> (output collector could return such hint upon collecting the result).
> >> But
> >>>> that’s another topic outside of this FLIP’s scope.
> >>>>
> >>>> Piotrek
> >>>>
> >>>>> On 11 Dec 2019, at 10:41, Till Rohrmann <[hidden email]>
> >> wrote:
> >>>>>
> >>>>> Hi Becket,
> >>>>>
> >>>>> quick clarification from my side because I think you misunderstood my
> >>>>> question. I did not suggest to let the SourceReader return only a
> >>> single
> >>>>> record at a time when calling getNextRecords. As the return type
> >>>> indicates,
> >>>>> the method can return an arbitrary number of records.
> >>>>>
> >>>>> Cheers,
> >>>>> Till
> >>>>>
> >>>>> On Wed, Dec 11, 2019 at 10:13 AM Dawid Wysakowicz <
> >>>> [hidden email] <mailto:[hidden email]>>
> >>>>> wrote:
> >>>>>
> >>>>>> Hi Becket,
> >>>>>>
> >>>>>> Issue #1 - Design of Source interface
> >>>>>>
> >>>>>> I mentioned the lack of a method like
> >>>> Source#createEnumerator(Boundedness
> >>>>>> boundedness, SplitEnumeratorContext context), because without the
> >>>> current
> >>>>>> proposal is not complete/does not work.
> >>>>>>
> >>>>>> If we say that boundedness is an intrinsic property of a source imo
> >> we
> >>>>>> don't need the Source#createEnumerator(Boundedness boundedness,
> >>>>>> SplitEnumeratorContext context) method.
> >>>>>>
> >>>>>> Assuming a source from my previous example:
> >>>>>>
> >>>>>> Source source = KafkaSource.builder()
> >>>>>>   ...
> >>>>>>   .untilTimestamp(...)
> >>>>>>   .build()
> >>>>>>
> >>>>>> Would the enumerator differ if created like
> >>>>>> source.createEnumerator(CONTINUOUS_UNBOUNDED, ...) vs source
> >>>>>> .createEnumerator(BOUNDED, ...)? I know I am repeating myself, but
> >>> this
> >>>> is
> >>>>>> the part that my opinion differ the most from the current proposal.
> >> I
> >>>>>> really think it should always be the source that tells if it is
> >>> bounded
> >>>> or
> >>>>>> not. In the current proposal methods continousSource/boundedSource
> >>>> somewhat
> >>>>>> reconfigure the source, which I think is misleading.
> >>>>>>
> >>>>>> I think a call like:
> >>>>>>
> >>>>>> Source source = KafkaSource.builder()
> >>>>>>   ...
> >>>>>>   .readContinously() / readUntilLatestOffset() / readUntilTimestamp
> /
> >>>> readUntilOffsets / ...
> >>>>>>   .build()
> >>>>>>
> >>>>>> is way cleaner (and expressive) than
> >>>>>>
> >>>>>> Source source = KafkaSource.builder()
> >>>>>>   ...
> >>>>>>   .build()
> >>>>>>
> >>>>>>
> >>>>>> env.continousSource(source) // which actually underneath would call
> >>>> createEnumerator(CONTINUOUS, ctx) which would be equivalent to
> >>>> source.readContinously().createEnumerator(ctx)
> >>>>>> // or
> >>>>>> env.boundedSource(source) // which actually underneath would call
> >>>> createEnumerator(BOUNDED, ctx) which would be equivalent to
> >>>> source.readUntilLatestOffset().createEnumerator(ctx)
> >>>>>>
> >>>>>>
> >>>>>> Sorry for the comparison, but to me it seems there is too much magic
> >>>>>> happening underneath those two calls.
> >>>>>>
> >>>>>> I really believe the Source interface should have getBoundedness
> >>> method
> >>>>>> instead of (supportBoundedness) + createEnumerator(Boundedness, ...)
> >>>>>>
> >>>>>>
> >>>>>> Issue #2 - Design of
> >>>>>> ExecutionEnvironment#source()/continuousSource()/boundedSource()
> >>>>>>
> >>>>>> As you might have guessed I am slightly in favor of option #2
> >>> modified.
> >>>>>> Yes I am aware every step of the dag would have to be able to say if
> >>> it
> >>>> is
> >>>>>> bounded or not. I have a feeling it would be easier to express cross
> >>>>>> bounded/unbounded operations, but I must admit I have not thought it
> >>>>>> through thoroughly, In the spirit of batch is just a special case of
> >>>>>> streaming I thought BoundedStream would extend from DataStream.
> >>> Correct
> >>>> me
> >>>>>> if I am wrong. In such a setup the cross bounded/unbounded operation
> >>>> could
> >>>>>> be expressed quite easily I think:
> >>>>>>
> >>>>>> DataStream {
> >>>>>>   DataStream join(DataStream, ...); // we could not really tell if
> >> the
> >>>> result is bounded or not, but because bounded stream is a special case
> >> of
> >>>> unbounded the API object is correct, irrespective if the left or right
> >>> side
> >>>> of the join is bounded
> >>>>>> }
> >>>>>>
> >>>>>> BoundedStream extends DataStream {
> >>>>>>   BoundedStream join(BoundedStream, ...); // only if both sides are
> >>>> bounded the result can be bounded as well. However we do have access
> to
> >>> the
> >>>> DataStream#join here, so you can still join with a DataStream
> >>>>>> }
> >>>>>>
> >>>>>>
> >>>>>> On the other hand I also see benefits of two completely disjointed
> >>> APIs,
> >>>>>> as we could prohibit some streaming calls in the bounded API. I
> >> can't
> >>>> think
> >>>>>> of any unbounded operators that could not be implemented for bounded
> >>>> stream.
> >>>>>>
> >>>>>> Besides I think we both agree we don't like the method:
> >>>>>>
> >>>>>> DataStream boundedStream(Source)
> >>>>>>
> >>>>>> suggested in the current state of the FLIP. Do we ? :)
> >>>>>>
> >>>>>> Best,
> >>>>>>
> >>>>>> Dawid
> >>>>>>
> >>>>>> On 10/12/2019 18:57, Becket Qin wrote:
> >>>>>>
> >>>>>> Hi folks,
> >>>>>>
> >>>>>> Thanks for the discussion, great feedback. Also thanks Dawid for the
> >>>>>> explanation, it is much clearer now.
> >>>>>>
> >>>>>> One thing that is indeed missing from the FLIP is how the
> >> boundedness
> >>> is
> >>>>>> passed to the Source implementation. So the API should be
> >>>>>> Source#createEnumerator(Boundedness boundedness,
> >>> SplitEnumeratorContext
> >>>>>> context)
> >>>>>> And we can probably remove the Source#supportBoundedness(Boundedness
> >>>>>> boundedness) method.
> >>>>>>
> >>>>>> Assuming we have that, we are essentially choosing from one of the
> >>>>>> following two options:
> >>>>>>
> >>>>>> Option 1:
> >>>>>> // The source is continuous source, and only unbounded operations
> >> can
> >>> be
> >>>>>> performed.
> >>>>>> DataStream<Type> datastream = env.continuousSource(someSource);
> >>>>>>
> >>>>>> // The source is bounded source, both bounded and unbounded
> >> operations
> >>>> can
> >>>>>> be performed.
> >>>>>> BoundedDataStream<Type> boundedDataStream =
> >>>> env.boundedSource(someSource);
> >>>>>>
> >>>>>>   - Pros:
> >>>>>>        a) explicit boundary between bounded / unbounded streams, it
> >> is
> >>>>>> quite simple and clear to the users.
> >>>>>>   - Cons:
> >>>>>>        a) For applications that do not involve bounded operations,
> >> they
> >>>>>> still have to call different API to distinguish bounded / unbounded
> >>>> streams.
> >>>>>>        b) No support for bounded stream to run in a streaming
> runtime
> >>>>>> setting, i.e. scheduling and operators behaviors.
> >>>>>>
> >>>>>>
> >>>>>> Option 2:
> >>>>>> // The source is either bounded or unbounded, but only unbounded
> >>>> operations
> >>>>>> could be performed on the returned DataStream.
> >>>>>> DataStream<Type> dataStream = env.source(someSource);
> >>>>>>
> >>>>>> // The source must be a bounded source, otherwise exception is
> >> thrown.
> >>>>>> BoundedDataStream<Type> boundedDataStream =
> >>>>>> env.boundedSource(boundedSource);
> >>>>>>
> >>>>>> The pros and cons are exactly the opposite of option 1.
> >>>>>>   - Pros:
> >>>>>>        a) For applications that do not involve bounded operations,
> >> they
> >>>>>> still have to call different API to distinguish bounded / unbounded
> >>>> streams.
> >>>>>>        b) Support for bounded stream to run in a streaming runtime
> >>>> setting,
> >>>>>> i.e. scheduling and operators behaviors.
> >>>>>>   - Cons:
> >>>>>>        a) Bounded / unbounded streams are kind of mixed, i.e. given
> a
> >>>>>> DataStream, it is not clear whether it is bounded or not, unless you
> >>>> have
> >>>>>> the access to its source.
> >>>>>>
> >>>>>>
> >>>>>> If we only think from the Source API perspective, option 2 seems a
> >>>> better
> >>>>>> choice because functionality wise it is a superset of option 1, at
> >> the
> >>>> cost
> >>>>>> of some seemingly acceptable ambiguity in the DataStream API.
> >>>>>> But if we look at the DataStream API as a whole, option 1 seems a
> >>>> clearer
> >>>>>> choice. For example, some times a library may have to know whether a
> >>>>>> certain task will finish or not. And it would be difficult to tell
> >> if
> >>>> the
> >>>>>> input is a DataStream, unless additional information is provided all
> >>> the
> >>>>>> way from the Source. One possible solution is to have a *modified
> >>>> option 2*
> >>>>>> which adds a method to the DataStream API to indicate boundedness,
> >>> such
> >>>> as
> >>>>>> getBoundedness(). It would solve the problem with a potential
> >>> confusion
> >>>> of
> >>>>>> what is difference between a DataStream with getBoundedness()=true
> >>> and a
> >>>>>> BoundedDataStream. But that seems not super difficult to explain.
> >>>>>>
> >>>>>> So from API's perspective, I don't have a strong opinion between
> >>>> *option 1*
> >>>>>> and *modified option 2. *I like the cleanness of option 1, but
> >>> modified
> >>>>>> option 2 would be more attractive if we have concrete use case for
> >> the
> >>>>>> "Bounded stream with unbounded streaming runtime settings".
> >>>>>>
> >>>>>> Re: Till
> >>>>>>
> >>>>>>
> >>>>>> Maybe this has already been asked before but I was wondering why the
> >>>>>> SourceReader interface has the method pollNext which hands the
> >>>>>> responsibility of outputting elements to the SourceReader
> >>>> implementation?
> >>>>>> Has this been done for backwards compatibility reasons with the old
> >>>> source
> >>>>>> interface? If not, then one could define a Collection<E>
> >>>> getNextRecords()
> >>>>>> method which returns the currently retrieved records and then the
> >>> caller
> >>>>>> emits them outside of the SourceReader. That way the interface would
> >>> not
> >>>>>> allow to implement an outputting loop where we never hand back
> >> control
> >>>> to
> >>>>>> the caller. At the moment, this contract can be easily broken and is
> >>>> only
> >>>>>> mentioned loosely in the JavaDocs.
> >>>>>>
> >>>>>>
> >>>>>> The primary reason we handover the SourceOutput to the SourceReader
> >> is
> >>>>>> because sometimes it is difficult for a SourceReader to emit one
> >>> record
> >>>> at
> >>>>>> a time. One example is some batched messaging systems which only
> >> have
> >>> an
> >>>>>> offset for the entire batch instead of individual messages in the
> >>>> batch. In
> >>>>>> that case, returning one record at a time would leave the
> >> SourceReader
> >>>> in
> >>>>>> an uncheckpointable state because they can only checkpoint at the
> >>> batch
> >>>>>> boundaries.
> >>>>>>
> >>>>>> Thanks,
> >>>>>>
> >>>>>> Jiangjie (Becket) Qin
> >>>>>>
> >>>>>> On Tue, Dec 10, 2019 at 5:33 PM Till Rohrmann <[hidden email]
> >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> >>>> [hidden email]>> wrote:
> >>>>>>
> >>>>>>
> >>>>>> Hi everyone,
> >>>>>>
> >>>>>> thanks for drafting this FLIP. It reads very well.
> >>>>>>
> >>>>>> Concerning Dawid's proposal, I tend to agree. The boundedness could
> >>> come
> >>>>>> from the source and tell the system how to treat the operator
> >>>> (scheduling
> >>>>>> wise). From a user's perspective it should be fine to get back a
> >>>> DataStream
> >>>>>> when calling env.source(boundedSource) if he does not need special
> >>>>>> operations defined on a BoundedDataStream. If he needs this, then
> >> one
> >>>> could
> >>>>>> use the method BoundedDataStream env.boundedSource(boundedSource).
> >>>>>>
> >>>>>> If possible, we could enforce the proper usage of
> >> env.boundedSource()
> >>> by
> >>>>>> introducing a BoundedSource type so that one cannot pass an
> >>>>>> unbounded source to it. That way users would not be able to shoot
> >>>>>> themselves in the foot.
> >>>>>>
> >>>>>> Maybe this has already been asked before but I was wondering why the
> >>>>>> SourceReader interface has the method pollNext which hands the
> >>>>>> responsibility of outputting elements to the SourceReader
> >>>> implementation?
> >>>>>> Has this been done for backwards compatibility reasons with the old
> >>>> source
> >>>>>> interface? If not, then one could define a Collection<E>
> >>>> getNextRecords()
> >>>>>> method which returns the currently retrieved records and then the
> >>> caller
> >>>>>> emits them outside of the SourceReader. That way the interface would
> >>> not
> >>>>>> allow to implement an outputting loop where we never hand back
> >> control
> >>>> to
> >>>>>> the caller. At the moment, this contract can be easily broken and is
> >>>> only
> >>>>>> mentioned loosely in the JavaDocs.
> >>>>>>
> >>>>>> Cheers,
> >>>>>> Till
> >>>>>>
> >>>>>> On Tue, Dec 10, 2019 at 7:49 AM Jingsong Li <[hidden email]
> >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> >>>> [hidden email]>>
> >>>>>> wrote:
> >>>>>>
> >>>>>>
> >>>>>> Hi all,
> >>>>>>
> >>>>>> I think current design is good.
> >>>>>>
> >>>>>> My understanding is:
> >>>>>>
> >>>>>> For execution mode: bounded mode and continuous mode, It's totally
> >>>>>> different. I don't think we have the ability to integrate the two
> >>> models
> >>>>>>
> >>>>>> at
> >>>>>>
> >>>>>> present. It's about scheduling, memory, algorithms, States, etc. we
> >>>>>> shouldn't confuse them.
> >>>>>>
> >>>>>> For source capabilities: only bounded, only continuous, both bounded
> >>> and
> >>>>>> continuous.
> >>>>>> I think Kafka is a source that can be ran both bounded
> >>>>>> and continuous execution mode.
> >>>>>> And Kafka with end offset should be ran both bounded
> >>>>>> and continuous execution mode.  Using apache Beam with Flink
> >> runner, I
> >>>>>>
> >>>>>> used
> >>>>>>
> >>>>>> to run a "bounded" Kafka in streaming mode. For our previous
> >>> DataStream,
> >>>>>>
> >>>>>> it
> >>>>>>
> >>>>>> is not necessarily required that the source cannot be bounded.
> >>>>>>
> >>>>>> So it is my thought for Dawid's question:
> >>>>>> 1.pass a bounded source to continuousSource() +1
> >>>>>> 2.pass a continuous source to boundedSource() -1, should throw
> >>>> exception.
> >>>>>>
> >>>>>> In StreamExecutionEnvironment, continuousSource and boundedSource
> >>> define
> >>>>>> the execution mode. It defines a clear boundary of execution mode.
> >>>>>>
> >>>>>> Best,
> >>>>>> Jingsong Lee
> >>>>>>
> >>>>>> On Tue, Dec 10, 2019 at 10:37 AM Jark Wu <[hidden email] <mailto:
> >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> wrote:
> >>>>>>
> >>>>>>
> >>>>>> I agree with Dawid's point that the boundedness information should
> >>> come
> >>>>>> from the source itself (e.g. the end timestamp), not through
> >>>>>> env.boundedSouce()/continuousSource().
> >>>>>> I think if we want to support something like `env.source()` that
> >>> derive
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> execution mode from source, `supportsBoundedness(Boundedness)`
> >>>>>> method is not enough, because we don't know whether it is bounded or
> >>>>>>
> >>>>>> not.
> >>>>>>
> >>>>>> Best,
> >>>>>> Jark
> >>>>>>
> >>>>>>
> >>>>>> On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <
> >> [hidden email]
> >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> >>>> [hidden email]>>
> >>>>>> wrote:
> >>>>>>
> >>>>>>
> >>>>>> One more thing. In the current proposal, with the
> >>>>>> supportsBoundedness(Boundedness) method and the boundedness coming
> >>>>>>
> >>>>>> from
> >>>>>>
> >>>>>> either continuousSource or boundedSource I could not find how this
> >>>>>> information is fed back to the SplitEnumerator.
> >>>>>>
> >>>>>> Best,
> >>>>>>
> >>>>>> Dawid
> >>>>>>
> >>>>>> On 09/12/2019 13:52, Becket Qin wrote:
> >>>>>>
> >>>>>> Hi Dawid,
> >>>>>>
> >>>>>> Thanks for the comments. This actually brings another relevant
> >>>>>>
> >>>>>> question
> >>>>>>
> >>>>>> about what does a "bounded source" imply. I actually had the same
> >>>>>> impression when I look at the Source API. Here is what I understand
> >>>>>>
> >>>>>> after
> >>>>>>
> >>>>>> some discussion with Stephan. The bounded source has the following
> >>>>>>
> >>>>>> impacts.
> >>>>>>
> >>>>>> 1. API validity.
> >>>>>> - A bounded source generates a bounded stream so some operations
> >>>>>>
> >>>>>> that
> >>>>>>
> >>>>>> only
> >>>>>>
> >>>>>> works for bounded records would be performed, e.g. sort.
> >>>>>> - To expose these bounded stream only APIs, there are two options:
> >>>>>>      a. Add them to the DataStream API and throw exception if a
> >>>>>>
> >>>>>> method
> >>>>>>
> >>>>>> is
> >>>>>>
> >>>>>> called on an unbounded stream.
> >>>>>>      b. Create a BoundedDataStream class which is returned from
> >>>>>> env.boundedSource(), while DataStream is returned from
> >>>>>>
> >>>>>> env.continousSource().
> >>>>>>
> >>>>>> Note that this cannot be done by having single
> >>>>>>
> >>>>>> env.source(theSource)
> >>>>>>
> >>>>>> even
> >>>>>>
> >>>>>> the Source has a getBoundedness() method.
> >>>>>>
> >>>>>> 2. Scheduling
> >>>>>> - A bounded source could be computed stage by stage without
> >>>>>>
> >>>>>> bringing
> >>>>>>
> >>>>>> up
> >>>>>>
> >>>>>> all
> >>>>>>
> >>>>>> the tasks at the same time.
> >>>>>>
> >>>>>> 3. Operator behaviors
> >>>>>> - A bounded source indicates the records are finite so some
> >>>>>>
> >>>>>> operators
> >>>>>>
> >>>>>> can
> >>>>>>
> >>>>>> wait until it receives all the records before it starts the
> >>>>>>
> >>>>>> processing.
> >>>>>>
> >>>>>> In the above impact, only 1 is relevant to the API design. And the
> >>>>>>
> >>>>>> current
> >>>>>>
> >>>>>> proposal in FLIP-27 is following 1.b.
> >>>>>>
> >>>>>> // boundedness depends of source property, imo this should always
> >>>>>>
> >>>>>> be
> >>>>>>
> >>>>>> preferred
> >>>>>>
> >>>>>>
> >>>>>> DataStream<MyType> stream = env.source(theSource);
> >>>>>>
> >>>>>>
> >>>>>> In your proposal, does DataStream have bounded stream only methods?
> >>>>>>
> >>>>>> It
> >>>>>>
> >>>>>> looks it should have, otherwise passing a bounded Source to
> >>>>>>
> >>>>>> env.source()
> >>>>>>
> >>>>>> would be confusing. In that case, we will essentially do 1.a if an
> >>>>>> unbounded Source is created from env.source(unboundedSource).
> >>>>>>
> >>>>>> If we have the methods only supported for bounded streams in
> >>>>>>
> >>>>>> DataStream,
> >>>>>>
> >>>>>> it
> >>>>>>
> >>>>>> seems a little weird to have a separate BoundedDataStream
> >>>>>>
> >>>>>> interface.
> >>>>>>
> >>>>>> Am I understand it correctly?
> >>>>>>
> >>>>>> Thanks,
> >>>>>>
> >>>>>> Jiangjie (Becket) Qin
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>> On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <
> >>>>>>
> >>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>
> >>>>>> wrote:
> >>>>>>
> >>>>>>
> >>>>>> Hi all,
> >>>>>>
> >>>>>> Really well written proposal and very important one. I must admit
> >>>>>>
> >>>>>> I
> >>>>>>
> >>>>>> have
> >>>>>>
> >>>>>> not understood all the intricacies of it yet.
> >>>>>>
> >>>>>> One question I have though is about where does the information
> >>>>>>
> >>>>>> about
> >>>>>>
> >>>>>> boundedness come from. I think in most cases it is a property of
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> source. As you described it might be e.g. end offset, a flag
> >>>>>>
> >>>>>> should
> >>>>>>
> >>>>>> it
> >>>>>>
> >>>>>> monitor new splits etc. I think it would be a really nice use case
> >>>>>>
> >>>>>> to
> >>>>>>
> >>>>>> be
> >>>>>>
> >>>>>> able to say:
> >>>>>>
> >>>>>> new KafkaSource().readUntil(long timestamp),
> >>>>>>
> >>>>>> which could work as an "end offset". Moreover I think all Bounded
> >>>>>>
> >>>>>> sources
> >>>>>>
> >>>>>> support continuous mode, but no intrinsically continuous source
> >>>>>>
> >>>>>> support
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> Bounded mode. If I understood the proposal correctly it suggest
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> boundedness sort of "comes" from the outside of the source, from
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> invokation of either boundedStream or continousSource.
> >>>>>>
> >>>>>> I am wondering if it would make sense to actually change the
> >>>>>>
> >>>>>> method
> >>>>>>
> >>>>>> boolean Source#supportsBoundedness(Boundedness)
> >>>>>>
> >>>>>> to
> >>>>>>
> >>>>>> Boundedness Source#getBoundedness().
> >>>>>>
> >>>>>> As for the methods #boundedSource, #continousSource, assuming the
> >>>>>> boundedness is property of the source they do not affect how the
> >>>>>>
> >>>>>> enumerator
> >>>>>>
> >>>>>> works, but mostly how the dag is scheduled, right? I am not
> >>>>>>
> >>>>>> against
> >>>>>>
> >>>>>> those
> >>>>>>
> >>>>>> methods, but I think it is a very specific use case to actually
> >>>>>>
> >>>>>> override
> >>>>>>
> >>>>>> the property of the source. In general I would expect users to
> >>>>>>
> >>>>>> only
> >>>>>>
> >>>>>> call
> >>>>>>
> >>>>>> env.source(theSource), where the source tells if it is bounded or
> >>>>>>
> >>>>>> not. I
> >>>>>>
> >>>>>> would suggest considering following set of methods:
> >>>>>>
> >>>>>> // boundedness depends of source property, imo this should always
> >>>>>>
> >>>>>> be
> >>>>>>
> >>>>>> preferred
> >>>>>>
> >>>>>> DataStream<MyType> stream = env.source(theSource);
> >>>>>>
> >>>>>>
> >>>>>> // always continous execution, whether bounded or unbounded source
> >>>>>>
> >>>>>> DataStream<MyType> boundedStream = env.continousSource(theSource);
> >>>>>>
> >>>>>> // imo this would make sense if the BoundedDataStream provides
> >>>>>>
> >>>>>> additional features unavailable for continous mode
> >>>>>>
> >>>>>> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
> >>>>>>
> >>>>>>
> >>>>>> Best,
> >>>>>>
> >>>>>> Dawid
> >>>>>>
> >>>>>>
> >>>>>> On 04/12/2019 11:25, Stephan Ewen wrote:
> >>>>>>
> >>>>>> Thanks, Becket, for updating this.
> >>>>>>
> >>>>>> I agree with moving the aspects you mentioned into separate FLIPs
> >>>>>>
> >>>>>> -
> >>>>>>
> >>>>>> this
> >>>>>>
> >>>>>> one way becoming unwieldy in size.
> >>>>>>
> >>>>>> +1 to the FLIP in its current state. Its a very detailed write-up,
> >>>>>>
> >>>>>> nicely
> >>>>>>
> >>>>>> done!
> >>>>>>
> >>>>>> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]
> >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> >>>> [hidden email]>>
> >>>>>>
> >>>>>> <
> >>>>>>
> >>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> >>>>>>
> >>>>>> Hi all,
> >>>>>>
> >>>>>> Sorry for the long belated update. I have updated FLIP-27 wiki
> >>>>>>
> >>>>>> page
> >>>>>>
> >>>>>> with
> >>>>>>
> >>>>>> the latest proposals. Some noticeable changes include:
> >>>>>> 1. A new generic communication mechanism between SplitEnumerator
> >>>>>>
> >>>>>> and
> >>>>>>
> >>>>>> SourceReader.
> >>>>>> 2. Some detail API method signature changes.
> >>>>>>
> >>>>>> We left a few things out of this FLIP and will address them in
> >>>>>>
> >>>>>> separate
> >>>>>>
> >>>>>> FLIPs. Including:
> >>>>>> 1. Per split event time.
> >>>>>> 2. Event time alignment.
> >>>>>> 3. Fine grained failover for SplitEnumerator failure.
> >>>>>>
> >>>>>> Please let us know if you have any question.
> >>>>>>
> >>>>>> Thanks,
> >>>>>>
> >>>>>> Jiangjie (Becket) Qin
> >>>>>>
> >>>>>> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]
> >>> <mailto:
> >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> >>>>>>
> >>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> >>>>>>
> >>>>>> Hi  Łukasz!
> >>>>>>
> >>>>>> Becket and me are working hard on figuring out the last details
> >>>>>>
> >>>>>> and
> >>>>>>
> >>>>>> implementing the first PoC. We would update the FLIP hopefully
> >>>>>>
> >>>>>> next
> >>>>>>
> >>>>>> week.
> >>>>>>
> >>>>>> There is a fair chance that a first version of this will be in
> >>>>>>
> >>>>>> 1.10,
> >>>>>>
> >>>>>> but
> >>>>>>
> >>>>>> I
> >>>>>>
> >>>>>> think it will take another release to battle test it and migrate
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> connectors.
> >>>>>>
> >>>>>> Best,
> >>>>>> Stephan
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <[hidden email]
> >>>> <mailto:[hidden email]>
> >>>>>>
> >>>>>> <
> >>>>>>
> >>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>
> >>>>>> wrote:
> >>>>>>
> >>>>>> Hi,
> >>>>>>
> >>>>>> This proposal looks very promising for us. Do you have any plans
> >>>>>>
> >>>>>> in
> >>>>>>
> >>>>>> which
> >>>>>>
> >>>>>> Flink release it is going to be released? We are thinking on
> >>>>>>
> >>>>>> using a
> >>>>>>
> >>>>>> Data
> >>>>>>
> >>>>>> Set API for our future use cases but on the other hand Data Set
> >>>>>>
> >>>>>> API
> >>>>>>
> >>>>>> is
> >>>>>>
> >>>>>> going to be deprecated so using proposed bounded data streams
> >>>>>>
> >>>>>> solution
> >>>>>>
> >>>>>> could be more viable in the long term.
> >>>>>>
> >>>>>> Thanks,
> >>>>>> Łukasz
> >>>>>>
> >>>>>> On 2019/10/01 15:48:03, Thomas Weise <[hidden email]
> >> <mailto:
> >>>> [hidden email]>> <[hidden email] <mailto:
> >>>> [hidden email]>> <
> >>>>>>
> >>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> >>>>>>
> >>>>>> Thanks for putting together this proposal!
> >>>>>>
> >>>>>> I see that the "Per Split Event Time" and "Event Time Alignment"
> >>>>>>
> >>>>>> sections
> >>>>>>
> >>>>>> are still TBD.
> >>>>>>
> >>>>>> It would probably be good to flesh those out a bit before
> >>>>>>
> >>>>>> proceeding
> >>>>>>
> >>>>>> too
> >>>>>>
> >>>>>> far
> >>>>>>
> >>>>>> as the event time alignment will probably influence the
> >>>>>>
> >>>>>> interaction
> >>>>>>
> >>>>>> with
> >>>>>>
> >>>>>> the split reader, specifically ReaderStatus
> >>>>>>
> >>>>>> emitNext(SourceOutput<E>
> >>>>>>
> >>>>>> output).
> >>>>>>
> >>>>>> We currently have only one implementation for event time alignment
> >>>>>>
> >>>>>> in
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> Kinesis consumer. The synchronization in that case takes place as
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> last
> >>>>>>
> >>>>>> step before records are emitted downstream (RecordEmitter). With
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> currently proposed interfaces, the equivalent can be implemented
> >>>>>>
> >>>>>> in
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> reader loop, although note that in the Kinesis consumer the per
> >>>>>>
> >>>>>> shard
> >>>>>>
> >>>>>> threads push records.
> >>>>>>
> >>>>>> Synchronization has not been implemented for the Kafka consumer
> >>>>>>
> >>>>>> yet.
> >>>>>>
> >>>>>> https://issues.apache.org/jira/browse/FLINK-12675 <
> >>>> https://issues.apache.org/jira/browse/FLINK-12675>
> >>>>>>
> >>>>>> When I looked at it, I realized that the implementation will look
> >>>>>>
> >>>>>> quite
> >>>>>>
> >>>>>> different
> >>>>>> from Kinesis because it needs to take place in the pull part,
> >>>>>>
> >>>>>> where
> >>>>>>
> >>>>>> records
> >>>>>>
> >>>>>> are taken from the Kafka client. Due to the multiplexing it cannot
> >>>>>>
> >>>>>> be
> >>>>>>
> >>>>>> done
> >>>>>>
> >>>>>> by blocking the split thread like it currently works for Kinesis.
> >>>>>>
> >>>>>> Reading
> >>>>>>
> >>>>>> from individual Kafka partitions needs to be controlled via
> >>>>>>
> >>>>>> pause/resume
> >>>>>>
> >>>>>> on the Kafka client.
> >>>>>>
> >>>>>> To take on that responsibility the split thread would need to be
> >>>>>>
> >>>>>> aware
> >>>>>>
> >>>>>> of
> >>>>>>
> >>>>>> the
> >>>>>> watermarks or at least whether it should or should not continue to
> >>>>>>
> >>>>>> consume
> >>>>>>
> >>>>>> a given split and this may require a different SourceReader or
> >>>>>>
> >>>>>> SourceOutput
> >>>>>>
> >>>>>> interface.
> >>>>>>
> >>>>>> Thanks,
> >>>>>> Thomas
> >>>>>>
> >>>>>>
> >>>>>> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email]
> >> <mailto:
> >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> >> <
> >>>>>>
> >>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> >>>>>>
> >>>>>> Hi Stephan,
> >>>>>>
> >>>>>> Thank you for feedback!
> >>>>>> Will take a look at your branch before public discussing.
> >>>>>>
> >>>>>>
> >>>>>> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]
> >>>> <mailto:[hidden email]>> <[hidden email] <mailto:[hidden email]
> >>>>
> >>>>>>
> >>>>>> <
> >>>>>>
> >>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>
> >>>>>> wrote:
> >>>>>>
> >>>>>> Hi Biao!
> >>>>>>
> >>>>>> Thanks for reviving this. I would like to join this discussion,
> >>>>>>
> >>>>>> but
> >>>>>>
> >>>>>> am
> >>>>>>
> >>>>>> quite occupied with the 1.9 release, so can we maybe pause this
> >>>>>>
> >>>>>> discussion
> >>>>>>
> >>>>>> for a week or so?
> >>>>>>
> >>>>>> In the meantime I can share some suggestion based on prior
> >>>>>>
> >>>>>> experiments:
> >>>>>>
> >>>>>> How to do watermarks / timestamp extractors in a simpler and more
> >>>>>>
> >>>>>> flexible
> >>>>>>
> >>>>>> way. I think that part is quite promising should be part of the
> >>>>>>
> >>>>>> new
> >>>>>>
> >>>>>> source
> >>>>>>
> >>>>>> interface.
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> >>>> <
> >>>>
> >>>
> >>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> >>>>>
> >>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> >>>> <
> >>>>
> >>>
> >>
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> >>>>>
> >>>>>>
> >>>>>> Some experiments on how to build the source reader and its
> >>>>>>
> >>>>>> library
> >>>>>>
> >>>>>> for
> >>>>>>
> >>>>>> common threading/split patterns:
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> >>>> <
> >>>>
> >>>
> >>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> >>>>>
> >>>>>>
> >>>>>> Best,
> >>>>>> Stephan
> >>>>>>
> >>>>>>
> >>>>>> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]
> >>> <mailto:
> >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> >> <
> >>>>>>
> >>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>
> >>>>>> wrote:
> >>>>>>
> >>>>>> Hi devs,
> >>>>>>
> >>>>>> Since 1.9 is nearly released, I think we could get back to
> >>>>>>
> >>>>>> FLIP-27.
> >>>>>>
> >>>>>> I
> >>>>>>
> >>>>>> believe it should be included in 1.10.
> >>>>>>
> >>>>>> There are so many things mentioned in document of FLIP-27. [1] I
> >>>>>>
> >>>>>> think
> >>>>>>
> >>>>>> we'd better discuss them separately. However the wiki is not a
> >>>>>>
> >>>>>> good
> >>>>>>
> >>>>>> place
> >>>>>>
> >>>>>> to discuss. I wrote google doc about SplitReader API which
> >>>>>>
> >>>>>> misses
> >>>>>>
> >>>>>> some
> >>>>>>
> >>>>>> details in the document. [2]
> >>>>>>
> >>>>>> 1.
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> >>>> <
> >>>>
> >>>
> >>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> >>>>>
> >>>>>>
> >>>>>> 2.
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> >>>> <
> >>>>
> >>>
> >>
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> >>>>>
> >>>>>>
> >>>>>> CC Stephan, Aljoscha, Piotrek, Becket
> >>>>>>
> >>>>>>
> >>>>>> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email]
> >> <mailto:
> >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> >> <
> >>>>>>
> >>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>
> >>>>>> wrote:
> >>>>>>
> >>>>>> Hi Steven,
> >>>>>> Thank you for the feedback. Please take a look at the document
> >>>>>>
> >>>>>> FLIP-27
> >>>>>>
> >>>>>> <
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> >>>> <
> >>>>
> >>>
> >>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> >>>>>
> >>>>>>
> >>>>>> which
> >>>>>>
> >>>>>> is updated recently. A lot of details of enumerator were added
> >>>>>>
> >>>>>> in
> >>>>>>
> >>>>>> this
> >>>>>>
> >>>>>> document. I think it would help.
> >>>>>>
> >>>>>> Steven Wu <[hidden email] <mailto:[hidden email]>> <
> >>>> [hidden email] <mailto:[hidden email]>> <
> >>> [hidden email]
> >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> >>>> [hidden email]>>
> >>>>>>
> >>>>>> 于2019年3月28日周四
> >>>>>>
> >>>>>> 下午12:52写道：
> >>>>>>
> >>>>>> This proposal mentioned that SplitEnumerator might run on the
> >>>>>> JobManager or
> >>>>>> in a single task on a TaskManager.
> >>>>>>
> >>>>>> if enumerator is a single task on a taskmanager, then the job
> >>>>>>
> >>>>>> DAG
> >>>>>>
> >>>>>> can
> >>>>>>
> >>>>>> never
> >>>>>> been embarrassingly parallel anymore. That will nullify the
> >>>>>>
> >>>>>> leverage
> >>>>>>
> >>>>>> of
> >>>>>>
> >>>>>> fine-grained recovery for embarrassingly parallel jobs.
> >>>>>>
> >>>>>> It's not clear to me what's the implication of running
> >>>>>>
> >>>>>> enumerator
> >>>>>>
> >>>>>> on
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> jobmanager. So I will leave that out for now.
> >>>>>>
> >>>>>> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email]
> >> <mailto:
> >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> >> <
> >>>>>>
> >>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>
> >>>>>> wrote:
> >>>>>>
> >>>>>> Hi Stephan & Piotrek,
> >>>>>>
> >>>>>> Thank you for feedback.
> >>>>>>
> >>>>>> It seems that there are a lot of things to do in community.
> >>>>>>
> >>>>>> I
> >>>>>>
> >>>>>> am
> >>>>>>
> >>>>>> just
> >>>>>>
> >>>>>> afraid that this discussion may be forgotten since there so
> >>>>>>
> >>>>>> many
> >>>>>>
> >>>>>> proposals
> >>>>>>
> >>>>>> recently.
> >>>>>> Anyway, wish to see the split topics soon :)
> >>>>>>
> >>>>>> Piotr Nowojski <[hidden email] <mailto:[hidden email]
> >>>>
> >>> <
> >>>> [hidden email] <mailto:[hidden email]>> <
> >>>> [hidden email] <mailto:[hidden email]>> <
> >>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>
> >>>>>> 于2019年1月24日周四
> >>>>>>
> >>>>>> 下午8:21写道：
> >>>>>>
> >>>>>> Hi Biao!
> >>>>>>
> >>>>>> This discussion was stalled because of preparations for
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> open
> >>>>>>
> >>>>>> sourcing
> >>>>>>
> >>>>>> & merging Blink. I think before creating the tickets we
> >>>>>>
> >>>>>> should
> >>>>>>
> >>>>>> split this
> >>>>>>
> >>>>>> discussion into topics/areas outlined by Stephan and
> >>>>>>
> >>>>>> create
> >>>>>>
> >>>>>> Flips
> >>>>>>
> >>>>>> for
> >>>>>>
> >>>>>> that.
> >>>>>>
> >>>>>> I think there is no chance for this to be completed in
> >>>>>>
> >>>>>> couple
> >>>>>>
> >>>>>> of
> >>>>>>
> >>>>>> remaining
> >>>>>>
> >>>>>> weeks/1 month before 1.8 feature freeze, however it would
> >>>>>>
> >>>>>> be
> >>>>>>
> >>>>>> good
> >>>>>>
> >>>>>> to aim
> >>>>>>
> >>>>>> with those changes for 1.9.
> >>>>>>
> >>>>>> Piotrek
> >>>>>>
> >>>>>>
> >>>>>> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email] <mailto:
> >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> >> <
> >>>>>>
> >>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>
> >>>>>> wrote:
> >>>>>>
> >>>>>> Hi community,
> >>>>>> The summary of Stephan makes a lot sense to me. It is
> >>>>>>
> >>>>>> much
> >>>>>>
> >>>>>> clearer
> >>>>>>
> >>>>>> indeed
> >>>>>>
> >>>>>> after splitting the complex topic into small ones.
> >>>>>> I was wondering is there any detail plan for next step?
> >>>>>>
> >>>>>> If
> >>>>>>
> >>>>>> not,
> >>>>>>
> >>>>>> I
> >>>>>>
> >>>>>> would
> >>>>>>
> >>>>>> like to push this thing forward by creating some JIRA
> >>>>>>
> >>>>>> issues.
> >>>>>>
> >>>>>> Another question is that should version 1.8 include
> >>>>>>
> >>>>>> these
> >>>>>>
> >>>>>> features?
> >>>>>>
> >>>>>> Stephan Ewen <[hidden email] <mailto:[hidden email]>> <
> >>>> [hidden email] <mailto:[hidden email]>> <[hidden email]
> <mailto:
> >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> >>>> 于2018年12月1日周六
> >>>>>>
> >>>>>> 上午4:20写道：
> >>>>>>
> >>>>>> Thanks everyone for the lively discussion. Let me try
> >>>>>>
> >>>>>> to
> >>>>>>
> >>>>>> summarize
> >>>>>>
> >>>>>> where I
> >>>>>>
> >>>>>> see convergence in the discussion and open issues.
> >>>>>> I'll try to group this by design aspect of the source.
> >>>>>>
> >>>>>> Please
> >>>>>>
> >>>>>> let me
> >>>>>>
> >>>>>> know
> >>>>>>
> >>>>>> if I got things wrong or missed something crucial here.
> >>>>>>
> >>>>>> For issues 1-3, if the below reflects the state of the
> >>>>>>
> >>>>>> discussion, I
> >>>>>>
> >>>>>> would
> >>>>>>
> >>>>>> try and update the FLIP in the next days.
> >>>>>> For the remaining ones we need more discussion.
> >>>>>>
> >>>>>> I would suggest to fork each of these aspects into a
> >>>>>>
> >>>>>> separate
> >>>>>>
> >>>>>> mail
> >>>>>>
> >>>>>> thread,
> >>>>>>
> >>>>>> or will loose sight of the individual aspects.
> >>>>>>
> >>>>>> *(1) Separation of Split Enumerator and Split Reader*
> >>>>>>
> >>>>>> - All seem to agree this is a good thing
> >>>>>> - Split Enumerator could in the end live on JobManager
> >>>>>>
> >>>>>> (and
> >>>>>>
> >>>>>> assign
> >>>>>>
> >>>>>> splits
> >>>>>>
> >>>>>> via RPC) or in a task (and assign splits via data
> >>>>>>
> >>>>>> streams)
> >>>>>>
> >>>>>> - this discussion is orthogonal and should come later,
> >>>>>>
> >>>>>> when
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> interface
> >>>>>>
> >>>>>> is agreed upon.
> >>>>>>
> >>>>>> *(2) Split Readers for one or more splits*
> >>>>>>
> >>>>>> - Discussion seems to agree that we need to support
> >>>>>>
> >>>>>> one
> >>>>>>
> >>>>>> reader
> >>>>>>
> >>>>>> that
> >>>>>>
> >>>>>> possibly handles multiple splits concurrently.
> >>>>>> - The requirement comes from sources where one
> >>>>>>
> >>>>>> poll()-style
> >>>>>>
> >>>>>> call
> >>>>>>
> >>>>>> fetches
> >>>>>>
> >>>>>> data from different splits / partitions
> >>>>>>    --> example sources that require that would be for
> >>>>>>
> >>>>>> example
> >>>>>>
> >>>>>> Kafka,
> >>>>>>
> >>>>>> Pravega, Pulsar
> >>>>>>
> >>>>>> - Could have one split reader per source, or multiple
> >>>>>>
> >>>>>> split
> >>>>>>
> >>>>>> readers
> >>>>>>
> >>>>>> that
> >>>>>>
> >>>>>> share the "poll()" function
> >>>>>> - To not make it too complicated, we can start with
> >>>>>>
> >>>>>> thinking
> >>>>>>
> >>>>>> about
> >>>>>>
> >>>>>> one
> >>>>>>
> >>>>>> split reader for all splits initially and see if that
> >>>>>>
> >>>>>> covers
> >>>>>>
> >>>>>> all
> >>>>>>
> >>>>>> requirements
> >>>>>>
> >>>>>> *(3) Threading model of the Split Reader*
> >>>>>>
> >>>>>> - Most active part of the discussion ;-)
> >>>>>>
> >>>>>> - A non-blocking way for Flink's task code to interact
> >>>>>>
> >>>>>> with
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> source
> >>>>>>
> >>>>>> is
> >>>>>>
> >>>>>> needed in order to a task runtime code based on a
> >>>>>> single-threaded/actor-style task design
> >>>>>>    --> I personally am a big proponent of that, it will
> >>>>>>
> >>>>>> help
> >>>>>>
> >>>>>> with
> >>>>>>
> >>>>>> well-behaved checkpoints, efficiency, and simpler yet
> >>>>>>
> >>>>>> more
> >>>>>>
> >>>>>> robust
> >>>>>>
> >>>>>> runtime
> >>>>>>
> >>>>>> code
> >>>>>>
> >>>>>> - Users care about simple abstraction, so as a
> >>>>>>
> >>>>>> subclass
> >>>>>>
> >>>>>> of
> >>>>>>
> >>>>>> SplitReader
> >>>>>>
> >>>>>> (non-blocking / async) we need to have a
> >>>>>>
> >>>>>> BlockingSplitReader
> >>>>>>
> >>>>>> which
> >>>>>>
> >>>>>> will
> >>>>>>
> >>>>>> form the basis of most source implementations.
> >>>>>>
> >>>>>> BlockingSplitReader
> >>>>>>
> >>>>>> lets
> >>>>>>
> >>>>>> users do blocking simple poll() calls.
> >>>>>> - The BlockingSplitReader would spawn a thread (or
> >>>>>>
> >>>>>> more)
> >>>>>>
> >>>>>> and
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> thread(s) can make blocking calls and hand over data
> >>>>>>
> >>>>>> buffers
> >>>>>>
> >>>>>> via
> >>>>>>
> >>>>>> a
> >>>>>>
> >>>>>> blocking
> >>>>>>
> >>>>>> queue
> >>>>>> - This should allow us to cover both, a fully async
> >>>>>>
> >>>>>> runtime,
> >>>>>>
> >>>>>> and a
> >>>>>>
> >>>>>> simple
> >>>>>>
> >>>>>> blocking interface for users.
> >>>>>> - This is actually very similar to how the Kafka
> >>>>>>
> >>>>>> connectors
> >>>>>>
> >>>>>> work.
> >>>>>>
> >>>>>> Kafka
> >>>>>>
> >>>>>> 9+ with one thread, Kafka 8 with multiple threads
> >>>>>>
> >>>>>> - On the base SplitReader (the async one), the
> >>>>>>
> >>>>>> non-blocking
> >>>>>>
> >>>>>> method
> >>>>>>
> >>>>>> that
> >>>>>>
> >>>>>> gets the next chunk of data would signal data
> >>>>>>
> >>>>>> availability
> >>>>>>
> >>>>>> via
> >>>>>>
> >>>>>> a
> >>>>>>
> >>>>>> CompletableFuture, because that gives the best
> >>>>>>
> >>>>>> flexibility
> >>>>>>
> >>>>>> (can
> >>>>>>
> >>>>>> await
> >>>>>>
> >>>>>> completion or register notification handlers).
> >>>>>> - The source task would register a "thenHandle()" (or
> >>>>>>
> >>>>>> similar)
> >>>>>>
> >>>>>> on the
> >>>>>>
> >>>>>> future to put a "take next data" task into the
> >>>>>>
> >>>>>> actor-style
> >>>>>>
> >>>>>> mailbox
> >>>>>>
> >>>>>> *(4) Split Enumeration and Assignment*
> >>>>>>
> >>>>>> - Splits may be generated lazily, both in cases where
> >>>>>>
> >>>>>> there
> >>>>>>
> >>>>>> is a
> >>>>>>
> >>>>>> limited
> >>>>>>
> >>>>>> number of splits (but very many), or splits are
> >>>>>>
> >>>>>> discovered
> >>>>>>
> >>>>>> over
> >>>>>>
> >>>>>> time
> >>>>>>
> >>>>>> - Assignment should also be lazy, to get better load
> >>>>>>
> >>>>>> balancing
> >>>>>>
> >>>>>> - Assignment needs support locality preferences
> >>>>>>
> >>>>>> - Possible design based on discussion so far:
> >>>>>>
> >>>>>>    --> SplitReader has a method "addSplits(SplitT...)"
> >>>>>>
> >>>>>> to
> >>>>>>
> >>>>>> add
> >>>>>>
> >>>>>> one or
> >>>>>>
> >>>>>> more
> >>>>>>
> >>>>>> splits. Some split readers might assume they have only
> >>>>>>
> >>>>>> one
> >>>>>>
> >>>>>> split
> >>>>>>
> >>>>>> ever,
> >>>>>>
> >>>>>> concurrently, others assume multiple splits. (Note:
> >>>>>>
> >>>>>> idea
> >>>>>>
> >>>>>> behind
> >>>>>>
> >>>>>> being
> >>>>>>
> >>>>>> able
> >>>>>>
> >>>>>> to add multiple splits at the same time is to ease
> >>>>>>
> >>>>>> startup
> >>>>>>
> >>>>>> where
> >>>>>>
> >>>>>> multiple
> >>>>>>
> >>>>>> splits may be assigned instantly.)
> >>>>>>    --> SplitReader has a context object on which it can
> >>>>>>
> >>>>>> call
> >>>>>>
> >>>>>> indicate
> >>>>>>
> >>>>>> when
> >>>>>>
> >>>>>> splits are completed. The enumerator gets that
> >>>>>>
> >>>>>> notification and
> >>>>>>
> >>>>>> can
> >>>>>>
> >>>>>> use
> >>>>>>
> >>>>>> to
> >>>>>>
> >>>>>> decide when to assign new splits. This should help both
> >>>>>>
> >>>>>> in
> >>>>>>
> >>>>>> cases
> >>>>>>
> >>>>>> of
> >>>>>>
> >>>>>> sources
> >>>>>>
> >>>>>> that take splits lazily (file readers) and in case the
> >>>>>>
> >>>>>> source
> >>>>>>
> >>>>>> needs to
> >>>>>>
> >>>>>> preserve a partial order between splits (Kinesis,
> >>>>>>
> >>>>>> Pravega,
> >>>>>>
> >>>>>> Pulsar may
> >>>>>>
> >>>>>> need
> >>>>>>
> >>>>>> that).
> >>>>>>    --> SplitEnumerator gets notification when
> >>>>>>
> >>>>>> SplitReaders
> >>>>>>
> >>>>>> start
> >>>>>>
> >>>>>> and
> >>>>>>
> >>>>>> when
> >>>>>>
> >>>>>> they finish splits. They can decide at that moment to
> >>>>>>
> >>>>>> push
> >>>>>>
> >>>>>> more
> >>>>>>
> >>>>>> splits
> >>>>>>
> >>>>>> to
> >>>>>>
> >>>>>> that reader
> >>>>>>    --> The SplitEnumerator should probably be aware of
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> source
> >>>>>>
> >>>>>> parallelism, to build its initial distribution.
> >>>>>>
> >>>>>> - Open question: Should the source expose something
> >>>>>>
> >>>>>> like
> >>>>>>
> >>>>>> "host
> >>>>>>
> >>>>>> preferences", so that yarn/mesos/k8s can take this into
> >>>>>>
> >>>>>> account
> >>>>>>
> >>>>>> when
> >>>>>>
> >>>>>> selecting a node to start a TM on?
> >>>>>>
> >>>>>> *(5) Watermarks and event time alignment*
> >>>>>>
> >>>>>> - Watermark generation, as well as idleness, needs to
> >>>>>>
> >>>>>> be
> >>>>>>
> >>>>>> per
> >>>>>>
> >>>>>> split
> >>>>>>
> >>>>>> (like
> >>>>>>
> >>>>>> currently in the Kafka Source, per partition)
> >>>>>> - It is desirable to support optional
> >>>>>>
> >>>>>> event-time-alignment,
> >>>>>>
> >>>>>> meaning
> >>>>>>
> >>>>>> that
> >>>>>>
> >>>>>> splits that are ahead are back-pressured or temporarily
> >>>>>>
> >>>>>> unsubscribed
> >>>>>>
> >>>>>> - I think i would be desirable to encapsulate
> >>>>>>
> >>>>>> watermark
> >>>>>>
> >>>>>> generation
> >>>>>>
> >>>>>> logic
> >>>>>>
> >>>>>> in watermark generators, for a separation of concerns.
> >>>>>>
> >>>>>> The
> >>>>>>
> >>>>>> watermark
> >>>>>>
> >>>>>> generators should run per split.
> >>>>>> - Using watermark generators would also help with
> >>>>>>
> >>>>>> another
> >>>>>>
> >>>>>> problem of
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> suggested interface, namely supporting non-periodic
> >>>>>>
> >>>>>> watermarks
> >>>>>>
> >>>>>> efficiently.
> >>>>>>
> >>>>>> - Need a way to "dispatch" next record to different
> >>>>>>
> >>>>>> watermark
> >>>>>>
> >>>>>> generators
> >>>>>>
> >>>>>> - Need a way to tell SplitReader to "suspend" a split
> >>>>>>
> >>>>>> until a
> >>>>>>
> >>>>>> certain
> >>>>>>
> >>>>>> watermark is reached (event time backpressure)
> >>>>>> - This would in fact be not needed (and thus simpler)
> >>>>>>
> >>>>>> if
> >>>>>>
> >>>>>> we
> >>>>>>
> >>>>>> had
> >>>>>>
> >>>>>> a
> >>>>>>
> >>>>>> SplitReader per split and may be a reason to re-open
> >>>>>>
> >>>>>> that
> >>>>>>
> >>>>>> discussion
> >>>>>>
> >>>>>> *(6) Watermarks across splits and in the Split
> >>>>>>
> >>>>>> Enumerator*
> >>>>>>
> >>>>>> - The split enumerator may need some watermark
> >>>>>>
> >>>>>> awareness,
> >>>>>>
> >>>>>> which
> >>>>>>
> >>>>>> should
> >>>>>>
> >>>>>> be
> >>>>>>
> >>>>>> purely based on split metadata (like create timestamp
> >>>>>>
> >>>>>> of
> >>>>>>
> >>>>>> file
> >>>>>>
> >>>>>> splits)
> >>>>>>
> >>>>>> - If there are still more splits with overlapping
> >>>>>>
> >>>>>> event
> >>>>>>
> >>>>>> time
> >>>>>>
> >>>>>> range
> >>>>>>
> >>>>>> for
> >>>>>>
> >>>>>> a
> >>>>>>
> >>>>>> split reader, then that split reader should not advance
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> watermark
> >>>>>>
> >>>>>> within the split beyond the overlap boundary. Otherwise
> >>>>>>
> >>>>>> future
> >>>>>>
> >>>>>> splits
> >>>>>>
> >>>>>> will
> >>>>>>
> >>>>>> produce late data.
> >>>>>>
> >>>>>> - One way to approach this could be that the split
> >>>>>>
> >>>>>> enumerator
> >>>>>>
> >>>>>> may
> >>>>>>
> >>>>>> send
> >>>>>>
> >>>>>> watermarks to the readers, and the readers cannot emit
> >>>>>>
> >>>>>> watermarks
> >>>>>>
> >>>>>> beyond
> >>>>>>
> >>>>>> that received watermark.
> >>>>>> - Many split enumerators would simply immediately send
> >>>>>>
> >>>>>> Long.MAX
> >>>>>>
> >>>>>> out
> >>>>>>
> >>>>>> and
> >>>>>>
> >>>>>> leave the progress purely to the split readers.
> >>>>>>
> >>>>>> - For event-time alignment / split back pressure, this
> >>>>>>
> >>>>>> begs
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> question
> >>>>>>
> >>>>>> how we can avoid deadlocks that may arise when splits
> >>>>>>
> >>>>>> are
> >>>>>>
> >>>>>> suspended
> >>>>>>
> >>>>>> for
> >>>>>>
> >>>>>> event time back pressure,
> >>>>>>
> >>>>>> *(7) Batch and streaming Unification*
> >>>>>>
> >>>>>> - Functionality wise, the above design should support
> >>>>>>
> >>>>>> both
> >>>>>>
> >>>>>> - Batch often (mostly) does not care about reading "in
> >>>>>>
> >>>>>> order"
> >>>>>>
> >>>>>> and
> >>>>>>
> >>>>>> generating watermarks
> >>>>>>    --> Might use different enumerator logic that is
> >>>>>>
> >>>>>> more
> >>>>>>
> >>>>>> locality
> >>>>>>
> >>>>>> aware
> >>>>>>
> >>>>>> and ignores event time order
> >>>>>>    --> Does not generate watermarks
> >>>>>> - Would be great if bounded sources could be
> >>>>>>
> >>>>>> identified
> >>>>>>
> >>>>>> at
> >>>>>>
> >>>>>> compile
> >>>>>>
> >>>>>> time,
> >>>>>>
> >>>>>> so that "env.addBoundedSource(...)" is type safe and
> >>>>>>
> >>>>>> can
> >>>>>>
> >>>>>> return a
> >>>>>>
> >>>>>> "BoundedDataStream".
> >>>>>> - Possible to defer this discussion until later
> >>>>>>
> >>>>>> *Miscellaneous Comments*
> >>>>>>
> >>>>>> - Should the source have a TypeInformation for the
> >>>>>>
> >>>>>> produced
> >>>>>>
> >>>>>> type,
> >>>>>>
> >>>>>> instead
> >>>>>>
> >>>>>> of a serializer? We need a type information in the
> >>>>>>
> >>>>>> stream
> >>>>>>
> >>>>>> anyways, and
> >>>>>>
> >>>>>> can
> >>>>>>
> >>>>>> derive the serializer from that. Plus, creating the
> >>>>>>
> >>>>>> serializer
> >>>>>>
> >>>>>> should
> >>>>>>
> >>>>>> respect the ExecutionConfig.
> >>>>>>
> >>>>>> - The TypeSerializer interface is very powerful but
> >>>>>>
> >>>>>> also
> >>>>>>
> >>>>>> not
> >>>>>>
> >>>>>> easy to
> >>>>>>
> >>>>>> implement. Its purpose is to handle data super
> >>>>>>
> >>>>>> efficiently,
> >>>>>>
> >>>>>> support
> >>>>>>
> >>>>>> flexible ways of evolution, etc.
> >>>>>> For metadata I would suggest to look at the
> >>>>>>
> >>>>>> SimpleVersionedSerializer
> >>>>>>
> >>>>>> instead, which is used for example for checkpoint
> >>>>>>
> >>>>>> master
> >>>>>>
> >>>>>> hooks,
> >>>>>>
> >>>>>> or for
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> streaming file sink. I think that is is a good match
> >>>>>>
> >>>>>> for
> >>>>>>
> >>>>>> cases
> >>>>>>
> >>>>>> where
> >>>>>>
> >>>>>> we
> >>>>>>
> >>>>>> do
> >>>>>>
> >>>>>> not need more than ser/deser (no copy, etc.) and don't
> >>>>>>
> >>>>>> need to
> >>>>>>
> >>>>>> push
> >>>>>>
> >>>>>> versioning out of the serialization paths for best
> >>>>>>
> >>>>>> performance
> >>>>>>
> >>>>>> (as in
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> TypeSerializer)
> >>>>>>
> >>>>>>
> >>>>>> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
> >>>>>>
> >>>>>> [hidden email]>
> >>>>>>
> >>>>>> wrote:
> >>>>>>
> >>>>>>
> >>>>>> Hi Biao,
> >>>>>>
> >>>>>> Thanks for the answer!
> >>>>>>
> >>>>>> So given the multi-threaded readers, now we have as
> >>>>>>
> >>>>>> open
> >>>>>>
> >>>>>> questions:
> >>>>>>
> >>>>>> 1) How do we let the checkpoints pass through our
> >>>>>>
> >>>>>> multi-threaded
> >>>>>>
> >>>>>> reader
> >>>>>>
> >>>>>> operator?
> >>>>>>
> >>>>>> 2) Do we have separate reader and source operators or
> >>>>>>
> >>>>>> not? In
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> strategy
> >>>>>>
> >>>>>> that has a separate source, the source operator has a
> >>>>>>
> >>>>>> parallelism of
> >>>>>>
> >>>>>> 1
> >>>>>>
> >>>>>> and
> >>>>>>
> >>>>>> is responsible for split recovery only.
> >>>>>>
> >>>>>> For the first one, given also the constraints
> >>>>>>
> >>>>>> (blocking,
> >>>>>>
> >>>>>> finite
> >>>>>>
> >>>>>> queues,
> >>>>>>
> >>>>>> etc), I do not have an answer yet.
> >>>>>>
> >>>>>> For the 2nd, I think that we should go with separate
> >>>>>>
> >>>>>> operators
> >>>>>>
> >>>>>> for
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> source and the readers, for the following reasons:
> >>>>>>
> >>>>>> 1) This is more aligned with a potential future
> >>>>>>
> >>>>>> improvement
> >>>>>>
> >>>>>> where the
> >>>>>>
> >>>>>> split
> >>>>>>
> >>>>>> discovery becomes a responsibility of the JobManager
> >>>>>>
> >>>>>> and
> >>>>>>
> >>>>>> readers are
> >>>>>>
> >>>>>> pooling more work from the JM.
> >>>>>>
> >>>>>> 2) The source is going to be the "single point of
> >>>>>>
> >>>>>> truth".
> >>>>>>
> >>>>>> It
> >>>>>>
> >>>>>> will
> >>>>>>
> >>>>>> know
> >>>>>>
> >>>>>> what
> >>>>>>
> >>>>>> has been processed and what not. If the source and the
> >>>>>>
> >>>>>> readers
> >>>>>>
> >>>>>> are a
> >>>>>>
> >>>>>> single
> >>>>>>
> >>>>>> operator with parallelism > 1, or in general, if the
> >>>>>>
> >>>>>> split
> >>>>>>
> >>>>>> discovery
> >>>>>>
> >>>>>> is
> >>>>>>
> >>>>>> done by each task individually, then:
> >>>>>>   i) we have to have a deterministic scheme for each
> >>>>>>
> >>>>>> reader to
> >>>>>>
> >>>>>> assign
> >>>>>>
> >>>>>> splits to itself (e.g. mod subtaskId). This is not
> >>>>>>
> >>>>>> necessarily
> >>>>>>
> >>>>>> trivial
> >>>>>>
> >>>>>> for
> >>>>>>
> >>>>>> all sources.
> >>>>>>   ii) each reader would have to keep a copy of all its
> >>>>>>
> >>>>>> processed
> >>>>>>
> >>>>>> slpits
> >>>>>>
> >>>>>>   iii) the state has to be a union state with a
> >>>>>>
> >>>>>> non-trivial
> >>>>>>
> >>>>>> merging
> >>>>>>
> >>>>>> logic
> >>>>>>
> >>>>>> in order to support rescaling.
> >>>>>>
> >>>>>> Two additional points that you raised above:
> >>>>>>
> >>>>>> i) The point that you raised that we need to keep all
> >>>>>>
> >>>>>> splits
> >>>>>>
> >>>>>> (processed
> >>>>>>
> >>>>>> and
> >>>>>>
> >>>>>> not-processed) I think is a bit of a strong
> >>>>>>
> >>>>>> requirement.
> >>>>>>
> >>>>>> This
> >>>>>>
> >>>>>> would
> >>>>>>
> >>>>>> imply
> >>>>>>
> >>>>>> that for infinite sources the state will grow
> >>>>>>
> >>>>>> indefinitely.
> >>>>>>
> >>>>>> This is
> >>>>>>
> >>>>>> problem
> >>>>>>
> >>>>>> is even more pronounced if we do not have a single
> >>>>>>
> >>>>>> source
> >>>>>>
> >>>>>> that
> >>>>>>
> >>>>>> assigns
> >>>>>>
> >>>>>> splits to readers, as each reader will have its own
> >>>>>>
> >>>>>> copy
> >>>>>>
> >>>>>> of
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> state.
> >>>>>>
> >>>>>> ii) it is true that for finite sources we need to
> >>>>>>
> >>>>>> somehow
> >>>>>>
> >>>>>> not
> >>>>>>
> >>>>>> close
> >>>>>>
> >>>>>> the
> >>>>>>
> >>>>>> readers when the source/split discoverer finishes. The
> >>>>>> ContinuousFileReaderOperator has a work-around for
> >>>>>>
> >>>>>> that.
> >>>>>>
> >>>>>> It is
> >>>>>>
> >>>>>> not
> >>>>>>
> >>>>>> elegant,
> >>>>>>
> >>>>>> and checkpoints are not emitted after closing the
> >>>>>>
> >>>>>> source,
> >>>>>>
> >>>>>> but
> >>>>>>
> >>>>>> this, I
> >>>>>>
> >>>>>> believe, is a bigger problem which requires more
> >>>>>>
> >>>>>> changes
> >>>>>>
> >>>>>> than
> >>>>>>
> >>>>>> just
> >>>>>>
> >>>>>> refactoring the source interface.
> >>>>>>
> >>>>>> Cheers,
> >>>>>> Kostas
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>> --
> >>>>>> Best, Jingsong Lee
> >>>>
> >>>>
> >>>
> >>
> >>
> >> --
> >> Best, Jingsong Lee
> >>
> >
>
>

[Jark Wu-2]

Hi Becket,

That's great we have reached a consensus on Source#getBoundedness().

Regarding to option#3, my concern is that if we don't support streaming
mode for bounded source,
how could we create a testing source for streaming mode? Currently, all the
testing source for streaming
are bounded, so that the integration test will finish finally.

Regarding to Source#getRecordOrder(), could we have a implicit contract
that unbounded source should
already read in order (i.e. reading partitions in parallel), for bounded
source the order is not mandatory.
This is also the behaviors of the current sources.
1) a source can't guarantee it reads in strict order, because the producer
may produce data not in order.
2) *Bounded-StrictOrder* is not necessary, because batch can reorder data.

Best,
Jark



On Tue, 17 Dec 2019 at 22:03, Becket Qin <[hidden email]> wrote:

> Hi folks,
>
> Thanks for the comments. I am convinced that the Source API should not take
> boundedness as a parameter after it is constructed. What Timo and Dawid
> suggested sounds a reasonable solution to me. So the Source API would
> become:
>
> Source {
>     Boundedness getBoundedness();
> }
>
> Assuming the above Source API, in addition to the two options mentioned in
> earlier emails, I am thinking of another option:
>
> *Option 3:*
> // MySource must be unbounded, otherwise throws exception.
> DataStream<Type> dataStream = env.source(mySource);
>
> // MySource must be bounded, otherwise throws exception.
> BoundedDataStream<Type> boundedDataStream = env.boundedSource(mySource);
>
> The pros of this API are:
>    a) It fits the requirements from Table / SQL well.
>    b) DataStream users still have type safety (option 2 only has partial
> type safety).
>    c) Cristal clear boundedness from the API which makes DataStream join /
> connect easy to reason about.
> The caveats I see,
>    a) It is inconsistent with Table since Table has one unified interface.
>    b) No streaming mode for bounded source.
>
> @Stephan Ewen <[hidden email]> @Aljoscha Krettek
> <[hidden email]> what do you think of the approach?
>
>
> Orthogonal to the above API, I am wondering whether boundedness is the only
> dimension needed to describe the characteristic of the Source behavior. We
> may also need to have another dimension of *record order*.
>
> For example, when a file source is reading from a directory with bounded
> records, it may have two ways to read.
> 1. Read files in parallel.
> 2. Read files in the chronological order.
> In both cases, the file source is a Bounded Source. However, the processing
> requirement for downstream may be different. In the first case, the
> record processing and result emitting order does not matter, e.g. word
> count. In the second case, the records may have to be processed in the
> order they were read, e.g. change log processing.
>
> If the Source only has a getBoundedness() method, the downstream processors
> would not know whether the records emitted from the Source should be
> processed in order or not. So combining the boundedness and record order,
> we will have four scenarios:
>
> *Bounded-StrictOrder*:     A segment of change log.
> *Bounded-Random*:          Batch Word Count.
> *Unbounded-StrictOrder*: An infinite change log.
> *Unbounded-Random*:     Streaming Word Count.
>
> Option 2 mentioned in the previous email was kind of trying to handle the
> Bounded-StrictOrder case by creating a DataStream from a bounded source,
> which actually does not work.
> It looks that we do not have strict order support in some operators at this
> point, e.g. join. But we may still want to add the semantic to the Source
> first so later on we don't need to change all the source implementations,
> especially given that many of them will be implemented by 3rd party.
>
> Given that, we need another dimension of *Record Order* in the Source. More
> specifically, the API would become:
>
> Source {
>     Boundedness getBoundedness();
>     RecordOrder getRecordOrder();
> }
>
> public enum RecordOrder {
>     /** The record in the DataStream must be processed in its strict order
> for correctness. */
>     STRICT,
>     /** The record in the DataStream can be processed in arbitrary order.
> */
>     RANDOM;
> }
>
> Any thoughts?
>
> Thanks,
>
> Jiangjie (Becket) Qin
>
> On Tue, Dec 17, 2019 at 3:44 PM Timo Walther <[hidden email]> wrote:
>
> > Hi Becket,
> >
> > I completely agree with Dawid's suggestion. The information about the
> > boundedness should come out of the source. Because most of the streaming
> > sources can be made bounded based on some connector specific criterion.
> > In Kafka, it would be an end offset or end timestamp but in any case
> > having just a env.boundedSource() is not enough because parameters for
> > making the source bounded are missing.
> >
> > I suggest to have a simple `isBounded(): Boolean` flag in every source
> > that might be influenced by a connector builder as Dawid mentioned.
> >
> > For type safety during programming, we can still go with *Final state
> > 1*. By having a env.source() vs env.boundedSource(). The latter would
> > just enforce that the boolean flag is set to `true` and could make
> > bounded operations available (if we need that actually).
> >
> > However, I don't think that we should start making a unified Table API
> > ununified again. Boundedness is an optimization property. Every bounded
> > operation can also executed in an unbounded way using updates/retraction
> > or watermarks.
> >
> > Regards,
> > Timo
> >
> >
> > On 15.12.19 14:22, Becket Qin wrote:
> > > Hi Dawid and Jark,
> > >
> > > I think the discussion ultimately boils down to the question that which
> > one
> > > of the following two final states do we want? Once we make this
> decision,
> > > everything else can be naturally derived.
> > >
> > > *Final state 1*: Separate API for bounded / unbounded DataStream &
> Table.
> > > That means any code users write will be valid at the point when they
> > write
> > > the code. This is similar to having type safety check at programming
> > time.
> > > For example,
> > >
> > > BoundedDataStream extends DataStream {
> > > // Operations only available for bounded data.
> > > BoundedDataStream sort(...);
> > >
> > > // Interaction with another BoundedStream returns a Bounded stream.
> > > BoundedJoinedDataStream join(BoundedDataStream other)
> > >
> > > // Interaction with another unbounded stream returns an unbounded
> stream.
> > > JoinedDataStream join(DataStream other)
> > > }
> > >
> > > BoundedTable extends Table {
> > >    // Bounded only operation.
> > > BoundedTable sort(...);
> > >
> > > // Interaction with another BoundedTable returns a BoundedTable.
> > > BoundedTable join(BoundedTable other)
> > >
> > > // Interaction with another unbounded table returns an unbounded table.
> > > Table join(Table other)
> > > }
> > >
> > > *Final state 2*: One unified API for bounded / unbounded DataStream /
> > > Table.
> > > That unified API may throw exception at DAG compilation time if an
> > invalid
> > > operation is tried. This is what Table API currently follows.
> > >
> > > DataStream {
> > > // Throws exception if the DataStream is unbounded.
> > > DataStream sort();
> > > // Get boundedness.
> > > Boundedness getBoundedness();
> > > }
> > >
> > > Table {
> > > // Throws exception if the table has infinite rows.
> > > Table orderBy();
> > >
> > > // Get boundedness.
> > > Boundedness getBoundedness();
> > > }
> > >
> > >>From what I understand, there is no consensus so far on this decision
> > yet.
> > > Whichever final state we choose, we need to make it consistent across
> the
> > > entire project. We should avoid the case that Table follows one final
> > state
> > > while DataStream follows another. Some arguments I am aware of from
> both
> > > sides so far are following:
> > >
> > > Arguments for final state 1:
> > > 1a) Clean API with method safety check at programming time.
> > > 1b) (Counter 2b) Although SQL does not have programming time error
> > check, SQL
> > > is not really a "programming language" per se. So SQL can be different
> > from
> > > Table and DataStream.
> > > 1c)  Although final state 2 seems making it easier for SQL to use given
> > it
> > > is more "config based" than "parameter based", final state 1 can
> probably
> > > also meet what SQL wants by wrapping the Source in TableSource /
> > > TableSourceFactory API if needed.
> > >
> > > Arguments for final state 2:
> > > 2a) The Source API itself seems already sort of following the unified
> API
> > > pattern.
> > > 2b) There is no "programming time" method error check in SQL case, so
> we
> > > cannot really achieve final state 1 across the board.
> > > 2c) It is an easier path given our current status, i.e. Table is
> already
> > > following final state 2.
> > > 2d) Users can always explicitly check the boundedness if they want to.
> > >
> > > As I mentioned earlier, my initial thought was also to have a
> > > "configuration based" Source rather than a "parameter based" Source. So
> > it
> > > is completely possible that I missed some important consideration or
> > design
> > > principles that we want to enforce for the project. It would be good
> > > if @Stephan
> > > Ewen <[hidden email]> and @Aljoscha Krettek <
> > [hidden email]> can
> > > also provide more thoughts on this.
> > >
> > >
> > > Re: Jingsong
> > >
> > > As you said, there are some batched system source, like parquet/orc
> > source.
> > >> Could we have the batch emit interface to improve performance? The
> > queue of
> > >> per record may cause performance degradation.
> > >
> > >
> > > The current interface does not necessarily cause performance problem
> in a
> > > multi-threading case. In fact, the base implementation allows
> > SplitReaders
> > > to add a batch <E> of records<T> to the records queue<E>, so each
> element
> > > in the records queue would be a batch <E>. In this case, when the main
> > > thread polls records, it will take a batch <E> of records <T> from the
> > > shared records queue and process the records <T> in a batch manner.
> > >
> > > Thanks,
> > >
> > > Jiangjie (Becket) Qin
> > >
> > > On Thu, Dec 12, 2019 at 1:29 PM Jingsong Li <[hidden email]>
> > wrote:
> > >
> > >> Hi Becket,
> > >>
> > >> I also have some performance concerns too.
> > >>
> > >> If I understand correctly, SourceOutput will emit data per record into
> > the
> > >> queue? I'm worried about the multithreading performance of this queue.
> > >>
> > >>> One example is some batched messaging systems which only have an
> offset
> > >> for the entire batch instead of individual messages in the batch.
> > >>
> > >> As you said, there are some batched system source, like parquet/orc
> > source.
> > >> Could we have the batch emit interface to improve performance? The
> > queue of
> > >> per record may cause performance degradation.
> > >>
> > >> Best,
> > >> Jingsong Lee
> > >>
> > >> On Thu, Dec 12, 2019 at 9:15 AM Jark Wu <[hidden email]> wrote:
> > >>
> > >>> Hi Becket,
> > >>>
> > >>> I think Dawid explained things clearly and makes a lot of sense.
> > >>> I'm also in favor of #2, because #1 doesn't work for our future
> unified
> > >>> envrionment.
> > >>>
> > >>> You can see the vision in this documentation [1]. In the future, we
> > would
> > >>> like to
> > >>> drop the global streaming/batch mode in SQL (i.e.
> > >>> EnvironmentSettings#inStreamingMode/inBatchMode).
> > >>> A source is bounded or unbounded once defined, so queries can be
> > inferred
> > >>> from source to run
> > >>> in streaming or batch or hybrid mode. However, in #1, we will lose
> this
> > >>> ability because the framework
> > >>> doesn't know whether the source is bounded or unbounded.
> > >>>
> > >>> Best,
> > >>> Jark
> > >>>
> > >>>
> > >>> [1]:
> > >>>
> > >>>
> > >>
> >
> https://docs.google.com/document/d/1yrKXEIRATfxHJJ0K3t6wUgXAtZq8D-XgvEnvl2uUcr0/edit#heading=h.v4ib17buma1p
> > >>>
> > >>> On Wed, 11 Dec 2019 at 20:52, Piotr Nowojski <[hidden email]>
> > >> wrote:
> > >>>
> > >>>> Hi,
> > >>>>
> > >>>> Regarding the:
> > >>>>
> > >>>> Collection<E> getNextRecords()
> > >>>>
> > >>>> I’m pretty sure such design would unfortunately impact the
> performance
> > >>>> (accessing and potentially creating the collection on the hot path).
> > >>>>
> > >>>> Also the
> > >>>>
> > >>>> InputStatus emitNext(DataOutput<T> output) throws Exception;
> > >>>> or
> > >>>> Status pollNext(SourceOutput<T> sourceOutput) throws Exception;
> > >>>>
> > >>>> Gives us some opportunities in the future, to allow Source hot
> looping
> > >>>> inside, until it receives some signal “please exit because of some
> > >>> reasons”
> > >>>> (output collector could return such hint upon collecting the
> result).
> > >> But
> > >>>> that’s another topic outside of this FLIP’s scope.
> > >>>>
> > >>>> Piotrek
> > >>>>
> > >>>>> On 11 Dec 2019, at 10:41, Till Rohrmann <[hidden email]>
> > >> wrote:
> > >>>>>
> > >>>>> Hi Becket,
> > >>>>>
> > >>>>> quick clarification from my side because I think you misunderstood
> my
> > >>>>> question. I did not suggest to let the SourceReader return only a
> > >>> single
> > >>>>> record at a time when calling getNextRecords. As the return type
> > >>>> indicates,
> > >>>>> the method can return an arbitrary number of records.
> > >>>>>
> > >>>>> Cheers,
> > >>>>> Till
> > >>>>>
> > >>>>> On Wed, Dec 11, 2019 at 10:13 AM Dawid Wysakowicz <
> > >>>> [hidden email] <mailto:[hidden email]>>
> > >>>>> wrote:
> > >>>>>
> > >>>>>> Hi Becket,
> > >>>>>>
> > >>>>>> Issue #1 - Design of Source interface
> > >>>>>>
> > >>>>>> I mentioned the lack of a method like
> > >>>> Source#createEnumerator(Boundedness
> > >>>>>> boundedness, SplitEnumeratorContext context), because without the
> > >>>> current
> > >>>>>> proposal is not complete/does not work.
> > >>>>>>
> > >>>>>> If we say that boundedness is an intrinsic property of a source
> imo
> > >> we
> > >>>>>> don't need the Source#createEnumerator(Boundedness boundedness,
> > >>>>>> SplitEnumeratorContext context) method.
> > >>>>>>
> > >>>>>> Assuming a source from my previous example:
> > >>>>>>
> > >>>>>> Source source = KafkaSource.builder()
> > >>>>>>   ...
> > >>>>>>   .untilTimestamp(...)
> > >>>>>>   .build()
> > >>>>>>
> > >>>>>> Would the enumerator differ if created like
> > >>>>>> source.createEnumerator(CONTINUOUS_UNBOUNDED, ...) vs source
> > >>>>>> .createEnumerator(BOUNDED, ...)? I know I am repeating myself, but
> > >>> this
> > >>>> is
> > >>>>>> the part that my opinion differ the most from the current
> proposal.
> > >> I
> > >>>>>> really think it should always be the source that tells if it is
> > >>> bounded
> > >>>> or
> > >>>>>> not. In the current proposal methods continousSource/boundedSource
> > >>>> somewhat
> > >>>>>> reconfigure the source, which I think is misleading.
> > >>>>>>
> > >>>>>> I think a call like:
> > >>>>>>
> > >>>>>> Source source = KafkaSource.builder()
> > >>>>>>   ...
> > >>>>>>   .readContinously() / readUntilLatestOffset() /
> readUntilTimestamp
> > /
> > >>>> readUntilOffsets / ...
> > >>>>>>   .build()
> > >>>>>>
> > >>>>>> is way cleaner (and expressive) than
> > >>>>>>
> > >>>>>> Source source = KafkaSource.builder()
> > >>>>>>   ...
> > >>>>>>   .build()
> > >>>>>>
> > >>>>>>
> > >>>>>> env.continousSource(source) // which actually underneath would
> call
> > >>>> createEnumerator(CONTINUOUS, ctx) which would be equivalent to
> > >>>> source.readContinously().createEnumerator(ctx)
> > >>>>>> // or
> > >>>>>> env.boundedSource(source) // which actually underneath would call
> > >>>> createEnumerator(BOUNDED, ctx) which would be equivalent to
> > >>>> source.readUntilLatestOffset().createEnumerator(ctx)
> > >>>>>>
> > >>>>>>
> > >>>>>> Sorry for the comparison, but to me it seems there is too much
> magic
> > >>>>>> happening underneath those two calls.
> > >>>>>>
> > >>>>>> I really believe the Source interface should have getBoundedness
> > >>> method
> > >>>>>> instead of (supportBoundedness) + createEnumerator(Boundedness,
> ...)
> > >>>>>>
> > >>>>>>
> > >>>>>> Issue #2 - Design of
> > >>>>>> ExecutionEnvironment#source()/continuousSource()/boundedSource()
> > >>>>>>
> > >>>>>> As you might have guessed I am slightly in favor of option #2
> > >>> modified.
> > >>>>>> Yes I am aware every step of the dag would have to be able to say
> if
> > >>> it
> > >>>> is
> > >>>>>> bounded or not. I have a feeling it would be easier to express
> cross
> > >>>>>> bounded/unbounded operations, but I must admit I have not thought
> it
> > >>>>>> through thoroughly, In the spirit of batch is just a special case
> of
> > >>>>>> streaming I thought BoundedStream would extend from DataStream.
> > >>> Correct
> > >>>> me
> > >>>>>> if I am wrong. In such a setup the cross bounded/unbounded
> operation
> > >>>> could
> > >>>>>> be expressed quite easily I think:
> > >>>>>>
> > >>>>>> DataStream {
> > >>>>>>   DataStream join(DataStream, ...); // we could not really tell if
> > >> the
> > >>>> result is bounded or not, but because bounded stream is a special
> case
> > >> of
> > >>>> unbounded the API object is correct, irrespective if the left or
> right
> > >>> side
> > >>>> of the join is bounded
> > >>>>>> }
> > >>>>>>
> > >>>>>> BoundedStream extends DataStream {
> > >>>>>>   BoundedStream join(BoundedStream, ...); // only if both sides
> are
> > >>>> bounded the result can be bounded as well. However we do have access
> > to
> > >>> the
> > >>>> DataStream#join here, so you can still join with a DataStream
> > >>>>>> }
> > >>>>>>
> > >>>>>>
> > >>>>>> On the other hand I also see benefits of two completely disjointed
> > >>> APIs,
> > >>>>>> as we could prohibit some streaming calls in the bounded API. I
> > >> can't
> > >>>> think
> > >>>>>> of any unbounded operators that could not be implemented for
> bounded
> > >>>> stream.
> > >>>>>>
> > >>>>>> Besides I think we both agree we don't like the method:
> > >>>>>>
> > >>>>>> DataStream boundedStream(Source)
> > >>>>>>
> > >>>>>> suggested in the current state of the FLIP. Do we ? :)
> > >>>>>>
> > >>>>>> Best,
> > >>>>>>
> > >>>>>> Dawid
> > >>>>>>
> > >>>>>> On 10/12/2019 18:57, Becket Qin wrote:
> > >>>>>>
> > >>>>>> Hi folks,
> > >>>>>>
> > >>>>>> Thanks for the discussion, great feedback. Also thanks Dawid for
> the
> > >>>>>> explanation, it is much clearer now.
> > >>>>>>
> > >>>>>> One thing that is indeed missing from the FLIP is how the
> > >> boundedness
> > >>> is
> > >>>>>> passed to the Source implementation. So the API should be
> > >>>>>> Source#createEnumerator(Boundedness boundedness,
> > >>> SplitEnumeratorContext
> > >>>>>> context)
> > >>>>>> And we can probably remove the
> Source#supportBoundedness(Boundedness
> > >>>>>> boundedness) method.
> > >>>>>>
> > >>>>>> Assuming we have that, we are essentially choosing from one of the
> > >>>>>> following two options:
> > >>>>>>
> > >>>>>> Option 1:
> > >>>>>> // The source is continuous source, and only unbounded operations
> > >> can
> > >>> be
> > >>>>>> performed.
> > >>>>>> DataStream<Type> datastream = env.continuousSource(someSource);
> > >>>>>>
> > >>>>>> // The source is bounded source, both bounded and unbounded
> > >> operations
> > >>>> can
> > >>>>>> be performed.
> > >>>>>> BoundedDataStream<Type> boundedDataStream =
> > >>>> env.boundedSource(someSource);
> > >>>>>>
> > >>>>>>   - Pros:
> > >>>>>>        a) explicit boundary between bounded / unbounded streams,
> it
> > >> is
> > >>>>>> quite simple and clear to the users.
> > >>>>>>   - Cons:
> > >>>>>>        a) For applications that do not involve bounded operations,
> > >> they
> > >>>>>> still have to call different API to distinguish bounded /
> unbounded
> > >>>> streams.
> > >>>>>>        b) No support for bounded stream to run in a streaming
> > runtime
> > >>>>>> setting, i.e. scheduling and operators behaviors.
> > >>>>>>
> > >>>>>>
> > >>>>>> Option 2:
> > >>>>>> // The source is either bounded or unbounded, but only unbounded
> > >>>> operations
> > >>>>>> could be performed on the returned DataStream.
> > >>>>>> DataStream<Type> dataStream = env.source(someSource);
> > >>>>>>
> > >>>>>> // The source must be a bounded source, otherwise exception is
> > >> thrown.
> > >>>>>> BoundedDataStream<Type> boundedDataStream =
> > >>>>>> env.boundedSource(boundedSource);
> > >>>>>>
> > >>>>>> The pros and cons are exactly the opposite of option 1.
> > >>>>>>   - Pros:
> > >>>>>>        a) For applications that do not involve bounded operations,
> > >> they
> > >>>>>> still have to call different API to distinguish bounded /
> unbounded
> > >>>> streams.
> > >>>>>>        b) Support for bounded stream to run in a streaming runtime
> > >>>> setting,
> > >>>>>> i.e. scheduling and operators behaviors.
> > >>>>>>   - Cons:
> > >>>>>>        a) Bounded / unbounded streams are kind of mixed, i.e.
> given
> > a
> > >>>>>> DataStream, it is not clear whether it is bounded or not, unless
> you
> > >>>> have
> > >>>>>> the access to its source.
> > >>>>>>
> > >>>>>>
> > >>>>>> If we only think from the Source API perspective, option 2 seems a
> > >>>> better
> > >>>>>> choice because functionality wise it is a superset of option 1, at
> > >> the
> > >>>> cost
> > >>>>>> of some seemingly acceptable ambiguity in the DataStream API.
> > >>>>>> But if we look at the DataStream API as a whole, option 1 seems a
> > >>>> clearer
> > >>>>>> choice. For example, some times a library may have to know
> whether a
> > >>>>>> certain task will finish or not. And it would be difficult to tell
> > >> if
> > >>>> the
> > >>>>>> input is a DataStream, unless additional information is provided
> all
> > >>> the
> > >>>>>> way from the Source. One possible solution is to have a *modified
> > >>>> option 2*
> > >>>>>> which adds a method to the DataStream API to indicate boundedness,
> > >>> such
> > >>>> as
> > >>>>>> getBoundedness(). It would solve the problem with a potential
> > >>> confusion
> > >>>> of
> > >>>>>> what is difference between a DataStream with getBoundedness()=true
> > >>> and a
> > >>>>>> BoundedDataStream. But that seems not super difficult to explain.
> > >>>>>>
> > >>>>>> So from API's perspective, I don't have a strong opinion between
> > >>>> *option 1*
> > >>>>>> and *modified option 2. *I like the cleanness of option 1, but
> > >>> modified
> > >>>>>> option 2 would be more attractive if we have concrete use case for
> > >> the
> > >>>>>> "Bounded stream with unbounded streaming runtime settings".
> > >>>>>>
> > >>>>>> Re: Till
> > >>>>>>
> > >>>>>>
> > >>>>>> Maybe this has already been asked before but I was wondering why
> the
> > >>>>>> SourceReader interface has the method pollNext which hands the
> > >>>>>> responsibility of outputting elements to the SourceReader
> > >>>> implementation?
> > >>>>>> Has this been done for backwards compatibility reasons with the
> old
> > >>>> source
> > >>>>>> interface? If not, then one could define a Collection<E>
> > >>>> getNextRecords()
> > >>>>>> method which returns the currently retrieved records and then the
> > >>> caller
> > >>>>>> emits them outside of the SourceReader. That way the interface
> would
> > >>> not
> > >>>>>> allow to implement an outputting loop where we never hand back
> > >> control
> > >>>> to
> > >>>>>> the caller. At the moment, this contract can be easily broken and
> is
> > >>>> only
> > >>>>>> mentioned loosely in the JavaDocs.
> > >>>>>>
> > >>>>>>
> > >>>>>> The primary reason we handover the SourceOutput to the
> SourceReader
> > >> is
> > >>>>>> because sometimes it is difficult for a SourceReader to emit one
> > >>> record
> > >>>> at
> > >>>>>> a time. One example is some batched messaging systems which only
> > >> have
> > >>> an
> > >>>>>> offset for the entire batch instead of individual messages in the
> > >>>> batch. In
> > >>>>>> that case, returning one record at a time would leave the
> > >> SourceReader
> > >>>> in
> > >>>>>> an uncheckpointable state because they can only checkpoint at the
> > >>> batch
> > >>>>>> boundaries.
> > >>>>>>
> > >>>>>> Thanks,
> > >>>>>>
> > >>>>>> Jiangjie (Becket) Qin
> > >>>>>>
> > >>>>>> On Tue, Dec 10, 2019 at 5:33 PM Till Rohrmann <
> [hidden email]
> > >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> > >>>> [hidden email]>> wrote:
> > >>>>>>
> > >>>>>>
> > >>>>>> Hi everyone,
> > >>>>>>
> > >>>>>> thanks for drafting this FLIP. It reads very well.
> > >>>>>>
> > >>>>>> Concerning Dawid's proposal, I tend to agree. The boundedness
> could
> > >>> come
> > >>>>>> from the source and tell the system how to treat the operator
> > >>>> (scheduling
> > >>>>>> wise). From a user's perspective it should be fine to get back a
> > >>>> DataStream
> > >>>>>> when calling env.source(boundedSource) if he does not need special
> > >>>>>> operations defined on a BoundedDataStream. If he needs this, then
> > >> one
> > >>>> could
> > >>>>>> use the method BoundedDataStream env.boundedSource(boundedSource).
> > >>>>>>
> > >>>>>> If possible, we could enforce the proper usage of
> > >> env.boundedSource()
> > >>> by
> > >>>>>> introducing a BoundedSource type so that one cannot pass an
> > >>>>>> unbounded source to it. That way users would not be able to shoot
> > >>>>>> themselves in the foot.
> > >>>>>>
> > >>>>>> Maybe this has already been asked before but I was wondering why
> the
> > >>>>>> SourceReader interface has the method pollNext which hands the
> > >>>>>> responsibility of outputting elements to the SourceReader
> > >>>> implementation?
> > >>>>>> Has this been done for backwards compatibility reasons with the
> old
> > >>>> source
> > >>>>>> interface? If not, then one could define a Collection<E>
> > >>>> getNextRecords()
> > >>>>>> method which returns the currently retrieved records and then the
> > >>> caller
> > >>>>>> emits them outside of the SourceReader. That way the interface
> would
> > >>> not
> > >>>>>> allow to implement an outputting loop where we never hand back
> > >> control
> > >>>> to
> > >>>>>> the caller. At the moment, this contract can be easily broken and
> is
> > >>>> only
> > >>>>>> mentioned loosely in the JavaDocs.
> > >>>>>>
> > >>>>>> Cheers,
> > >>>>>> Till
> > >>>>>>
> > >>>>>> On Tue, Dec 10, 2019 at 7:49 AM Jingsong Li <
> [hidden email]
> > >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> > >>>> [hidden email]>>
> > >>>>>> wrote:
> > >>>>>>
> > >>>>>>
> > >>>>>> Hi all,
> > >>>>>>
> > >>>>>> I think current design is good.
> > >>>>>>
> > >>>>>> My understanding is:
> > >>>>>>
> > >>>>>> For execution mode: bounded mode and continuous mode, It's totally
> > >>>>>> different. I don't think we have the ability to integrate the two
> > >>> models
> > >>>>>>
> > >>>>>> at
> > >>>>>>
> > >>>>>> present. It's about scheduling, memory, algorithms, States, etc.
> we
> > >>>>>> shouldn't confuse them.
> > >>>>>>
> > >>>>>> For source capabilities: only bounded, only continuous, both
> bounded
> > >>> and
> > >>>>>> continuous.
> > >>>>>> I think Kafka is a source that can be ran both bounded
> > >>>>>> and continuous execution mode.
> > >>>>>> And Kafka with end offset should be ran both bounded
> > >>>>>> and continuous execution mode.  Using apache Beam with Flink
> > >> runner, I
> > >>>>>>
> > >>>>>> used
> > >>>>>>
> > >>>>>> to run a "bounded" Kafka in streaming mode. For our previous
> > >>> DataStream,
> > >>>>>>
> > >>>>>> it
> > >>>>>>
> > >>>>>> is not necessarily required that the source cannot be bounded.
> > >>>>>>
> > >>>>>> So it is my thought for Dawid's question:
> > >>>>>> 1.pass a bounded source to continuousSource() +1
> > >>>>>> 2.pass a continuous source to boundedSource() -1, should throw
> > >>>> exception.
> > >>>>>>
> > >>>>>> In StreamExecutionEnvironment, continuousSource and boundedSource
> > >>> define
> > >>>>>> the execution mode. It defines a clear boundary of execution mode.
> > >>>>>>
> > >>>>>> Best,
> > >>>>>> Jingsong Lee
> > >>>>>>
> > >>>>>> On Tue, Dec 10, 2019 at 10:37 AM Jark Wu <[hidden email]
> <mailto:
> > >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> > wrote:
> > >>>>>>
> > >>>>>>
> > >>>>>> I agree with Dawid's point that the boundedness information should
> > >>> come
> > >>>>>> from the source itself (e.g. the end timestamp), not through
> > >>>>>> env.boundedSouce()/continuousSource().
> > >>>>>> I think if we want to support something like `env.source()` that
> > >>> derive
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> execution mode from source, `supportsBoundedness(Boundedness)`
> > >>>>>> method is not enough, because we don't know whether it is bounded
> or
> > >>>>>>
> > >>>>>> not.
> > >>>>>>
> > >>>>>> Best,
> > >>>>>> Jark
> > >>>>>>
> > >>>>>>
> > >>>>>> On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <
> > >> [hidden email]
> > >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> > >>>> [hidden email]>>
> > >>>>>> wrote:
> > >>>>>>
> > >>>>>>
> > >>>>>> One more thing. In the current proposal, with the
> > >>>>>> supportsBoundedness(Boundedness) method and the boundedness coming
> > >>>>>>
> > >>>>>> from
> > >>>>>>
> > >>>>>> either continuousSource or boundedSource I could not find how this
> > >>>>>> information is fed back to the SplitEnumerator.
> > >>>>>>
> > >>>>>> Best,
> > >>>>>>
> > >>>>>> Dawid
> > >>>>>>
> > >>>>>> On 09/12/2019 13:52, Becket Qin wrote:
> > >>>>>>
> > >>>>>> Hi Dawid,
> > >>>>>>
> > >>>>>> Thanks for the comments. This actually brings another relevant
> > >>>>>>
> > >>>>>> question
> > >>>>>>
> > >>>>>> about what does a "bounded source" imply. I actually had the same
> > >>>>>> impression when I look at the Source API. Here is what I
> understand
> > >>>>>>
> > >>>>>> after
> > >>>>>>
> > >>>>>> some discussion with Stephan. The bounded source has the following
> > >>>>>>
> > >>>>>> impacts.
> > >>>>>>
> > >>>>>> 1. API validity.
> > >>>>>> - A bounded source generates a bounded stream so some operations
> > >>>>>>
> > >>>>>> that
> > >>>>>>
> > >>>>>> only
> > >>>>>>
> > >>>>>> works for bounded records would be performed, e.g. sort.
> > >>>>>> - To expose these bounded stream only APIs, there are two options:
> > >>>>>>      a. Add them to the DataStream API and throw exception if a
> > >>>>>>
> > >>>>>> method
> > >>>>>>
> > >>>>>> is
> > >>>>>>
> > >>>>>> called on an unbounded stream.
> > >>>>>>      b. Create a BoundedDataStream class which is returned from
> > >>>>>> env.boundedSource(), while DataStream is returned from
> > >>>>>>
> > >>>>>> env.continousSource().
> > >>>>>>
> > >>>>>> Note that this cannot be done by having single
> > >>>>>>
> > >>>>>> env.source(theSource)
> > >>>>>>
> > >>>>>> even
> > >>>>>>
> > >>>>>> the Source has a getBoundedness() method.
> > >>>>>>
> > >>>>>> 2. Scheduling
> > >>>>>> - A bounded source could be computed stage by stage without
> > >>>>>>
> > >>>>>> bringing
> > >>>>>>
> > >>>>>> up
> > >>>>>>
> > >>>>>> all
> > >>>>>>
> > >>>>>> the tasks at the same time.
> > >>>>>>
> > >>>>>> 3. Operator behaviors
> > >>>>>> - A bounded source indicates the records are finite so some
> > >>>>>>
> > >>>>>> operators
> > >>>>>>
> > >>>>>> can
> > >>>>>>
> > >>>>>> wait until it receives all the records before it starts the
> > >>>>>>
> > >>>>>> processing.
> > >>>>>>
> > >>>>>> In the above impact, only 1 is relevant to the API design. And the
> > >>>>>>
> > >>>>>> current
> > >>>>>>
> > >>>>>> proposal in FLIP-27 is following 1.b.
> > >>>>>>
> > >>>>>> // boundedness depends of source property, imo this should always
> > >>>>>>
> > >>>>>> be
> > >>>>>>
> > >>>>>> preferred
> > >>>>>>
> > >>>>>>
> > >>>>>> DataStream<MyType> stream = env.source(theSource);
> > >>>>>>
> > >>>>>>
> > >>>>>> In your proposal, does DataStream have bounded stream only
> methods?
> > >>>>>>
> > >>>>>> It
> > >>>>>>
> > >>>>>> looks it should have, otherwise passing a bounded Source to
> > >>>>>>
> > >>>>>> env.source()
> > >>>>>>
> > >>>>>> would be confusing. In that case, we will essentially do 1.a if an
> > >>>>>> unbounded Source is created from env.source(unboundedSource).
> > >>>>>>
> > >>>>>> If we have the methods only supported for bounded streams in
> > >>>>>>
> > >>>>>> DataStream,
> > >>>>>>
> > >>>>>> it
> > >>>>>>
> > >>>>>> seems a little weird to have a separate BoundedDataStream
> > >>>>>>
> > >>>>>> interface.
> > >>>>>>
> > >>>>>> Am I understand it correctly?
> > >>>>>>
> > >>>>>> Thanks,
> > >>>>>>
> > >>>>>> Jiangjie (Becket) Qin
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>> On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <
> > >>>>>>
> > >>>>>> [hidden email] <mailto:[hidden email]>>
> > >>>>>>
> > >>>>>> wrote:
> > >>>>>>
> > >>>>>>
> > >>>>>> Hi all,
> > >>>>>>
> > >>>>>> Really well written proposal and very important one. I must admit
> > >>>>>>
> > >>>>>> I
> > >>>>>>
> > >>>>>> have
> > >>>>>>
> > >>>>>> not understood all the intricacies of it yet.
> > >>>>>>
> > >>>>>> One question I have though is about where does the information
> > >>>>>>
> > >>>>>> about
> > >>>>>>
> > >>>>>> boundedness come from. I think in most cases it is a property of
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> source. As you described it might be e.g. end offset, a flag
> > >>>>>>
> > >>>>>> should
> > >>>>>>
> > >>>>>> it
> > >>>>>>
> > >>>>>> monitor new splits etc. I think it would be a really nice use case
> > >>>>>>
> > >>>>>> to
> > >>>>>>
> > >>>>>> be
> > >>>>>>
> > >>>>>> able to say:
> > >>>>>>
> > >>>>>> new KafkaSource().readUntil(long timestamp),
> > >>>>>>
> > >>>>>> which could work as an "end offset". Moreover I think all Bounded
> > >>>>>>
> > >>>>>> sources
> > >>>>>>
> > >>>>>> support continuous mode, but no intrinsically continuous source
> > >>>>>>
> > >>>>>> support
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> Bounded mode. If I understood the proposal correctly it suggest
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> boundedness sort of "comes" from the outside of the source, from
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> invokation of either boundedStream or continousSource.
> > >>>>>>
> > >>>>>> I am wondering if it would make sense to actually change the
> > >>>>>>
> > >>>>>> method
> > >>>>>>
> > >>>>>> boolean Source#supportsBoundedness(Boundedness)
> > >>>>>>
> > >>>>>> to
> > >>>>>>
> > >>>>>> Boundedness Source#getBoundedness().
> > >>>>>>
> > >>>>>> As for the methods #boundedSource, #continousSource, assuming the
> > >>>>>> boundedness is property of the source they do not affect how the
> > >>>>>>
> > >>>>>> enumerator
> > >>>>>>
> > >>>>>> works, but mostly how the dag is scheduled, right? I am not
> > >>>>>>
> > >>>>>> against
> > >>>>>>
> > >>>>>> those
> > >>>>>>
> > >>>>>> methods, but I think it is a very specific use case to actually
> > >>>>>>
> > >>>>>> override
> > >>>>>>
> > >>>>>> the property of the source. In general I would expect users to
> > >>>>>>
> > >>>>>> only
> > >>>>>>
> > >>>>>> call
> > >>>>>>
> > >>>>>> env.source(theSource), where the source tells if it is bounded or
> > >>>>>>
> > >>>>>> not. I
> > >>>>>>
> > >>>>>> would suggest considering following set of methods:
> > >>>>>>
> > >>>>>> // boundedness depends of source property, imo this should always
> > >>>>>>
> > >>>>>> be
> > >>>>>>
> > >>>>>> preferred
> > >>>>>>
> > >>>>>> DataStream<MyType> stream = env.source(theSource);
> > >>>>>>
> > >>>>>>
> > >>>>>> // always continous execution, whether bounded or unbounded source
> > >>>>>>
> > >>>>>> DataStream<MyType> boundedStream = env.continousSource(theSource);
> > >>>>>>
> > >>>>>> // imo this would make sense if the BoundedDataStream provides
> > >>>>>>
> > >>>>>> additional features unavailable for continous mode
> > >>>>>>
> > >>>>>> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
> > >>>>>>
> > >>>>>>
> > >>>>>> Best,
> > >>>>>>
> > >>>>>> Dawid
> > >>>>>>
> > >>>>>>
> > >>>>>> On 04/12/2019 11:25, Stephan Ewen wrote:
> > >>>>>>
> > >>>>>> Thanks, Becket, for updating this.
> > >>>>>>
> > >>>>>> I agree with moving the aspects you mentioned into separate FLIPs
> > >>>>>>
> > >>>>>> -
> > >>>>>>
> > >>>>>> this
> > >>>>>>
> > >>>>>> one way becoming unwieldy in size.
> > >>>>>>
> > >>>>>> +1 to the FLIP in its current state. Its a very detailed write-up,
> > >>>>>>
> > >>>>>> nicely
> > >>>>>>
> > >>>>>> done!
> > >>>>>>
> > >>>>>> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]
> > >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> > >>>> [hidden email]>>
> > >>>>>>
> > >>>>>> <
> > >>>>>>
> > >>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> > >>>>>>
> > >>>>>> Hi all,
> > >>>>>>
> > >>>>>> Sorry for the long belated update. I have updated FLIP-27 wiki
> > >>>>>>
> > >>>>>> page
> > >>>>>>
> > >>>>>> with
> > >>>>>>
> > >>>>>> the latest proposals. Some noticeable changes include:
> > >>>>>> 1. A new generic communication mechanism between SplitEnumerator
> > >>>>>>
> > >>>>>> and
> > >>>>>>
> > >>>>>> SourceReader.
> > >>>>>> 2. Some detail API method signature changes.
> > >>>>>>
> > >>>>>> We left a few things out of this FLIP and will address them in
> > >>>>>>
> > >>>>>> separate
> > >>>>>>
> > >>>>>> FLIPs. Including:
> > >>>>>> 1. Per split event time.
> > >>>>>> 2. Event time alignment.
> > >>>>>> 3. Fine grained failover for SplitEnumerator failure.
> > >>>>>>
> > >>>>>> Please let us know if you have any question.
> > >>>>>>
> > >>>>>> Thanks,
> > >>>>>>
> > >>>>>> Jiangjie (Becket) Qin
> > >>>>>>
> > >>>>>> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]
> > >>> <mailto:
> > >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> > >>>>>>
> > >>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> > >>>>>>
> > >>>>>> Hi  Łukasz!
> > >>>>>>
> > >>>>>> Becket and me are working hard on figuring out the last details
> > >>>>>>
> > >>>>>> and
> > >>>>>>
> > >>>>>> implementing the first PoC. We would update the FLIP hopefully
> > >>>>>>
> > >>>>>> next
> > >>>>>>
> > >>>>>> week.
> > >>>>>>
> > >>>>>> There is a fair chance that a first version of this will be in
> > >>>>>>
> > >>>>>> 1.10,
> > >>>>>>
> > >>>>>> but
> > >>>>>>
> > >>>>>> I
> > >>>>>>
> > >>>>>> think it will take another release to battle test it and migrate
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> connectors.
> > >>>>>>
> > >>>>>> Best,
> > >>>>>> Stephan
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <[hidden email]
> > >>>> <mailto:[hidden email]>
> > >>>>>>
> > >>>>>> <
> > >>>>>>
> > >>>>>> [hidden email] <mailto:[hidden email]>>
> > >>>>>>
> > >>>>>> wrote:
> > >>>>>>
> > >>>>>> Hi,
> > >>>>>>
> > >>>>>> This proposal looks very promising for us. Do you have any plans
> > >>>>>>
> > >>>>>> in
> > >>>>>>
> > >>>>>> which
> > >>>>>>
> > >>>>>> Flink release it is going to be released? We are thinking on
> > >>>>>>
> > >>>>>> using a
> > >>>>>>
> > >>>>>> Data
> > >>>>>>
> > >>>>>> Set API for our future use cases but on the other hand Data Set
> > >>>>>>
> > >>>>>> API
> > >>>>>>
> > >>>>>> is
> > >>>>>>
> > >>>>>> going to be deprecated so using proposed bounded data streams
> > >>>>>>
> > >>>>>> solution
> > >>>>>>
> > >>>>>> could be more viable in the long term.
> > >>>>>>
> > >>>>>> Thanks,
> > >>>>>> Łukasz
> > >>>>>>
> > >>>>>> On 2019/10/01 15:48:03, Thomas Weise <[hidden email]
> > >> <mailto:
> > >>>> [hidden email]>> <[hidden email] <mailto:
> > >>>> [hidden email]>> <
> > >>>>>>
> > >>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> > >>>>>>
> > >>>>>> Thanks for putting together this proposal!
> > >>>>>>
> > >>>>>> I see that the "Per Split Event Time" and "Event Time Alignment"
> > >>>>>>
> > >>>>>> sections
> > >>>>>>
> > >>>>>> are still TBD.
> > >>>>>>
> > >>>>>> It would probably be good to flesh those out a bit before
> > >>>>>>
> > >>>>>> proceeding
> > >>>>>>
> > >>>>>> too
> > >>>>>>
> > >>>>>> far
> > >>>>>>
> > >>>>>> as the event time alignment will probably influence the
> > >>>>>>
> > >>>>>> interaction
> > >>>>>>
> > >>>>>> with
> > >>>>>>
> > >>>>>> the split reader, specifically ReaderStatus
> > >>>>>>
> > >>>>>> emitNext(SourceOutput<E>
> > >>>>>>
> > >>>>>> output).
> > >>>>>>
> > >>>>>> We currently have only one implementation for event time alignment
> > >>>>>>
> > >>>>>> in
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> Kinesis consumer. The synchronization in that case takes place as
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> last
> > >>>>>>
> > >>>>>> step before records are emitted downstream (RecordEmitter). With
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> currently proposed interfaces, the equivalent can be implemented
> > >>>>>>
> > >>>>>> in
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> reader loop, although note that in the Kinesis consumer the per
> > >>>>>>
> > >>>>>> shard
> > >>>>>>
> > >>>>>> threads push records.
> > >>>>>>
> > >>>>>> Synchronization has not been implemented for the Kafka consumer
> > >>>>>>
> > >>>>>> yet.
> > >>>>>>
> > >>>>>> https://issues.apache.org/jira/browse/FLINK-12675 <
> > >>>> https://issues.apache.org/jira/browse/FLINK-12675>
> > >>>>>>
> > >>>>>> When I looked at it, I realized that the implementation will look
> > >>>>>>
> > >>>>>> quite
> > >>>>>>
> > >>>>>> different
> > >>>>>> from Kinesis because it needs to take place in the pull part,
> > >>>>>>
> > >>>>>> where
> > >>>>>>
> > >>>>>> records
> > >>>>>>
> > >>>>>> are taken from the Kafka client. Due to the multiplexing it cannot
> > >>>>>>
> > >>>>>> be
> > >>>>>>
> > >>>>>> done
> > >>>>>>
> > >>>>>> by blocking the split thread like it currently works for Kinesis.
> > >>>>>>
> > >>>>>> Reading
> > >>>>>>
> > >>>>>> from individual Kafka partitions needs to be controlled via
> > >>>>>>
> > >>>>>> pause/resume
> > >>>>>>
> > >>>>>> on the Kafka client.
> > >>>>>>
> > >>>>>> To take on that responsibility the split thread would need to be
> > >>>>>>
> > >>>>>> aware
> > >>>>>>
> > >>>>>> of
> > >>>>>>
> > >>>>>> the
> > >>>>>> watermarks or at least whether it should or should not continue to
> > >>>>>>
> > >>>>>> consume
> > >>>>>>
> > >>>>>> a given split and this may require a different SourceReader or
> > >>>>>>
> > >>>>>> SourceOutput
> > >>>>>>
> > >>>>>> interface.
> > >>>>>>
> > >>>>>> Thanks,
> > >>>>>> Thomas
> > >>>>>>
> > >>>>>>
> > >>>>>> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email]
> > >> <mailto:
> > >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]
> >>
> > >> <
> > >>>>>>
> > >>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> > >>>>>>
> > >>>>>> Hi Stephan,
> > >>>>>>
> > >>>>>> Thank you for feedback!
> > >>>>>> Will take a look at your branch before public discussing.
> > >>>>>>
> > >>>>>>
> > >>>>>> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]
> > >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> [hidden email]
> > >>>>
> > >>>>>>
> > >>>>>> <
> > >>>>>>
> > >>>>>> [hidden email] <mailto:[hidden email]>>
> > >>>>>>
> > >>>>>> wrote:
> > >>>>>>
> > >>>>>> Hi Biao!
> > >>>>>>
> > >>>>>> Thanks for reviving this. I would like to join this discussion,
> > >>>>>>
> > >>>>>> but
> > >>>>>>
> > >>>>>> am
> > >>>>>>
> > >>>>>> quite occupied with the 1.9 release, so can we maybe pause this
> > >>>>>>
> > >>>>>> discussion
> > >>>>>>
> > >>>>>> for a week or so?
> > >>>>>>
> > >>>>>> In the meantime I can share some suggestion based on prior
> > >>>>>>
> > >>>>>> experiments:
> > >>>>>>
> > >>>>>> How to do watermarks / timestamp extractors in a simpler and more
> > >>>>>>
> > >>>>>> flexible
> > >>>>>>
> > >>>>>> way. I think that part is quite promising should be part of the
> > >>>>>>
> > >>>>>> new
> > >>>>>>
> > >>>>>> source
> > >>>>>>
> > >>>>>> interface.
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>
> > >>>
> > >>
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> > >>>> <
> > >>>>
> > >>>
> > >>
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> > >>>>>
> > >>>>>>
> > >>>>>>
> > >>>>
> > >>>
> > >>
> >
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> > >>>> <
> > >>>>
> > >>>
> > >>
> >
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> > >>>>>
> > >>>>>>
> > >>>>>> Some experiments on how to build the source reader and its
> > >>>>>>
> > >>>>>> library
> > >>>>>>
> > >>>>>> for
> > >>>>>>
> > >>>>>> common threading/split patterns:
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>
> > >>>
> > >>
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> > >>>> <
> > >>>>
> > >>>
> > >>
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> > >>>>>
> > >>>>>>
> > >>>>>> Best,
> > >>>>>> Stephan
> > >>>>>>
> > >>>>>>
> > >>>>>> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]
> > >>> <mailto:
> > >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]
> >>
> > >> <
> > >>>>>>
> > >>>>>> [hidden email] <mailto:[hidden email]>>
> > >>>>>>
> > >>>>>> wrote:
> > >>>>>>
> > >>>>>> Hi devs,
> > >>>>>>
> > >>>>>> Since 1.9 is nearly released, I think we could get back to
> > >>>>>>
> > >>>>>> FLIP-27.
> > >>>>>>
> > >>>>>> I
> > >>>>>>
> > >>>>>> believe it should be included in 1.10.
> > >>>>>>
> > >>>>>> There are so many things mentioned in document of FLIP-27. [1] I
> > >>>>>>
> > >>>>>> think
> > >>>>>>
> > >>>>>> we'd better discuss them separately. However the wiki is not a
> > >>>>>>
> > >>>>>> good
> > >>>>>>
> > >>>>>> place
> > >>>>>>
> > >>>>>> to discuss. I wrote google doc about SplitReader API which
> > >>>>>>
> > >>>>>> misses
> > >>>>>>
> > >>>>>> some
> > >>>>>>
> > >>>>>> details in the document. [2]
> > >>>>>>
> > >>>>>> 1.
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>
> > >>>
> > >>
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> > >>>> <
> > >>>>
> > >>>
> > >>
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> > >>>>>
> > >>>>>>
> > >>>>>> 2.
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>
> > >>>
> > >>
> >
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> > >>>> <
> > >>>>
> > >>>
> > >>
> >
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> > >>>>>
> > >>>>>>
> > >>>>>> CC Stephan, Aljoscha, Piotrek, Becket
> > >>>>>>
> > >>>>>>
> > >>>>>> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email]
> > >> <mailto:
> > >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]
> >>
> > >> <
> > >>>>>>
> > >>>>>> [hidden email] <mailto:[hidden email]>>
> > >>>>>>
> > >>>>>> wrote:
> > >>>>>>
> > >>>>>> Hi Steven,
> > >>>>>> Thank you for the feedback. Please take a look at the document
> > >>>>>>
> > >>>>>> FLIP-27
> > >>>>>>
> > >>>>>> <
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>
> > >>>
> > >>
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> > >>>> <
> > >>>>
> > >>>
> > >>
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> > >>>>>
> > >>>>>>
> > >>>>>> which
> > >>>>>>
> > >>>>>> is updated recently. A lot of details of enumerator were added
> > >>>>>>
> > >>>>>> in
> > >>>>>>
> > >>>>>> this
> > >>>>>>
> > >>>>>> document. I think it would help.
> > >>>>>>
> > >>>>>> Steven Wu <[hidden email] <mailto:[hidden email]>> <
> > >>>> [hidden email] <mailto:[hidden email]>> <
> > >>> [hidden email]
> > >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> > >>>> [hidden email]>>
> > >>>>>>
> > >>>>>> 于2019年3月28日周四
> > >>>>>>
> > >>>>>> 下午12:52写道：
> > >>>>>>
> > >>>>>> This proposal mentioned that SplitEnumerator might run on the
> > >>>>>> JobManager or
> > >>>>>> in a single task on a TaskManager.
> > >>>>>>
> > >>>>>> if enumerator is a single task on a taskmanager, then the job
> > >>>>>>
> > >>>>>> DAG
> > >>>>>>
> > >>>>>> can
> > >>>>>>
> > >>>>>> never
> > >>>>>> been embarrassingly parallel anymore. That will nullify the
> > >>>>>>
> > >>>>>> leverage
> > >>>>>>
> > >>>>>> of
> > >>>>>>
> > >>>>>> fine-grained recovery for embarrassingly parallel jobs.
> > >>>>>>
> > >>>>>> It's not clear to me what's the implication of running
> > >>>>>>
> > >>>>>> enumerator
> > >>>>>>
> > >>>>>> on
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> jobmanager. So I will leave that out for now.
> > >>>>>>
> > >>>>>> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email]
> > >> <mailto:
> > >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]
> >>
> > >> <
> > >>>>>>
> > >>>>>> [hidden email] <mailto:[hidden email]>>
> > >>>>>>
> > >>>>>> wrote:
> > >>>>>>
> > >>>>>> Hi Stephan & Piotrek,
> > >>>>>>
> > >>>>>> Thank you for feedback.
> > >>>>>>
> > >>>>>> It seems that there are a lot of things to do in community.
> > >>>>>>
> > >>>>>> I
> > >>>>>>
> > >>>>>> am
> > >>>>>>
> > >>>>>> just
> > >>>>>>
> > >>>>>> afraid that this discussion may be forgotten since there so
> > >>>>>>
> > >>>>>> many
> > >>>>>>
> > >>>>>> proposals
> > >>>>>>
> > >>>>>> recently.
> > >>>>>> Anyway, wish to see the split topics soon :)
> > >>>>>>
> > >>>>>> Piotr Nowojski <[hidden email] <mailto:
> [hidden email]
> > >>>>
> > >>> <
> > >>>> [hidden email] <mailto:[hidden email]>> <
> > >>>> [hidden email] <mailto:[hidden email]>> <
> > >>>> [hidden email] <mailto:[hidden email]>>
> > >>>>>>
> > >>>>>> 于2019年1月24日周四
> > >>>>>>
> > >>>>>> 下午8:21写道：
> > >>>>>>
> > >>>>>> Hi Biao!
> > >>>>>>
> > >>>>>> This discussion was stalled because of preparations for
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> open
> > >>>>>>
> > >>>>>> sourcing
> > >>>>>>
> > >>>>>> & merging Blink. I think before creating the tickets we
> > >>>>>>
> > >>>>>> should
> > >>>>>>
> > >>>>>> split this
> > >>>>>>
> > >>>>>> discussion into topics/areas outlined by Stephan and
> > >>>>>>
> > >>>>>> create
> > >>>>>>
> > >>>>>> Flips
> > >>>>>>
> > >>>>>> for
> > >>>>>>
> > >>>>>> that.
> > >>>>>>
> > >>>>>> I think there is no chance for this to be completed in
> > >>>>>>
> > >>>>>> couple
> > >>>>>>
> > >>>>>> of
> > >>>>>>
> > >>>>>> remaining
> > >>>>>>
> > >>>>>> weeks/1 month before 1.8 feature freeze, however it would
> > >>>>>>
> > >>>>>> be
> > >>>>>>
> > >>>>>> good
> > >>>>>>
> > >>>>>> to aim
> > >>>>>>
> > >>>>>> with those changes for 1.9.
> > >>>>>>
> > >>>>>> Piotrek
> > >>>>>>
> > >>>>>>
> > >>>>>> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email] <mailto:
> > >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]
> >>
> > >> <
> > >>>>>>
> > >>>>>> [hidden email] <mailto:[hidden email]>>
> > >>>>>>
> > >>>>>> wrote:
> > >>>>>>
> > >>>>>> Hi community,
> > >>>>>> The summary of Stephan makes a lot sense to me. It is
> > >>>>>>
> > >>>>>> much
> > >>>>>>
> > >>>>>> clearer
> > >>>>>>
> > >>>>>> indeed
> > >>>>>>
> > >>>>>> after splitting the complex topic into small ones.
> > >>>>>> I was wondering is there any detail plan for next step?
> > >>>>>>
> > >>>>>> If
> > >>>>>>
> > >>>>>> not,
> > >>>>>>
> > >>>>>> I
> > >>>>>>
> > >>>>>> would
> > >>>>>>
> > >>>>>> like to push this thing forward by creating some JIRA
> > >>>>>>
> > >>>>>> issues.
> > >>>>>>
> > >>>>>> Another question is that should version 1.8 include
> > >>>>>>
> > >>>>>> these
> > >>>>>>
> > >>>>>> features?
> > >>>>>>
> > >>>>>> Stephan Ewen <[hidden email] <mailto:[hidden email]>> <
> > >>>> [hidden email] <mailto:[hidden email]>> <[hidden email]
> > <mailto:
> > >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> > >>>> 于2018年12月1日周六
> > >>>>>>
> > >>>>>> 上午4:20写道：
> > >>>>>>
> > >>>>>> Thanks everyone for the lively discussion. Let me try
> > >>>>>>
> > >>>>>> to
> > >>>>>>
> > >>>>>> summarize
> > >>>>>>
> > >>>>>> where I
> > >>>>>>
> > >>>>>> see convergence in the discussion and open issues.
> > >>>>>> I'll try to group this by design aspect of the source.
> > >>>>>>
> > >>>>>> Please
> > >>>>>>
> > >>>>>> let me
> > >>>>>>
> > >>>>>> know
> > >>>>>>
> > >>>>>> if I got things wrong or missed something crucial here.
> > >>>>>>
> > >>>>>> For issues 1-3, if the below reflects the state of the
> > >>>>>>
> > >>>>>> discussion, I
> > >>>>>>
> > >>>>>> would
> > >>>>>>
> > >>>>>> try and update the FLIP in the next days.
> > >>>>>> For the remaining ones we need more discussion.
> > >>>>>>
> > >>>>>> I would suggest to fork each of these aspects into a
> > >>>>>>
> > >>>>>> separate
> > >>>>>>
> > >>>>>> mail
> > >>>>>>
> > >>>>>> thread,
> > >>>>>>
> > >>>>>> or will loose sight of the individual aspects.
> > >>>>>>
> > >>>>>> *(1) Separation of Split Enumerator and Split Reader*
> > >>>>>>
> > >>>>>> - All seem to agree this is a good thing
> > >>>>>> - Split Enumerator could in the end live on JobManager
> > >>>>>>
> > >>>>>> (and
> > >>>>>>
> > >>>>>> assign
> > >>>>>>
> > >>>>>> splits
> > >>>>>>
> > >>>>>> via RPC) or in a task (and assign splits via data
> > >>>>>>
> > >>>>>> streams)
> > >>>>>>
> > >>>>>> - this discussion is orthogonal and should come later,
> > >>>>>>
> > >>>>>> when
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> interface
> > >>>>>>
> > >>>>>> is agreed upon.
> > >>>>>>
> > >>>>>> *(2) Split Readers for one or more splits*
> > >>>>>>
> > >>>>>> - Discussion seems to agree that we need to support
> > >>>>>>
> > >>>>>> one
> > >>>>>>
> > >>>>>> reader
> > >>>>>>
> > >>>>>> that
> > >>>>>>
> > >>>>>> possibly handles multiple splits concurrently.
> > >>>>>> - The requirement comes from sources where one
> > >>>>>>
> > >>>>>> poll()-style
> > >>>>>>
> > >>>>>> call
> > >>>>>>
> > >>>>>> fetches
> > >>>>>>
> > >>>>>> data from different splits / partitions
> > >>>>>>    --> example sources that require that would be for
> > >>>>>>
> > >>>>>> example
> > >>>>>>
> > >>>>>> Kafka,
> > >>>>>>
> > >>>>>> Pravega, Pulsar
> > >>>>>>
> > >>>>>> - Could have one split reader per source, or multiple
> > >>>>>>
> > >>>>>> split
> > >>>>>>
> > >>>>>> readers
> > >>>>>>
> > >>>>>> that
> > >>>>>>
> > >>>>>> share the "poll()" function
> > >>>>>> - To not make it too complicated, we can start with
> > >>>>>>
> > >>>>>> thinking
> > >>>>>>
> > >>>>>> about
> > >>>>>>
> > >>>>>> one
> > >>>>>>
> > >>>>>> split reader for all splits initially and see if that
> > >>>>>>
> > >>>>>> covers
> > >>>>>>
> > >>>>>> all
> > >>>>>>
> > >>>>>> requirements
> > >>>>>>
> > >>>>>> *(3) Threading model of the Split Reader*
> > >>>>>>
> > >>>>>> - Most active part of the discussion ;-)
> > >>>>>>
> > >>>>>> - A non-blocking way for Flink's task code to interact
> > >>>>>>
> > >>>>>> with
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> source
> > >>>>>>
> > >>>>>> is
> > >>>>>>
> > >>>>>> needed in order to a task runtime code based on a
> > >>>>>> single-threaded/actor-style task design
> > >>>>>>    --> I personally am a big proponent of that, it will
> > >>>>>>
> > >>>>>> help
> > >>>>>>
> > >>>>>> with
> > >>>>>>
> > >>>>>> well-behaved checkpoints, efficiency, and simpler yet
> > >>>>>>
> > >>>>>> more
> > >>>>>>
> > >>>>>> robust
> > >>>>>>
> > >>>>>> runtime
> > >>>>>>
> > >>>>>> code
> > >>>>>>
> > >>>>>> - Users care about simple abstraction, so as a
> > >>>>>>
> > >>>>>> subclass
> > >>>>>>
> > >>>>>> of
> > >>>>>>
> > >>>>>> SplitReader
> > >>>>>>
> > >>>>>> (non-blocking / async) we need to have a
> > >>>>>>
> > >>>>>> BlockingSplitReader
> > >>>>>>
> > >>>>>> which
> > >>>>>>
> > >>>>>> will
> > >>>>>>
> > >>>>>> form the basis of most source implementations.
> > >>>>>>
> > >>>>>> BlockingSplitReader
> > >>>>>>
> > >>>>>> lets
> > >>>>>>
> > >>>>>> users do blocking simple poll() calls.
> > >>>>>> - The BlockingSplitReader would spawn a thread (or
> > >>>>>>
> > >>>>>> more)
> > >>>>>>
> > >>>>>> and
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> thread(s) can make blocking calls and hand over data
> > >>>>>>
> > >>>>>> buffers
> > >>>>>>
> > >>>>>> via
> > >>>>>>
> > >>>>>> a
> > >>>>>>
> > >>>>>> blocking
> > >>>>>>
> > >>>>>> queue
> > >>>>>> - This should allow us to cover both, a fully async
> > >>>>>>
> > >>>>>> runtime,
> > >>>>>>
> > >>>>>> and a
> > >>>>>>
> > >>>>>> simple
> > >>>>>>
> > >>>>>> blocking interface for users.
> > >>>>>> - This is actually very similar to how the Kafka
> > >>>>>>
> > >>>>>> connectors
> > >>>>>>
> > >>>>>> work.
> > >>>>>>
> > >>>>>> Kafka
> > >>>>>>
> > >>>>>> 9+ with one thread, Kafka 8 with multiple threads
> > >>>>>>
> > >>>>>> - On the base SplitReader (the async one), the
> > >>>>>>
> > >>>>>> non-blocking
> > >>>>>>
> > >>>>>> method
> > >>>>>>
> > >>>>>> that
> > >>>>>>
> > >>>>>> gets the next chunk of data would signal data
> > >>>>>>
> > >>>>>> availability
> > >>>>>>
> > >>>>>> via
> > >>>>>>
> > >>>>>> a
> > >>>>>>
> > >>>>>> CompletableFuture, because that gives the best
> > >>>>>>
> > >>>>>> flexibility
> > >>>>>>
> > >>>>>> (can
> > >>>>>>
> > >>>>>> await
> > >>>>>>
> > >>>>>> completion or register notification handlers).
> > >>>>>> - The source task would register a "thenHandle()" (or
> > >>>>>>
> > >>>>>> similar)
> > >>>>>>
> > >>>>>> on the
> > >>>>>>
> > >>>>>> future to put a "take next data" task into the
> > >>>>>>
> > >>>>>> actor-style
> > >>>>>>
> > >>>>>> mailbox
> > >>>>>>
> > >>>>>> *(4) Split Enumeration and Assignment*
> > >>>>>>
> > >>>>>> - Splits may be generated lazily, both in cases where
> > >>>>>>
> > >>>>>> there
> > >>>>>>
> > >>>>>> is a
> > >>>>>>
> > >>>>>> limited
> > >>>>>>
> > >>>>>> number of splits (but very many), or splits are
> > >>>>>>
> > >>>>>> discovered
> > >>>>>>
> > >>>>>> over
> > >>>>>>
> > >>>>>> time
> > >>>>>>
> > >>>>>> - Assignment should also be lazy, to get better load
> > >>>>>>
> > >>>>>> balancing
> > >>>>>>
> > >>>>>> - Assignment needs support locality preferences
> > >>>>>>
> > >>>>>> - Possible design based on discussion so far:
> > >>>>>>
> > >>>>>>    --> SplitReader has a method "addSplits(SplitT...)"
> > >>>>>>
> > >>>>>> to
> > >>>>>>
> > >>>>>> add
> > >>>>>>
> > >>>>>> one or
> > >>>>>>
> > >>>>>> more
> > >>>>>>
> > >>>>>> splits. Some split readers might assume they have only
> > >>>>>>
> > >>>>>> one
> > >>>>>>
> > >>>>>> split
> > >>>>>>
> > >>>>>> ever,
> > >>>>>>
> > >>>>>> concurrently, others assume multiple splits. (Note:
> > >>>>>>
> > >>>>>> idea
> > >>>>>>
> > >>>>>> behind
> > >>>>>>
> > >>>>>> being
> > >>>>>>
> > >>>>>> able
> > >>>>>>
> > >>>>>> to add multiple splits at the same time is to ease
> > >>>>>>
> > >>>>>> startup
> > >>>>>>
> > >>>>>> where
> > >>>>>>
> > >>>>>> multiple
> > >>>>>>
> > >>>>>> splits may be assigned instantly.)
> > >>>>>>    --> SplitReader has a context object on which it can
> > >>>>>>
> > >>>>>> call
> > >>>>>>
> > >>>>>> indicate
> > >>>>>>
> > >>>>>> when
> > >>>>>>
> > >>>>>> splits are completed. The enumerator gets that
> > >>>>>>
> > >>>>>> notification and
> > >>>>>>
> > >>>>>> can
> > >>>>>>
> > >>>>>> use
> > >>>>>>
> > >>>>>> to
> > >>>>>>
> > >>>>>> decide when to assign new splits. This should help both
> > >>>>>>
> > >>>>>> in
> > >>>>>>
> > >>>>>> cases
> > >>>>>>
> > >>>>>> of
> > >>>>>>
> > >>>>>> sources
> > >>>>>>
> > >>>>>> that take splits lazily (file readers) and in case the
> > >>>>>>
> > >>>>>> source
> > >>>>>>
> > >>>>>> needs to
> > >>>>>>
> > >>>>>> preserve a partial order between splits (Kinesis,
> > >>>>>>
> > >>>>>> Pravega,
> > >>>>>>
> > >>>>>> Pulsar may
> > >>>>>>
> > >>>>>> need
> > >>>>>>
> > >>>>>> that).
> > >>>>>>    --> SplitEnumerator gets notification when
> > >>>>>>
> > >>>>>> SplitReaders
> > >>>>>>
> > >>>>>> start
> > >>>>>>
> > >>>>>> and
> > >>>>>>
> > >>>>>> when
> > >>>>>>
> > >>>>>> they finish splits. They can decide at that moment to
> > >>>>>>
> > >>>>>> push
> > >>>>>>
> > >>>>>> more
> > >>>>>>
> > >>>>>> splits
> > >>>>>>
> > >>>>>> to
> > >>>>>>
> > >>>>>> that reader
> > >>>>>>    --> The SplitEnumerator should probably be aware of
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> source
> > >>>>>>
> > >>>>>> parallelism, to build its initial distribution.
> > >>>>>>
> > >>>>>> - Open question: Should the source expose something
> > >>>>>>
> > >>>>>> like
> > >>>>>>
> > >>>>>> "host
> > >>>>>>
> > >>>>>> preferences", so that yarn/mesos/k8s can take this into
> > >>>>>>
> > >>>>>> account
> > >>>>>>
> > >>>>>> when
> > >>>>>>
> > >>>>>> selecting a node to start a TM on?
> > >>>>>>
> > >>>>>> *(5) Watermarks and event time alignment*
> > >>>>>>
> > >>>>>> - Watermark generation, as well as idleness, needs to
> > >>>>>>
> > >>>>>> be
> > >>>>>>
> > >>>>>> per
> > >>>>>>
> > >>>>>> split
> > >>>>>>
> > >>>>>> (like
> > >>>>>>
> > >>>>>> currently in the Kafka Source, per partition)
> > >>>>>> - It is desirable to support optional
> > >>>>>>
> > >>>>>> event-time-alignment,
> > >>>>>>
> > >>>>>> meaning
> > >>>>>>
> > >>>>>> that
> > >>>>>>
> > >>>>>> splits that are ahead are back-pressured or temporarily
> > >>>>>>
> > >>>>>> unsubscribed
> > >>>>>>
> > >>>>>> - I think i would be desirable to encapsulate
> > >>>>>>
> > >>>>>> watermark
> > >>>>>>
> > >>>>>> generation
> > >>>>>>
> > >>>>>> logic
> > >>>>>>
> > >>>>>> in watermark generators, for a separation of concerns.
> > >>>>>>
> > >>>>>> The
> > >>>>>>
> > >>>>>> watermark
> > >>>>>>
> > >>>>>> generators should run per split.
> > >>>>>> - Using watermark generators would also help with
> > >>>>>>
> > >>>>>> another
> > >>>>>>
> > >>>>>> problem of
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> suggested interface, namely supporting non-periodic
> > >>>>>>
> > >>>>>> watermarks
> > >>>>>>
> > >>>>>> efficiently.
> > >>>>>>
> > >>>>>> - Need a way to "dispatch" next record to different
> > >>>>>>
> > >>>>>> watermark
> > >>>>>>
> > >>>>>> generators
> > >>>>>>
> > >>>>>> - Need a way to tell SplitReader to "suspend" a split
> > >>>>>>
> > >>>>>> until a
> > >>>>>>
> > >>>>>> certain
> > >>>>>>
> > >>>>>> watermark is reached (event time backpressure)
> > >>>>>> - This would in fact be not needed (and thus simpler)
> > >>>>>>
> > >>>>>> if
> > >>>>>>
> > >>>>>> we
> > >>>>>>
> > >>>>>> had
> > >>>>>>
> > >>>>>> a
> > >>>>>>
> > >>>>>> SplitReader per split and may be a reason to re-open
> > >>>>>>
> > >>>>>> that
> > >>>>>>
> > >>>>>> discussion
> > >>>>>>
> > >>>>>> *(6) Watermarks across splits and in the Split
> > >>>>>>
> > >>>>>> Enumerator*
> > >>>>>>
> > >>>>>> - The split enumerator may need some watermark
> > >>>>>>
> > >>>>>> awareness,
> > >>>>>>
> > >>>>>> which
> > >>>>>>
> > >>>>>> should
> > >>>>>>
> > >>>>>> be
> > >>>>>>
> > >>>>>> purely based on split metadata (like create timestamp
> > >>>>>>
> > >>>>>> of
> > >>>>>>
> > >>>>>> file
> > >>>>>>
> > >>>>>> splits)
> > >>>>>>
> > >>>>>> - If there are still more splits with overlapping
> > >>>>>>
> > >>>>>> event
> > >>>>>>
> > >>>>>> time
> > >>>>>>
> > >>>>>> range
> > >>>>>>
> > >>>>>> for
> > >>>>>>
> > >>>>>> a
> > >>>>>>
> > >>>>>> split reader, then that split reader should not advance
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> watermark
> > >>>>>>
> > >>>>>> within the split beyond the overlap boundary. Otherwise
> > >>>>>>
> > >>>>>> future
> > >>>>>>
> > >>>>>> splits
> > >>>>>>
> > >>>>>> will
> > >>>>>>
> > >>>>>> produce late data.
> > >>>>>>
> > >>>>>> - One way to approach this could be that the split
> > >>>>>>
> > >>>>>> enumerator
> > >>>>>>
> > >>>>>> may
> > >>>>>>
> > >>>>>> send
> > >>>>>>
> > >>>>>> watermarks to the readers, and the readers cannot emit
> > >>>>>>
> > >>>>>> watermarks
> > >>>>>>
> > >>>>>> beyond
> > >>>>>>
> > >>>>>> that received watermark.
> > >>>>>> - Many split enumerators would simply immediately send
> > >>>>>>
> > >>>>>> Long.MAX
> > >>>>>>
> > >>>>>> out
> > >>>>>>
> > >>>>>> and
> > >>>>>>
> > >>>>>> leave the progress purely to the split readers.
> > >>>>>>
> > >>>>>> - For event-time alignment / split back pressure, this
> > >>>>>>
> > >>>>>> begs
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> question
> > >>>>>>
> > >>>>>> how we can avoid deadlocks that may arise when splits
> > >>>>>>
> > >>>>>> are
> > >>>>>>
> > >>>>>> suspended
> > >>>>>>
> > >>>>>> for
> > >>>>>>
> > >>>>>> event time back pressure,
> > >>>>>>
> > >>>>>> *(7) Batch and streaming Unification*
> > >>>>>>
> > >>>>>> - Functionality wise, the above design should support
> > >>>>>>
> > >>>>>> both
> > >>>>>>
> > >>>>>> - Batch often (mostly) does not care about reading "in
> > >>>>>>
> > >>>>>> order"
> > >>>>>>
> > >>>>>> and
> > >>>>>>
> > >>>>>> generating watermarks
> > >>>>>>    --> Might use different enumerator logic that is
> > >>>>>>
> > >>>>>> more
> > >>>>>>
> > >>>>>> locality
> > >>>>>>
> > >>>>>> aware
> > >>>>>>
> > >>>>>> and ignores event time order
> > >>>>>>    --> Does not generate watermarks
> > >>>>>> - Would be great if bounded sources could be
> > >>>>>>
> > >>>>>> identified
> > >>>>>>
> > >>>>>> at
> > >>>>>>
> > >>>>>> compile
> > >>>>>>
> > >>>>>> time,
> > >>>>>>
> > >>>>>> so that "env.addBoundedSource(...)" is type safe and
> > >>>>>>
> > >>>>>> can
> > >>>>>>
> > >>>>>> return a
> > >>>>>>
> > >>>>>> "BoundedDataStream".
> > >>>>>> - Possible to defer this discussion until later
> > >>>>>>
> > >>>>>> *Miscellaneous Comments*
> > >>>>>>
> > >>>>>> - Should the source have a TypeInformation for the
> > >>>>>>
> > >>>>>> produced
> > >>>>>>
> > >>>>>> type,
> > >>>>>>
> > >>>>>> instead
> > >>>>>>
> > >>>>>> of a serializer? We need a type information in the
> > >>>>>>
> > >>>>>> stream
> > >>>>>>
> > >>>>>> anyways, and
> > >>>>>>
> > >>>>>> can
> > >>>>>>
> > >>>>>> derive the serializer from that. Plus, creating the
> > >>>>>>
> > >>>>>> serializer
> > >>>>>>
> > >>>>>> should
> > >>>>>>
> > >>>>>> respect the ExecutionConfig.
> > >>>>>>
> > >>>>>> - The TypeSerializer interface is very powerful but
> > >>>>>>
> > >>>>>> also
> > >>>>>>
> > >>>>>> not
> > >>>>>>
> > >>>>>> easy to
> > >>>>>>
> > >>>>>> implement. Its purpose is to handle data super
> > >>>>>>
> > >>>>>> efficiently,
> > >>>>>>
> > >>>>>> support
> > >>>>>>
> > >>>>>> flexible ways of evolution, etc.
> > >>>>>> For metadata I would suggest to look at the
> > >>>>>>
> > >>>>>> SimpleVersionedSerializer
> > >>>>>>
> > >>>>>> instead, which is used for example for checkpoint
> > >>>>>>
> > >>>>>> master
> > >>>>>>
> > >>>>>> hooks,
> > >>>>>>
> > >>>>>> or for
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> streaming file sink. I think that is is a good match
> > >>>>>>
> > >>>>>> for
> > >>>>>>
> > >>>>>> cases
> > >>>>>>
> > >>>>>> where
> > >>>>>>
> > >>>>>> we
> > >>>>>>
> > >>>>>> do
> > >>>>>>
> > >>>>>> not need more than ser/deser (no copy, etc.) and don't
> > >>>>>>
> > >>>>>> need to
> > >>>>>>
> > >>>>>> push
> > >>>>>>
> > >>>>>> versioning out of the serialization paths for best
> > >>>>>>
> > >>>>>> performance
> > >>>>>>
> > >>>>>> (as in
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> TypeSerializer)
> > >>>>>>
> > >>>>>>
> > >>>>>> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
> > >>>>>>
> > >>>>>> [hidden email]>
> > >>>>>>
> > >>>>>> wrote:
> > >>>>>>
> > >>>>>>
> > >>>>>> Hi Biao,
> > >>>>>>
> > >>>>>> Thanks for the answer!
> > >>>>>>
> > >>>>>> So given the multi-threaded readers, now we have as
> > >>>>>>
> > >>>>>> open
> > >>>>>>
> > >>>>>> questions:
> > >>>>>>
> > >>>>>> 1) How do we let the checkpoints pass through our
> > >>>>>>
> > >>>>>> multi-threaded
> > >>>>>>
> > >>>>>> reader
> > >>>>>>
> > >>>>>> operator?
> > >>>>>>
> > >>>>>> 2) Do we have separate reader and source operators or
> > >>>>>>
> > >>>>>> not? In
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> strategy
> > >>>>>>
> > >>>>>> that has a separate source, the source operator has a
> > >>>>>>
> > >>>>>> parallelism of
> > >>>>>>
> > >>>>>> 1
> > >>>>>>
> > >>>>>> and
> > >>>>>>
> > >>>>>> is responsible for split recovery only.
> > >>>>>>
> > >>>>>> For the first one, given also the constraints
> > >>>>>>
> > >>>>>> (blocking,
> > >>>>>>
> > >>>>>> finite
> > >>>>>>
> > >>>>>> queues,
> > >>>>>>
> > >>>>>> etc), I do not have an answer yet.
> > >>>>>>
> > >>>>>> For the 2nd, I think that we should go with separate
> > >>>>>>
> > >>>>>> operators
> > >>>>>>
> > >>>>>> for
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> source and the readers, for the following reasons:
> > >>>>>>
> > >>>>>> 1) This is more aligned with a potential future
> > >>>>>>
> > >>>>>> improvement
> > >>>>>>
> > >>>>>> where the
> > >>>>>>
> > >>>>>> split
> > >>>>>>
> > >>>>>> discovery becomes a responsibility of the JobManager
> > >>>>>>
> > >>>>>> and
> > >>>>>>
> > >>>>>> readers are
> > >>>>>>
> > >>>>>> pooling more work from the JM.
> > >>>>>>
> > >>>>>> 2) The source is going to be the "single point of
> > >>>>>>
> > >>>>>> truth".
> > >>>>>>
> > >>>>>> It
> > >>>>>>
> > >>>>>> will
> > >>>>>>
> > >>>>>> know
> > >>>>>>
> > >>>>>> what
> > >>>>>>
> > >>>>>> has been processed and what not. If the source and the
> > >>>>>>
> > >>>>>> readers
> > >>>>>>
> > >>>>>> are a
> > >>>>>>
> > >>>>>> single
> > >>>>>>
> > >>>>>> operator with parallelism > 1, or in general, if the
> > >>>>>>
> > >>>>>> split
> > >>>>>>
> > >>>>>> discovery
> > >>>>>>
> > >>>>>> is
> > >>>>>>
> > >>>>>> done by each task individually, then:
> > >>>>>>   i) we have to have a deterministic scheme for each
> > >>>>>>
> > >>>>>> reader to
> > >>>>>>
> > >>>>>> assign
> > >>>>>>
> > >>>>>> splits to itself (e.g. mod subtaskId). This is not
> > >>>>>>
> > >>>>>> necessarily
> > >>>>>>
> > >>>>>> trivial
> > >>>>>>
> > >>>>>> for
> > >>>>>>
> > >>>>>> all sources.
> > >>>>>>   ii) each reader would have to keep a copy of all its
> > >>>>>>
> > >>>>>> processed
> > >>>>>>
> > >>>>>> slpits
> > >>>>>>
> > >>>>>>   iii) the state has to be a union state with a
> > >>>>>>
> > >>>>>> non-trivial
> > >>>>>>
> > >>>>>> merging
> > >>>>>>
> > >>>>>> logic
> > >>>>>>
> > >>>>>> in order to support rescaling.
> > >>>>>>
> > >>>>>> Two additional points that you raised above:
> > >>>>>>
> > >>>>>> i) The point that you raised that we need to keep all
> > >>>>>>
> > >>>>>> splits
> > >>>>>>
> > >>>>>> (processed
> > >>>>>>
> > >>>>>> and
> > >>>>>>
> > >>>>>> not-processed) I think is a bit of a strong
> > >>>>>>
> > >>>>>> requirement.
> > >>>>>>
> > >>>>>> This
> > >>>>>>
> > >>>>>> would
> > >>>>>>
> > >>>>>> imply
> > >>>>>>
> > >>>>>> that for infinite sources the state will grow
> > >>>>>>
> > >>>>>> indefinitely.
> > >>>>>>
> > >>>>>> This is
> > >>>>>>
> > >>>>>> problem
> > >>>>>>
> > >>>>>> is even more pronounced if we do not have a single
> > >>>>>>
> > >>>>>> source
> > >>>>>>
> > >>>>>> that
> > >>>>>>
> > >>>>>> assigns
> > >>>>>>
> > >>>>>> splits to readers, as each reader will have its own
> > >>>>>>
> > >>>>>> copy
> > >>>>>>
> > >>>>>> of
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> state.
> > >>>>>>
> > >>>>>> ii) it is true that for finite sources we need to
> > >>>>>>
> > >>>>>> somehow
> > >>>>>>
> > >>>>>> not
> > >>>>>>
> > >>>>>> close
> > >>>>>>
> > >>>>>> the
> > >>>>>>
> > >>>>>> readers when the source/split discoverer finishes. The
> > >>>>>> ContinuousFileReaderOperator has a work-around for
> > >>>>>>
> > >>>>>> that.
> > >>>>>>
> > >>>>>> It is
> > >>>>>>
> > >>>>>> not
> > >>>>>>
> > >>>>>> elegant,
> > >>>>>>
> > >>>>>> and checkpoints are not emitted after closing the
> > >>>>>>
> > >>>>>> source,
> > >>>>>>
> > >>>>>> but
> > >>>>>>
> > >>>>>> this, I
> > >>>>>>
> > >>>>>> believe, is a bigger problem which requires more
> > >>>>>>
> > >>>>>> changes
> > >>>>>>
> > >>>>>> than
> > >>>>>>
> > >>>>>> just
> > >>>>>>
> > >>>>>> refactoring the source interface.
> > >>>>>>
> > >>>>>> Cheers,
> > >>>>>> Kostas
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>>
> > >>>>>> --
> > >>>>>> Best, Jingsong Lee
> > >>>>
> > >>>>
> > >>>
> > >>
> > >>
> > >> --
> > >> Best, Jingsong Lee
> > >>
> > >
> >
> >
>

[Becket Qin]

Hi Jark,

Please see the reply below:

Regarding to option#3, my concern is that if we don't support streaming
> mode for bounded source,
> how could we create a testing source for streaming mode? Currently, all the
> testing source for streaming
> are bounded, so that the integration test will finish finally.


An UNBOUNDED source does not mean it will never stops. It simply indicates
that the source *may* run forever, so the runtime needs to be prepared for
that, but the task may still stop at some point when it hits some
source-specific condition. So an UNBOUNDED testing source can still stop at
some point if needed.

Regarding to Source#getRecordOrder(), could we have a implicit contract
> that unbounded source should
> already read in order (i.e. reading partitions in parallel), for bounded
> source the order is not mandatory.



> This is also the behaviors of the current sources.

1) a source can't guarantee it reads in strict order, because the producer
> may produce data not in order.
> 2) *Bounded-StrictOrder* is not necessary, because batch can reorder data.


It is true that sometimes the source cannot guarantee the record order, but
sometimes it can. Right now, even for stream processing, there is no
processing order guarantee. For example, a join operator may emit a later
record which successfully found a join match earlier.
Event order is one of the most important requirements for event processing,
a clear order guarantee would be necessary. That said, I agree that right
now even if the sources provide the record order requirement, the runtime
is not able to guarantee that out of the box. So I am OK if we add the
record order to the Source later. But we should avoid misleading users to
make them think the processing order is guaranteed when using the unbounded
runtime.

Thanks,

Jiangjie (Becket) Qin

On Wed, Dec 18, 2019 at 10:29 AM Jark Wu <[hidden email]> wrote:

> Hi Becket,
>
> That's great we have reached a consensus on Source#getBoundedness().
>
> Regarding to option#3, my concern is that if we don't support streaming
> mode for bounded source,
> how could we create a testing source for streaming mode? Currently, all the
> testing source for streaming
> are bounded, so that the integration test will finish finally.
>
> Regarding to Source#getRecordOrder(), could we have a implicit contract
> that unbounded source should
> already read in order (i.e. reading partitions in parallel), for bounded
> source the order is not mandatory.
> This is also the behaviors of the current sources.
> 1) a source can't guarantee it reads in strict order, because the producer
> may produce data not in order.
> 2) *Bounded-StrictOrder* is not necessary, because batch can reorder data.
>
> Best,
> Jark
>
>
>
> On Tue, 17 Dec 2019 at 22:03, Becket Qin <[hidden email]> wrote:
>
> > Hi folks,
> >
> > Thanks for the comments. I am convinced that the Source API should not
> take
> > boundedness as a parameter after it is constructed. What Timo and Dawid
> > suggested sounds a reasonable solution to me. So the Source API would
> > become:
> >
> > Source {
> >     Boundedness getBoundedness();
> > }
> >
> > Assuming the above Source API, in addition to the two options mentioned
> in
> > earlier emails, I am thinking of another option:
> >
> > *Option 3:*
> > // MySource must be unbounded, otherwise throws exception.
> > DataStream<Type> dataStream = env.source(mySource);
> >
> > // MySource must be bounded, otherwise throws exception.
> > BoundedDataStream<Type> boundedDataStream = env.boundedSource(mySource);
> >
> > The pros of this API are:
> >    a) It fits the requirements from Table / SQL well.
> >    b) DataStream users still have type safety (option 2 only has partial
> > type safety).
> >    c) Cristal clear boundedness from the API which makes DataStream join
> /
> > connect easy to reason about.
> > The caveats I see,
> >    a) It is inconsistent with Table since Table has one unified
> interface.
> >    b) No streaming mode for bounded source.
> >
> > @Stephan Ewen <[hidden email]> @Aljoscha Krettek
> > <[hidden email]> what do you think of the approach?
> >
> >
> > Orthogonal to the above API, I am wondering whether boundedness is the
> only
> > dimension needed to describe the characteristic of the Source behavior.
> We
> > may also need to have another dimension of *record order*.
> >
> > For example, when a file source is reading from a directory with bounded
> > records, it may have two ways to read.
> > 1. Read files in parallel.
> > 2. Read files in the chronological order.
> > In both cases, the file source is a Bounded Source. However, the
> processing
> > requirement for downstream may be different. In the first case, the
> > record processing and result emitting order does not matter, e.g. word
> > count. In the second case, the records may have to be processed in the
> > order they were read, e.g. change log processing.
> >
> > If the Source only has a getBoundedness() method, the downstream
> processors
> > would not know whether the records emitted from the Source should be
> > processed in order or not. So combining the boundedness and record order,
> > we will have four scenarios:
> >
> > *Bounded-StrictOrder*:     A segment of change log.
> > *Bounded-Random*:          Batch Word Count.
> > *Unbounded-StrictOrder*: An infinite change log.
> > *Unbounded-Random*:     Streaming Word Count.
> >
> > Option 2 mentioned in the previous email was kind of trying to handle the
> > Bounded-StrictOrder case by creating a DataStream from a bounded source,
> > which actually does not work.
> > It looks that we do not have strict order support in some operators at
> this
> > point, e.g. join. But we may still want to add the semantic to the Source
> > first so later on we don't need to change all the source implementations,
> > especially given that many of them will be implemented by 3rd party.
> >
> > Given that, we need another dimension of *Record Order* in the Source.
> More
> > specifically, the API would become:
> >
> > Source {
> >     Boundedness getBoundedness();
> >     RecordOrder getRecordOrder();
> > }
> >
> > public enum RecordOrder {
> >     /** The record in the DataStream must be processed in its strict
> order
> > for correctness. */
> >     STRICT,
> >     /** The record in the DataStream can be processed in arbitrary order.
> > */
> >     RANDOM;
> > }
> >
> > Any thoughts?
> >
> > Thanks,
> >
> > Jiangjie (Becket) Qin
> >
> > On Tue, Dec 17, 2019 at 3:44 PM Timo Walther <[hidden email]> wrote:
> >
> > > Hi Becket,
> > >
> > > I completely agree with Dawid's suggestion. The information about the
> > > boundedness should come out of the source. Because most of the
> streaming
> > > sources can be made bounded based on some connector specific criterion.
> > > In Kafka, it would be an end offset or end timestamp but in any case
> > > having just a env.boundedSource() is not enough because parameters for
> > > making the source bounded are missing.
> > >
> > > I suggest to have a simple `isBounded(): Boolean` flag in every source
> > > that might be influenced by a connector builder as Dawid mentioned.
> > >
> > > For type safety during programming, we can still go with *Final state
> > > 1*. By having a env.source() vs env.boundedSource(). The latter would
> > > just enforce that the boolean flag is set to `true` and could make
> > > bounded operations available (if we need that actually).
> > >
> > > However, I don't think that we should start making a unified Table API
> > > ununified again. Boundedness is an optimization property. Every bounded
> > > operation can also executed in an unbounded way using
> updates/retraction
> > > or watermarks.
> > >
> > > Regards,
> > > Timo
> > >
> > >
> > > On 15.12.19 14:22, Becket Qin wrote:
> > > > Hi Dawid and Jark,
> > > >
> > > > I think the discussion ultimately boils down to the question that
> which
> > > one
> > > > of the following two final states do we want? Once we make this
> > decision,
> > > > everything else can be naturally derived.
> > > >
> > > > *Final state 1*: Separate API for bounded / unbounded DataStream &
> > Table.
> > > > That means any code users write will be valid at the point when they
> > > write
> > > > the code. This is similar to having type safety check at programming
> > > time.
> > > > For example,
> > > >
> > > > BoundedDataStream extends DataStream {
> > > > // Operations only available for bounded data.
> > > > BoundedDataStream sort(...);
> > > >
> > > > // Interaction with another BoundedStream returns a Bounded stream.
> > > > BoundedJoinedDataStream join(BoundedDataStream other)
> > > >
> > > > // Interaction with another unbounded stream returns an unbounded
> > stream.
> > > > JoinedDataStream join(DataStream other)
> > > > }
> > > >
> > > > BoundedTable extends Table {
> > > >    // Bounded only operation.
> > > > BoundedTable sort(...);
> > > >
> > > > // Interaction with another BoundedTable returns a BoundedTable.
> > > > BoundedTable join(BoundedTable other)
> > > >
> > > > // Interaction with another unbounded table returns an unbounded
> table.
> > > > Table join(Table other)
> > > > }
> > > >
> > > > *Final state 2*: One unified API for bounded / unbounded DataStream /
> > > > Table.
> > > > That unified API may throw exception at DAG compilation time if an
> > > invalid
> > > > operation is tried. This is what Table API currently follows.
> > > >
> > > > DataStream {
> > > > // Throws exception if the DataStream is unbounded.
> > > > DataStream sort();
> > > > // Get boundedness.
> > > > Boundedness getBoundedness();
> > > > }
> > > >
> > > > Table {
> > > > // Throws exception if the table has infinite rows.
> > > > Table orderBy();
> > > >
> > > > // Get boundedness.
> > > > Boundedness getBoundedness();
> > > > }
> > > >
> > > >>From what I understand, there is no consensus so far on this decision
> > > yet.
> > > > Whichever final state we choose, we need to make it consistent across
> > the
> > > > entire project. We should avoid the case that Table follows one final
> > > state
> > > > while DataStream follows another. Some arguments I am aware of from
> > both
> > > > sides so far are following:
> > > >
> > > > Arguments for final state 1:
> > > > 1a) Clean API with method safety check at programming time.
> > > > 1b) (Counter 2b) Although SQL does not have programming time error
> > > check, SQL
> > > > is not really a "programming language" per se. So SQL can be
> different
> > > from
> > > > Table and DataStream.
> > > > 1c)  Although final state 2 seems making it easier for SQL to use
> given
> > > it
> > > > is more "config based" than "parameter based", final state 1 can
> > probably
> > > > also meet what SQL wants by wrapping the Source in TableSource /
> > > > TableSourceFactory API if needed.
> > > >
> > > > Arguments for final state 2:
> > > > 2a) The Source API itself seems already sort of following the unified
> > API
> > > > pattern.
> > > > 2b) There is no "programming time" method error check in SQL case, so
> > we
> > > > cannot really achieve final state 1 across the board.
> > > > 2c) It is an easier path given our current status, i.e. Table is
> > already
> > > > following final state 2.
> > > > 2d) Users can always explicitly check the boundedness if they want
> to.
> > > >
> > > > As I mentioned earlier, my initial thought was also to have a
> > > > "configuration based" Source rather than a "parameter based" Source.
> So
> > > it
> > > > is completely possible that I missed some important consideration or
> > > design
> > > > principles that we want to enforce for the project. It would be good
> > > > if @Stephan
> > > > Ewen <[hidden email]> and @Aljoscha Krettek <
> > > [hidden email]> can
> > > > also provide more thoughts on this.
> > > >
> > > >
> > > > Re: Jingsong
> > > >
> > > > As you said, there are some batched system source, like parquet/orc
> > > source.
> > > >> Could we have the batch emit interface to improve performance? The
> > > queue of
> > > >> per record may cause performance degradation.
> > > >
> > > >
> > > > The current interface does not necessarily cause performance problem
> > in a
> > > > multi-threading case. In fact, the base implementation allows
> > > SplitReaders
> > > > to add a batch <E> of records<T> to the records queue<E>, so each
> > element
> > > > in the records queue would be a batch <E>. In this case, when the
> main
> > > > thread polls records, it will take a batch <E> of records <T> from
> the
> > > > shared records queue and process the records <T> in a batch manner.
> > > >
> > > > Thanks,
> > > >
> > > > Jiangjie (Becket) Qin
> > > >
> > > > On Thu, Dec 12, 2019 at 1:29 PM Jingsong Li <[hidden email]>
> > > wrote:
> > > >
> > > >> Hi Becket,
> > > >>
> > > >> I also have some performance concerns too.
> > > >>
> > > >> If I understand correctly, SourceOutput will emit data per record
> into
> > > the
> > > >> queue? I'm worried about the multithreading performance of this
> queue.
> > > >>
> > > >>> One example is some batched messaging systems which only have an
> > offset
> > > >> for the entire batch instead of individual messages in the batch.
> > > >>
> > > >> As you said, there are some batched system source, like parquet/orc
> > > source.
> > > >> Could we have the batch emit interface to improve performance? The
> > > queue of
> > > >> per record may cause performance degradation.
> > > >>
> > > >> Best,
> > > >> Jingsong Lee
> > > >>
> > > >> On Thu, Dec 12, 2019 at 9:15 AM Jark Wu <[hidden email]> wrote:
> > > >>
> > > >>> Hi Becket,
> > > >>>
> > > >>> I think Dawid explained things clearly and makes a lot of sense.
> > > >>> I'm also in favor of #2, because #1 doesn't work for our future
> > unified
> > > >>> envrionment.
> > > >>>
> > > >>> You can see the vision in this documentation [1]. In the future, we
> > > would
> > > >>> like to
> > > >>> drop the global streaming/batch mode in SQL (i.e.
> > > >>> EnvironmentSettings#inStreamingMode/inBatchMode).
> > > >>> A source is bounded or unbounded once defined, so queries can be
> > > inferred
> > > >>> from source to run
> > > >>> in streaming or batch or hybrid mode. However, in #1, we will lose
> > this
> > > >>> ability because the framework
> > > >>> doesn't know whether the source is bounded or unbounded.
> > > >>>
> > > >>> Best,
> > > >>> Jark
> > > >>>
> > > >>>
> > > >>> [1]:
> > > >>>
> > > >>>
> > > >>
> > >
> >
> https://docs.google.com/document/d/1yrKXEIRATfxHJJ0K3t6wUgXAtZq8D-XgvEnvl2uUcr0/edit#heading=h.v4ib17buma1p
> > > >>>
> > > >>> On Wed, 11 Dec 2019 at 20:52, Piotr Nowojski <[hidden email]>
> > > >> wrote:
> > > >>>
> > > >>>> Hi,
> > > >>>>
> > > >>>> Regarding the:
> > > >>>>
> > > >>>> Collection<E> getNextRecords()
> > > >>>>
> > > >>>> I’m pretty sure such design would unfortunately impact the
> > performance
> > > >>>> (accessing and potentially creating the collection on the hot
> path).
> > > >>>>
> > > >>>> Also the
> > > >>>>
> > > >>>> InputStatus emitNext(DataOutput<T> output) throws Exception;
> > > >>>> or
> > > >>>> Status pollNext(SourceOutput<T> sourceOutput) throws Exception;
> > > >>>>
> > > >>>> Gives us some opportunities in the future, to allow Source hot
> > looping
> > > >>>> inside, until it receives some signal “please exit because of some
> > > >>> reasons”
> > > >>>> (output collector could return such hint upon collecting the
> > result).
> > > >> But
> > > >>>> that’s another topic outside of this FLIP’s scope.
> > > >>>>
> > > >>>> Piotrek
> > > >>>>
> > > >>>>> On 11 Dec 2019, at 10:41, Till Rohrmann <[hidden email]>
> > > >> wrote:
> > > >>>>>
> > > >>>>> Hi Becket,
> > > >>>>>
> > > >>>>> quick clarification from my side because I think you
> misunderstood
> > my
> > > >>>>> question. I did not suggest to let the SourceReader return only a
> > > >>> single
> > > >>>>> record at a time when calling getNextRecords. As the return type
> > > >>>> indicates,
> > > >>>>> the method can return an arbitrary number of records.
> > > >>>>>
> > > >>>>> Cheers,
> > > >>>>> Till
> > > >>>>>
> > > >>>>> On Wed, Dec 11, 2019 at 10:13 AM Dawid Wysakowicz <
> > > >>>> [hidden email] <mailto:[hidden email]>>
> > > >>>>> wrote:
> > > >>>>>
> > > >>>>>> Hi Becket,
> > > >>>>>>
> > > >>>>>> Issue #1 - Design of Source interface
> > > >>>>>>
> > > >>>>>> I mentioned the lack of a method like
> > > >>>> Source#createEnumerator(Boundedness
> > > >>>>>> boundedness, SplitEnumeratorContext context), because without
> the
> > > >>>> current
> > > >>>>>> proposal is not complete/does not work.
> > > >>>>>>
> > > >>>>>> If we say that boundedness is an intrinsic property of a source
> > imo
> > > >> we
> > > >>>>>> don't need the Source#createEnumerator(Boundedness boundedness,
> > > >>>>>> SplitEnumeratorContext context) method.
> > > >>>>>>
> > > >>>>>> Assuming a source from my previous example:
> > > >>>>>>
> > > >>>>>> Source source = KafkaSource.builder()
> > > >>>>>>   ...
> > > >>>>>>   .untilTimestamp(...)
> > > >>>>>>   .build()
> > > >>>>>>
> > > >>>>>> Would the enumerator differ if created like
> > > >>>>>> source.createEnumerator(CONTINUOUS_UNBOUNDED, ...) vs source
> > > >>>>>> .createEnumerator(BOUNDED, ...)? I know I am repeating myself,
> but
> > > >>> this
> > > >>>> is
> > > >>>>>> the part that my opinion differ the most from the current
> > proposal.
> > > >> I
> > > >>>>>> really think it should always be the source that tells if it is
> > > >>> bounded
> > > >>>> or
> > > >>>>>> not. In the current proposal methods
> continousSource/boundedSource
> > > >>>> somewhat
> > > >>>>>> reconfigure the source, which I think is misleading.
> > > >>>>>>
> > > >>>>>> I think a call like:
> > > >>>>>>
> > > >>>>>> Source source = KafkaSource.builder()
> > > >>>>>>   ...
> > > >>>>>>   .readContinously() / readUntilLatestOffset() /
> > readUntilTimestamp
> > > /
> > > >>>> readUntilOffsets / ...
> > > >>>>>>   .build()
> > > >>>>>>
> > > >>>>>> is way cleaner (and expressive) than
> > > >>>>>>
> > > >>>>>> Source source = KafkaSource.builder()
> > > >>>>>>   ...
> > > >>>>>>   .build()
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> env.continousSource(source) // which actually underneath would
> > call
> > > >>>> createEnumerator(CONTINUOUS, ctx) which would be equivalent to
> > > >>>> source.readContinously().createEnumerator(ctx)
> > > >>>>>> // or
> > > >>>>>> env.boundedSource(source) // which actually underneath would
> call
> > > >>>> createEnumerator(BOUNDED, ctx) which would be equivalent to
> > > >>>> source.readUntilLatestOffset().createEnumerator(ctx)
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> Sorry for the comparison, but to me it seems there is too much
> > magic
> > > >>>>>> happening underneath those two calls.
> > > >>>>>>
> > > >>>>>> I really believe the Source interface should have getBoundedness
> > > >>> method
> > > >>>>>> instead of (supportBoundedness) + createEnumerator(Boundedness,
> > ...)
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> Issue #2 - Design of
> > > >>>>>> ExecutionEnvironment#source()/continuousSource()/boundedSource()
> > > >>>>>>
> > > >>>>>> As you might have guessed I am slightly in favor of option #2
> > > >>> modified.
> > > >>>>>> Yes I am aware every step of the dag would have to be able to
> say
> > if
> > > >>> it
> > > >>>> is
> > > >>>>>> bounded or not. I have a feeling it would be easier to express
> > cross
> > > >>>>>> bounded/unbounded operations, but I must admit I have not
> thought
> > it
> > > >>>>>> through thoroughly, In the spirit of batch is just a special
> case
> > of
> > > >>>>>> streaming I thought BoundedStream would extend from DataStream.
> > > >>> Correct
> > > >>>> me
> > > >>>>>> if I am wrong. In such a setup the cross bounded/unbounded
> > operation
> > > >>>> could
> > > >>>>>> be expressed quite easily I think:
> > > >>>>>>
> > > >>>>>> DataStream {
> > > >>>>>>   DataStream join(DataStream, ...); // we could not really tell
> if
> > > >> the
> > > >>>> result is bounded or not, but because bounded stream is a special
> > case
> > > >> of
> > > >>>> unbounded the API object is correct, irrespective if the left or
> > right
> > > >>> side
> > > >>>> of the join is bounded
> > > >>>>>> }
> > > >>>>>>
> > > >>>>>> BoundedStream extends DataStream {
> > > >>>>>>   BoundedStream join(BoundedStream, ...); // only if both sides
> > are
> > > >>>> bounded the result can be bounded as well. However we do have
> access
> > > to
> > > >>> the
> > > >>>> DataStream#join here, so you can still join with a DataStream
> > > >>>>>> }
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> On the other hand I also see benefits of two completely
> disjointed
> > > >>> APIs,
> > > >>>>>> as we could prohibit some streaming calls in the bounded API. I
> > > >> can't
> > > >>>> think
> > > >>>>>> of any unbounded operators that could not be implemented for
> > bounded
> > > >>>> stream.
> > > >>>>>>
> > > >>>>>> Besides I think we both agree we don't like the method:
> > > >>>>>>
> > > >>>>>> DataStream boundedStream(Source)
> > > >>>>>>
> > > >>>>>> suggested in the current state of the FLIP. Do we ? :)
> > > >>>>>>
> > > >>>>>> Best,
> > > >>>>>>
> > > >>>>>> Dawid
> > > >>>>>>
> > > >>>>>> On 10/12/2019 18:57, Becket Qin wrote:
> > > >>>>>>
> > > >>>>>> Hi folks,
> > > >>>>>>
> > > >>>>>> Thanks for the discussion, great feedback. Also thanks Dawid for
> > the
> > > >>>>>> explanation, it is much clearer now.
> > > >>>>>>
> > > >>>>>> One thing that is indeed missing from the FLIP is how the
> > > >> boundedness
> > > >>> is
> > > >>>>>> passed to the Source implementation. So the API should be
> > > >>>>>> Source#createEnumerator(Boundedness boundedness,
> > > >>> SplitEnumeratorContext
> > > >>>>>> context)
> > > >>>>>> And we can probably remove the
> > Source#supportBoundedness(Boundedness
> > > >>>>>> boundedness) method.
> > > >>>>>>
> > > >>>>>> Assuming we have that, we are essentially choosing from one of
> the
> > > >>>>>> following two options:
> > > >>>>>>
> > > >>>>>> Option 1:
> > > >>>>>> // The source is continuous source, and only unbounded
> operations
> > > >> can
> > > >>> be
> > > >>>>>> performed.
> > > >>>>>> DataStream<Type> datastream = env.continuousSource(someSource);
> > > >>>>>>
> > > >>>>>> // The source is bounded source, both bounded and unbounded
> > > >> operations
> > > >>>> can
> > > >>>>>> be performed.
> > > >>>>>> BoundedDataStream<Type> boundedDataStream =
> > > >>>> env.boundedSource(someSource);
> > > >>>>>>
> > > >>>>>>   - Pros:
> > > >>>>>>        a) explicit boundary between bounded / unbounded streams,
> > it
> > > >> is
> > > >>>>>> quite simple and clear to the users.
> > > >>>>>>   - Cons:
> > > >>>>>>        a) For applications that do not involve bounded
> operations,
> > > >> they
> > > >>>>>> still have to call different API to distinguish bounded /
> > unbounded
> > > >>>> streams.
> > > >>>>>>        b) No support for bounded stream to run in a streaming
> > > runtime
> > > >>>>>> setting, i.e. scheduling and operators behaviors.
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> Option 2:
> > > >>>>>> // The source is either bounded or unbounded, but only unbounded
> > > >>>> operations
> > > >>>>>> could be performed on the returned DataStream.
> > > >>>>>> DataStream<Type> dataStream = env.source(someSource);
> > > >>>>>>
> > > >>>>>> // The source must be a bounded source, otherwise exception is
> > > >> thrown.
> > > >>>>>> BoundedDataStream<Type> boundedDataStream =
> > > >>>>>> env.boundedSource(boundedSource);
> > > >>>>>>
> > > >>>>>> The pros and cons are exactly the opposite of option 1.
> > > >>>>>>   - Pros:
> > > >>>>>>        a) For applications that do not involve bounded
> operations,
> > > >> they
> > > >>>>>> still have to call different API to distinguish bounded /
> > unbounded
> > > >>>> streams.
> > > >>>>>>        b) Support for bounded stream to run in a streaming
> runtime
> > > >>>> setting,
> > > >>>>>> i.e. scheduling and operators behaviors.
> > > >>>>>>   - Cons:
> > > >>>>>>        a) Bounded / unbounded streams are kind of mixed, i.e.
> > given
> > > a
> > > >>>>>> DataStream, it is not clear whether it is bounded or not, unless
> > you
> > > >>>> have
> > > >>>>>> the access to its source.
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> If we only think from the Source API perspective, option 2
> seems a
> > > >>>> better
> > > >>>>>> choice because functionality wise it is a superset of option 1,
> at
> > > >> the
> > > >>>> cost
> > > >>>>>> of some seemingly acceptable ambiguity in the DataStream API.
> > > >>>>>> But if we look at the DataStream API as a whole, option 1 seems
> a
> > > >>>> clearer
> > > >>>>>> choice. For example, some times a library may have to know
> > whether a
> > > >>>>>> certain task will finish or not. And it would be difficult to
> tell
> > > >> if
> > > >>>> the
> > > >>>>>> input is a DataStream, unless additional information is provided
> > all
> > > >>> the
> > > >>>>>> way from the Source. One possible solution is to have a
> *modified
> > > >>>> option 2*
> > > >>>>>> which adds a method to the DataStream API to indicate
> boundedness,
> > > >>> such
> > > >>>> as
> > > >>>>>> getBoundedness(). It would solve the problem with a potential
> > > >>> confusion
> > > >>>> of
> > > >>>>>> what is difference between a DataStream with
> getBoundedness()=true
> > > >>> and a
> > > >>>>>> BoundedDataStream. But that seems not super difficult to
> explain.
> > > >>>>>>
> > > >>>>>> So from API's perspective, I don't have a strong opinion between
> > > >>>> *option 1*
> > > >>>>>> and *modified option 2. *I like the cleanness of option 1, but
> > > >>> modified
> > > >>>>>> option 2 would be more attractive if we have concrete use case
> for
> > > >> the
> > > >>>>>> "Bounded stream with unbounded streaming runtime settings".
> > > >>>>>>
> > > >>>>>> Re: Till
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> Maybe this has already been asked before but I was wondering why
> > the
> > > >>>>>> SourceReader interface has the method pollNext which hands the
> > > >>>>>> responsibility of outputting elements to the SourceReader
> > > >>>> implementation?
> > > >>>>>> Has this been done for backwards compatibility reasons with the
> > old
> > > >>>> source
> > > >>>>>> interface? If not, then one could define a Collection<E>
> > > >>>> getNextRecords()
> > > >>>>>> method which returns the currently retrieved records and then
> the
> > > >>> caller
> > > >>>>>> emits them outside of the SourceReader. That way the interface
> > would
> > > >>> not
> > > >>>>>> allow to implement an outputting loop where we never hand back
> > > >> control
> > > >>>> to
> > > >>>>>> the caller. At the moment, this contract can be easily broken
> and
> > is
> > > >>>> only
> > > >>>>>> mentioned loosely in the JavaDocs.
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> The primary reason we handover the SourceOutput to the
> > SourceReader
> > > >> is
> > > >>>>>> because sometimes it is difficult for a SourceReader to emit one
> > > >>> record
> > > >>>> at
> > > >>>>>> a time. One example is some batched messaging systems which only
> > > >> have
> > > >>> an
> > > >>>>>> offset for the entire batch instead of individual messages in
> the
> > > >>>> batch. In
> > > >>>>>> that case, returning one record at a time would leave the
> > > >> SourceReader
> > > >>>> in
> > > >>>>>> an uncheckpointable state because they can only checkpoint at
> the
> > > >>> batch
> > > >>>>>> boundaries.
> > > >>>>>>
> > > >>>>>> Thanks,
> > > >>>>>>
> > > >>>>>> Jiangjie (Becket) Qin
> > > >>>>>>
> > > >>>>>> On Tue, Dec 10, 2019 at 5:33 PM Till Rohrmann <
> > [hidden email]
> > > >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> > > >>>> [hidden email]>> wrote:
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> Hi everyone,
> > > >>>>>>
> > > >>>>>> thanks for drafting this FLIP. It reads very well.
> > > >>>>>>
> > > >>>>>> Concerning Dawid's proposal, I tend to agree. The boundedness
> > could
> > > >>> come
> > > >>>>>> from the source and tell the system how to treat the operator
> > > >>>> (scheduling
> > > >>>>>> wise). From a user's perspective it should be fine to get back a
> > > >>>> DataStream
> > > >>>>>> when calling env.source(boundedSource) if he does not need
> special
> > > >>>>>> operations defined on a BoundedDataStream. If he needs this,
> then
> > > >> one
> > > >>>> could
> > > >>>>>> use the method BoundedDataStream
> env.boundedSource(boundedSource).
> > > >>>>>>
> > > >>>>>> If possible, we could enforce the proper usage of
> > > >> env.boundedSource()
> > > >>> by
> > > >>>>>> introducing a BoundedSource type so that one cannot pass an
> > > >>>>>> unbounded source to it. That way users would not be able to
> shoot
> > > >>>>>> themselves in the foot.
> > > >>>>>>
> > > >>>>>> Maybe this has already been asked before but I was wondering why
> > the
> > > >>>>>> SourceReader interface has the method pollNext which hands the
> > > >>>>>> responsibility of outputting elements to the SourceReader
> > > >>>> implementation?
> > > >>>>>> Has this been done for backwards compatibility reasons with the
> > old
> > > >>>> source
> > > >>>>>> interface? If not, then one could define a Collection<E>
> > > >>>> getNextRecords()
> > > >>>>>> method which returns the currently retrieved records and then
> the
> > > >>> caller
> > > >>>>>> emits them outside of the SourceReader. That way the interface
> > would
> > > >>> not
> > > >>>>>> allow to implement an outputting loop where we never hand back
> > > >> control
> > > >>>> to
> > > >>>>>> the caller. At the moment, this contract can be easily broken
> and
> > is
> > > >>>> only
> > > >>>>>> mentioned loosely in the JavaDocs.
> > > >>>>>>
> > > >>>>>> Cheers,
> > > >>>>>> Till
> > > >>>>>>
> > > >>>>>> On Tue, Dec 10, 2019 at 7:49 AM Jingsong Li <
> > [hidden email]
> > > >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> > > >>>> [hidden email]>>
> > > >>>>>> wrote:
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> Hi all,
> > > >>>>>>
> > > >>>>>> I think current design is good.
> > > >>>>>>
> > > >>>>>> My understanding is:
> > > >>>>>>
> > > >>>>>> For execution mode: bounded mode and continuous mode, It's
> totally
> > > >>>>>> different. I don't think we have the ability to integrate the
> two
> > > >>> models
> > > >>>>>>
> > > >>>>>> at
> > > >>>>>>
> > > >>>>>> present. It's about scheduling, memory, algorithms, States, etc.
> > we
> > > >>>>>> shouldn't confuse them.
> > > >>>>>>
> > > >>>>>> For source capabilities: only bounded, only continuous, both
> > bounded
> > > >>> and
> > > >>>>>> continuous.
> > > >>>>>> I think Kafka is a source that can be ran both bounded
> > > >>>>>> and continuous execution mode.
> > > >>>>>> And Kafka with end offset should be ran both bounded
> > > >>>>>> and continuous execution mode.  Using apache Beam with Flink
> > > >> runner, I
> > > >>>>>>
> > > >>>>>> used
> > > >>>>>>
> > > >>>>>> to run a "bounded" Kafka in streaming mode. For our previous
> > > >>> DataStream,
> > > >>>>>>
> > > >>>>>> it
> > > >>>>>>
> > > >>>>>> is not necessarily required that the source cannot be bounded.
> > > >>>>>>
> > > >>>>>> So it is my thought for Dawid's question:
> > > >>>>>> 1.pass a bounded source to continuousSource() +1
> > > >>>>>> 2.pass a continuous source to boundedSource() -1, should throw
> > > >>>> exception.
> > > >>>>>>
> > > >>>>>> In StreamExecutionEnvironment, continuousSource and
> boundedSource
> > > >>> define
> > > >>>>>> the execution mode. It defines a clear boundary of execution
> mode.
> > > >>>>>>
> > > >>>>>> Best,
> > > >>>>>> Jingsong Lee
> > > >>>>>>
> > > >>>>>> On Tue, Dec 10, 2019 at 10:37 AM Jark Wu <[hidden email]
> > <mailto:
> > > >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> > > wrote:
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> I agree with Dawid's point that the boundedness information
> should
> > > >>> come
> > > >>>>>> from the source itself (e.g. the end timestamp), not through
> > > >>>>>> env.boundedSouce()/continuousSource().
> > > >>>>>> I think if we want to support something like `env.source()` that
> > > >>> derive
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> execution mode from source, `supportsBoundedness(Boundedness)`
> > > >>>>>> method is not enough, because we don't know whether it is
> bounded
> > or
> > > >>>>>>
> > > >>>>>> not.
> > > >>>>>>
> > > >>>>>> Best,
> > > >>>>>> Jark
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <
> > > >> [hidden email]
> > > >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> > > >>>> [hidden email]>>
> > > >>>>>> wrote:
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> One more thing. In the current proposal, with the
> > > >>>>>> supportsBoundedness(Boundedness) method and the boundedness
> coming
> > > >>>>>>
> > > >>>>>> from
> > > >>>>>>
> > > >>>>>> either continuousSource or boundedSource I could not find how
> this
> > > >>>>>> information is fed back to the SplitEnumerator.
> > > >>>>>>
> > > >>>>>> Best,
> > > >>>>>>
> > > >>>>>> Dawid
> > > >>>>>>
> > > >>>>>> On 09/12/2019 13:52, Becket Qin wrote:
> > > >>>>>>
> > > >>>>>> Hi Dawid,
> > > >>>>>>
> > > >>>>>> Thanks for the comments. This actually brings another relevant
> > > >>>>>>
> > > >>>>>> question
> > > >>>>>>
> > > >>>>>> about what does a "bounded source" imply. I actually had the
> same
> > > >>>>>> impression when I look at the Source API. Here is what I
> > understand
> > > >>>>>>
> > > >>>>>> after
> > > >>>>>>
> > > >>>>>> some discussion with Stephan. The bounded source has the
> following
> > > >>>>>>
> > > >>>>>> impacts.
> > > >>>>>>
> > > >>>>>> 1. API validity.
> > > >>>>>> - A bounded source generates a bounded stream so some operations
> > > >>>>>>
> > > >>>>>> that
> > > >>>>>>
> > > >>>>>> only
> > > >>>>>>
> > > >>>>>> works for bounded records would be performed, e.g. sort.
> > > >>>>>> - To expose these bounded stream only APIs, there are two
> options:
> > > >>>>>>      a. Add them to the DataStream API and throw exception if a
> > > >>>>>>
> > > >>>>>> method
> > > >>>>>>
> > > >>>>>> is
> > > >>>>>>
> > > >>>>>> called on an unbounded stream.
> > > >>>>>>      b. Create a BoundedDataStream class which is returned from
> > > >>>>>> env.boundedSource(), while DataStream is returned from
> > > >>>>>>
> > > >>>>>> env.continousSource().
> > > >>>>>>
> > > >>>>>> Note that this cannot be done by having single
> > > >>>>>>
> > > >>>>>> env.source(theSource)
> > > >>>>>>
> > > >>>>>> even
> > > >>>>>>
> > > >>>>>> the Source has a getBoundedness() method.
> > > >>>>>>
> > > >>>>>> 2. Scheduling
> > > >>>>>> - A bounded source could be computed stage by stage without
> > > >>>>>>
> > > >>>>>> bringing
> > > >>>>>>
> > > >>>>>> up
> > > >>>>>>
> > > >>>>>> all
> > > >>>>>>
> > > >>>>>> the tasks at the same time.
> > > >>>>>>
> > > >>>>>> 3. Operator behaviors
> > > >>>>>> - A bounded source indicates the records are finite so some
> > > >>>>>>
> > > >>>>>> operators
> > > >>>>>>
> > > >>>>>> can
> > > >>>>>>
> > > >>>>>> wait until it receives all the records before it starts the
> > > >>>>>>
> > > >>>>>> processing.
> > > >>>>>>
> > > >>>>>> In the above impact, only 1 is relevant to the API design. And
> the
> > > >>>>>>
> > > >>>>>> current
> > > >>>>>>
> > > >>>>>> proposal in FLIP-27 is following 1.b.
> > > >>>>>>
> > > >>>>>> // boundedness depends of source property, imo this should
> always
> > > >>>>>>
> > > >>>>>> be
> > > >>>>>>
> > > >>>>>> preferred
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> DataStream<MyType> stream = env.source(theSource);
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> In your proposal, does DataStream have bounded stream only
> > methods?
> > > >>>>>>
> > > >>>>>> It
> > > >>>>>>
> > > >>>>>> looks it should have, otherwise passing a bounded Source to
> > > >>>>>>
> > > >>>>>> env.source()
> > > >>>>>>
> > > >>>>>> would be confusing. In that case, we will essentially do 1.a if
> an
> > > >>>>>> unbounded Source is created from env.source(unboundedSource).
> > > >>>>>>
> > > >>>>>> If we have the methods only supported for bounded streams in
> > > >>>>>>
> > > >>>>>> DataStream,
> > > >>>>>>
> > > >>>>>> it
> > > >>>>>>
> > > >>>>>> seems a little weird to have a separate BoundedDataStream
> > > >>>>>>
> > > >>>>>> interface.
> > > >>>>>>
> > > >>>>>> Am I understand it correctly?
> > > >>>>>>
> > > >>>>>> Thanks,
> > > >>>>>>
> > > >>>>>> Jiangjie (Becket) Qin
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <
> > > >>>>>>
> > > >>>>>> [hidden email] <mailto:[hidden email]>>
> > > >>>>>>
> > > >>>>>> wrote:
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> Hi all,
> > > >>>>>>
> > > >>>>>> Really well written proposal and very important one. I must
> admit
> > > >>>>>>
> > > >>>>>> I
> > > >>>>>>
> > > >>>>>> have
> > > >>>>>>
> > > >>>>>> not understood all the intricacies of it yet.
> > > >>>>>>
> > > >>>>>> One question I have though is about where does the information
> > > >>>>>>
> > > >>>>>> about
> > > >>>>>>
> > > >>>>>> boundedness come from. I think in most cases it is a property of
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> source. As you described it might be e.g. end offset, a flag
> > > >>>>>>
> > > >>>>>> should
> > > >>>>>>
> > > >>>>>> it
> > > >>>>>>
> > > >>>>>> monitor new splits etc. I think it would be a really nice use
> case
> > > >>>>>>
> > > >>>>>> to
> > > >>>>>>
> > > >>>>>> be
> > > >>>>>>
> > > >>>>>> able to say:
> > > >>>>>>
> > > >>>>>> new KafkaSource().readUntil(long timestamp),
> > > >>>>>>
> > > >>>>>> which could work as an "end offset". Moreover I think all
> Bounded
> > > >>>>>>
> > > >>>>>> sources
> > > >>>>>>
> > > >>>>>> support continuous mode, but no intrinsically continuous source
> > > >>>>>>
> > > >>>>>> support
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> Bounded mode. If I understood the proposal correctly it suggest
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> boundedness sort of "comes" from the outside of the source, from
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> invokation of either boundedStream or continousSource.
> > > >>>>>>
> > > >>>>>> I am wondering if it would make sense to actually change the
> > > >>>>>>
> > > >>>>>> method
> > > >>>>>>
> > > >>>>>> boolean Source#supportsBoundedness(Boundedness)
> > > >>>>>>
> > > >>>>>> to
> > > >>>>>>
> > > >>>>>> Boundedness Source#getBoundedness().
> > > >>>>>>
> > > >>>>>> As for the methods #boundedSource, #continousSource, assuming
> the
> > > >>>>>> boundedness is property of the source they do not affect how the
> > > >>>>>>
> > > >>>>>> enumerator
> > > >>>>>>
> > > >>>>>> works, but mostly how the dag is scheduled, right? I am not
> > > >>>>>>
> > > >>>>>> against
> > > >>>>>>
> > > >>>>>> those
> > > >>>>>>
> > > >>>>>> methods, but I think it is a very specific use case to actually
> > > >>>>>>
> > > >>>>>> override
> > > >>>>>>
> > > >>>>>> the property of the source. In general I would expect users to
> > > >>>>>>
> > > >>>>>> only
> > > >>>>>>
> > > >>>>>> call
> > > >>>>>>
> > > >>>>>> env.source(theSource), where the source tells if it is bounded
> or
> > > >>>>>>
> > > >>>>>> not. I
> > > >>>>>>
> > > >>>>>> would suggest considering following set of methods:
> > > >>>>>>
> > > >>>>>> // boundedness depends of source property, imo this should
> always
> > > >>>>>>
> > > >>>>>> be
> > > >>>>>>
> > > >>>>>> preferred
> > > >>>>>>
> > > >>>>>> DataStream<MyType> stream = env.source(theSource);
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> // always continous execution, whether bounded or unbounded
> source
> > > >>>>>>
> > > >>>>>> DataStream<MyType> boundedStream =
> env.continousSource(theSource);
> > > >>>>>>
> > > >>>>>> // imo this would make sense if the BoundedDataStream provides
> > > >>>>>>
> > > >>>>>> additional features unavailable for continous mode
> > > >>>>>>
> > > >>>>>> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> Best,
> > > >>>>>>
> > > >>>>>> Dawid
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> On 04/12/2019 11:25, Stephan Ewen wrote:
> > > >>>>>>
> > > >>>>>> Thanks, Becket, for updating this.
> > > >>>>>>
> > > >>>>>> I agree with moving the aspects you mentioned into separate
> FLIPs
> > > >>>>>>
> > > >>>>>> -
> > > >>>>>>
> > > >>>>>> this
> > > >>>>>>
> > > >>>>>> one way becoming unwieldy in size.
> > > >>>>>>
> > > >>>>>> +1 to the FLIP in its current state. Its a very detailed
> write-up,
> > > >>>>>>
> > > >>>>>> nicely
> > > >>>>>>
> > > >>>>>> done!
> > > >>>>>>
> > > >>>>>> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]
> > > >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> > > >>>> [hidden email]>>
> > > >>>>>>
> > > >>>>>> <
> > > >>>>>>
> > > >>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> > > >>>>>>
> > > >>>>>> Hi all,
> > > >>>>>>
> > > >>>>>> Sorry for the long belated update. I have updated FLIP-27 wiki
> > > >>>>>>
> > > >>>>>> page
> > > >>>>>>
> > > >>>>>> with
> > > >>>>>>
> > > >>>>>> the latest proposals. Some noticeable changes include:
> > > >>>>>> 1. A new generic communication mechanism between SplitEnumerator
> > > >>>>>>
> > > >>>>>> and
> > > >>>>>>
> > > >>>>>> SourceReader.
> > > >>>>>> 2. Some detail API method signature changes.
> > > >>>>>>
> > > >>>>>> We left a few things out of this FLIP and will address them in
> > > >>>>>>
> > > >>>>>> separate
> > > >>>>>>
> > > >>>>>> FLIPs. Including:
> > > >>>>>> 1. Per split event time.
> > > >>>>>> 2. Event time alignment.
> > > >>>>>> 3. Fine grained failover for SplitEnumerator failure.
> > > >>>>>>
> > > >>>>>> Please let us know if you have any question.
> > > >>>>>>
> > > >>>>>> Thanks,
> > > >>>>>>
> > > >>>>>> Jiangjie (Becket) Qin
> > > >>>>>>
> > > >>>>>> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]
> > > >>> <mailto:
> > > >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> > > >>>>>>
> > > >>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> > > >>>>>>
> > > >>>>>> Hi  Łukasz!
> > > >>>>>>
> > > >>>>>> Becket and me are working hard on figuring out the last details
> > > >>>>>>
> > > >>>>>> and
> > > >>>>>>
> > > >>>>>> implementing the first PoC. We would update the FLIP hopefully
> > > >>>>>>
> > > >>>>>> next
> > > >>>>>>
> > > >>>>>> week.
> > > >>>>>>
> > > >>>>>> There is a fair chance that a first version of this will be in
> > > >>>>>>
> > > >>>>>> 1.10,
> > > >>>>>>
> > > >>>>>> but
> > > >>>>>>
> > > >>>>>> I
> > > >>>>>>
> > > >>>>>> think it will take another release to battle test it and migrate
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> connectors.
> > > >>>>>>
> > > >>>>>> Best,
> > > >>>>>> Stephan
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <
> [hidden email]
> > > >>>> <mailto:[hidden email]>
> > > >>>>>>
> > > >>>>>> <
> > > >>>>>>
> > > >>>>>> [hidden email] <mailto:[hidden email]>>
> > > >>>>>>
> > > >>>>>> wrote:
> > > >>>>>>
> > > >>>>>> Hi,
> > > >>>>>>
> > > >>>>>> This proposal looks very promising for us. Do you have any plans
> > > >>>>>>
> > > >>>>>> in
> > > >>>>>>
> > > >>>>>> which
> > > >>>>>>
> > > >>>>>> Flink release it is going to be released? We are thinking on
> > > >>>>>>
> > > >>>>>> using a
> > > >>>>>>
> > > >>>>>> Data
> > > >>>>>>
> > > >>>>>> Set API for our future use cases but on the other hand Data Set
> > > >>>>>>
> > > >>>>>> API
> > > >>>>>>
> > > >>>>>> is
> > > >>>>>>
> > > >>>>>> going to be deprecated so using proposed bounded data streams
> > > >>>>>>
> > > >>>>>> solution
> > > >>>>>>
> > > >>>>>> could be more viable in the long term.
> > > >>>>>>
> > > >>>>>> Thanks,
> > > >>>>>> Łukasz
> > > >>>>>>
> > > >>>>>> On 2019/10/01 15:48:03, Thomas Weise <[hidden email]
> > > >> <mailto:
> > > >>>> [hidden email]>> <[hidden email] <mailto:
> > > >>>> [hidden email]>> <
> > > >>>>>>
> > > >>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> > > >>>>>>
> > > >>>>>> Thanks for putting together this proposal!
> > > >>>>>>
> > > >>>>>> I see that the "Per Split Event Time" and "Event Time Alignment"
> > > >>>>>>
> > > >>>>>> sections
> > > >>>>>>
> > > >>>>>> are still TBD.
> > > >>>>>>
> > > >>>>>> It would probably be good to flesh those out a bit before
> > > >>>>>>
> > > >>>>>> proceeding
> > > >>>>>>
> > > >>>>>> too
> > > >>>>>>
> > > >>>>>> far
> > > >>>>>>
> > > >>>>>> as the event time alignment will probably influence the
> > > >>>>>>
> > > >>>>>> interaction
> > > >>>>>>
> > > >>>>>> with
> > > >>>>>>
> > > >>>>>> the split reader, specifically ReaderStatus
> > > >>>>>>
> > > >>>>>> emitNext(SourceOutput<E>
> > > >>>>>>
> > > >>>>>> output).
> > > >>>>>>
> > > >>>>>> We currently have only one implementation for event time
> alignment
> > > >>>>>>
> > > >>>>>> in
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> Kinesis consumer. The synchronization in that case takes place
> as
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> last
> > > >>>>>>
> > > >>>>>> step before records are emitted downstream (RecordEmitter). With
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> currently proposed interfaces, the equivalent can be implemented
> > > >>>>>>
> > > >>>>>> in
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> reader loop, although note that in the Kinesis consumer the per
> > > >>>>>>
> > > >>>>>> shard
> > > >>>>>>
> > > >>>>>> threads push records.
> > > >>>>>>
> > > >>>>>> Synchronization has not been implemented for the Kafka consumer
> > > >>>>>>
> > > >>>>>> yet.
> > > >>>>>>
> > > >>>>>> https://issues.apache.org/jira/browse/FLINK-12675 <
> > > >>>> https://issues.apache.org/jira/browse/FLINK-12675>
> > > >>>>>>
> > > >>>>>> When I looked at it, I realized that the implementation will
> look
> > > >>>>>>
> > > >>>>>> quite
> > > >>>>>>
> > > >>>>>> different
> > > >>>>>> from Kinesis because it needs to take place in the pull part,
> > > >>>>>>
> > > >>>>>> where
> > > >>>>>>
> > > >>>>>> records
> > > >>>>>>
> > > >>>>>> are taken from the Kafka client. Due to the multiplexing it
> cannot
> > > >>>>>>
> > > >>>>>> be
> > > >>>>>>
> > > >>>>>> done
> > > >>>>>>
> > > >>>>>> by blocking the split thread like it currently works for
> Kinesis.
> > > >>>>>>
> > > >>>>>> Reading
> > > >>>>>>
> > > >>>>>> from individual Kafka partitions needs to be controlled via
> > > >>>>>>
> > > >>>>>> pause/resume
> > > >>>>>>
> > > >>>>>> on the Kafka client.
> > > >>>>>>
> > > >>>>>> To take on that responsibility the split thread would need to be
> > > >>>>>>
> > > >>>>>> aware
> > > >>>>>>
> > > >>>>>> of
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>> watermarks or at least whether it should or should not continue
> to
> > > >>>>>>
> > > >>>>>> consume
> > > >>>>>>
> > > >>>>>> a given split and this may require a different SourceReader or
> > > >>>>>>
> > > >>>>>> SourceOutput
> > > >>>>>>
> > > >>>>>> interface.
> > > >>>>>>
> > > >>>>>> Thanks,
> > > >>>>>> Thomas
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email]
> > > >> <mailto:
> > > >>>> [hidden email]>> <[hidden email] <mailto:
> [hidden email]
> > >>
> > > >> <
> > > >>>>>>
> > > >>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> > > >>>>>>
> > > >>>>>> Hi Stephan,
> > > >>>>>>
> > > >>>>>> Thank you for feedback!
> > > >>>>>> Will take a look at your branch before public discussing.
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]
> > > >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> > [hidden email]
> > > >>>>
> > > >>>>>>
> > > >>>>>> <
> > > >>>>>>
> > > >>>>>> [hidden email] <mailto:[hidden email]>>
> > > >>>>>>
> > > >>>>>> wrote:
> > > >>>>>>
> > > >>>>>> Hi Biao!
> > > >>>>>>
> > > >>>>>> Thanks for reviving this. I would like to join this discussion,
> > > >>>>>>
> > > >>>>>> but
> > > >>>>>>
> > > >>>>>> am
> > > >>>>>>
> > > >>>>>> quite occupied with the 1.9 release, so can we maybe pause this
> > > >>>>>>
> > > >>>>>> discussion
> > > >>>>>>
> > > >>>>>> for a week or so?
> > > >>>>>>
> > > >>>>>> In the meantime I can share some suggestion based on prior
> > > >>>>>>
> > > >>>>>> experiments:
> > > >>>>>>
> > > >>>>>> How to do watermarks / timestamp extractors in a simpler and
> more
> > > >>>>>>
> > > >>>>>> flexible
> > > >>>>>>
> > > >>>>>> way. I think that part is quite promising should be part of the
> > > >>>>>>
> > > >>>>>> new
> > > >>>>>>
> > > >>>>>> source
> > > >>>>>>
> > > >>>>>> interface.
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>
> > > >>>
> > > >>
> > >
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> > > >>>> <
> > > >>>>
> > > >>>
> > > >>
> > >
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> > > >>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>
> > > >>>
> > > >>
> > >
> >
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> > > >>>> <
> > > >>>>
> > > >>>
> > > >>
> > >
> >
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> > > >>>>>
> > > >>>>>>
> > > >>>>>> Some experiments on how to build the source reader and its
> > > >>>>>>
> > > >>>>>> library
> > > >>>>>>
> > > >>>>>> for
> > > >>>>>>
> > > >>>>>> common threading/split patterns:
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>
> > > >>>
> > > >>
> > >
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> > > >>>> <
> > > >>>>
> > > >>>
> > > >>
> > >
> >
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> > > >>>>>
> > > >>>>>>
> > > >>>>>> Best,
> > > >>>>>> Stephan
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]
> > > >>> <mailto:
> > > >>>> [hidden email]>> <[hidden email] <mailto:
> [hidden email]
> > >>
> > > >> <
> > > >>>>>>
> > > >>>>>> [hidden email] <mailto:[hidden email]>>
> > > >>>>>>
> > > >>>>>> wrote:
> > > >>>>>>
> > > >>>>>> Hi devs,
> > > >>>>>>
> > > >>>>>> Since 1.9 is nearly released, I think we could get back to
> > > >>>>>>
> > > >>>>>> FLIP-27.
> > > >>>>>>
> > > >>>>>> I
> > > >>>>>>
> > > >>>>>> believe it should be included in 1.10.
> > > >>>>>>
> > > >>>>>> There are so many things mentioned in document of FLIP-27. [1] I
> > > >>>>>>
> > > >>>>>> think
> > > >>>>>>
> > > >>>>>> we'd better discuss them separately. However the wiki is not a
> > > >>>>>>
> > > >>>>>> good
> > > >>>>>>
> > > >>>>>> place
> > > >>>>>>
> > > >>>>>> to discuss. I wrote google doc about SplitReader API which
> > > >>>>>>
> > > >>>>>> misses
> > > >>>>>>
> > > >>>>>> some
> > > >>>>>>
> > > >>>>>> details in the document. [2]
> > > >>>>>>
> > > >>>>>> 1.
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>
> > > >>>
> > > >>
> > >
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> > > >>>> <
> > > >>>>
> > > >>>
> > > >>
> > >
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> > > >>>>>
> > > >>>>>>
> > > >>>>>> 2.
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>
> > > >>>
> > > >>
> > >
> >
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> > > >>>> <
> > > >>>>
> > > >>>
> > > >>
> > >
> >
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> > > >>>>>
> > > >>>>>>
> > > >>>>>> CC Stephan, Aljoscha, Piotrek, Becket
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email]
> > > >> <mailto:
> > > >>>> [hidden email]>> <[hidden email] <mailto:
> [hidden email]
> > >>
> > > >> <
> > > >>>>>>
> > > >>>>>> [hidden email] <mailto:[hidden email]>>
> > > >>>>>>
> > > >>>>>> wrote:
> > > >>>>>>
> > > >>>>>> Hi Steven,
> > > >>>>>> Thank you for the feedback. Please take a look at the document
> > > >>>>>>
> > > >>>>>> FLIP-27
> > > >>>>>>
> > > >>>>>> <
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>
> > > >>>
> > > >>
> > >
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> > > >>>> <
> > > >>>>
> > > >>>
> > > >>
> > >
> >
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> > > >>>>>
> > > >>>>>>
> > > >>>>>> which
> > > >>>>>>
> > > >>>>>> is updated recently. A lot of details of enumerator were added
> > > >>>>>>
> > > >>>>>> in
> > > >>>>>>
> > > >>>>>> this
> > > >>>>>>
> > > >>>>>> document. I think it would help.
> > > >>>>>>
> > > >>>>>> Steven Wu <[hidden email] <mailto:[hidden email]>>
> <
> > > >>>> [hidden email] <mailto:[hidden email]>> <
> > > >>> [hidden email]
> > > >>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> > > >>>> [hidden email]>>
> > > >>>>>>
> > > >>>>>> 于2019年3月28日周四
> > > >>>>>>
> > > >>>>>> 下午12:52写道：
> > > >>>>>>
> > > >>>>>> This proposal mentioned that SplitEnumerator might run on the
> > > >>>>>> JobManager or
> > > >>>>>> in a single task on a TaskManager.
> > > >>>>>>
> > > >>>>>> if enumerator is a single task on a taskmanager, then the job
> > > >>>>>>
> > > >>>>>> DAG
> > > >>>>>>
> > > >>>>>> can
> > > >>>>>>
> > > >>>>>> never
> > > >>>>>> been embarrassingly parallel anymore. That will nullify the
> > > >>>>>>
> > > >>>>>> leverage
> > > >>>>>>
> > > >>>>>> of
> > > >>>>>>
> > > >>>>>> fine-grained recovery for embarrassingly parallel jobs.
> > > >>>>>>
> > > >>>>>> It's not clear to me what's the implication of running
> > > >>>>>>
> > > >>>>>> enumerator
> > > >>>>>>
> > > >>>>>> on
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> jobmanager. So I will leave that out for now.
> > > >>>>>>
> > > >>>>>> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email]
> > > >> <mailto:
> > > >>>> [hidden email]>> <[hidden email] <mailto:
> [hidden email]
> > >>
> > > >> <
> > > >>>>>>
> > > >>>>>> [hidden email] <mailto:[hidden email]>>
> > > >>>>>>
> > > >>>>>> wrote:
> > > >>>>>>
> > > >>>>>> Hi Stephan & Piotrek,
> > > >>>>>>
> > > >>>>>> Thank you for feedback.
> > > >>>>>>
> > > >>>>>> It seems that there are a lot of things to do in community.
> > > >>>>>>
> > > >>>>>> I
> > > >>>>>>
> > > >>>>>> am
> > > >>>>>>
> > > >>>>>> just
> > > >>>>>>
> > > >>>>>> afraid that this discussion may be forgotten since there so
> > > >>>>>>
> > > >>>>>> many
> > > >>>>>>
> > > >>>>>> proposals
> > > >>>>>>
> > > >>>>>> recently.
> > > >>>>>> Anyway, wish to see the split topics soon :)
> > > >>>>>>
> > > >>>>>> Piotr Nowojski <[hidden email] <mailto:
> > [hidden email]
> > > >>>>
> > > >>> <
> > > >>>> [hidden email] <mailto:[hidden email]>> <
> > > >>>> [hidden email] <mailto:[hidden email]>> <
> > > >>>> [hidden email] <mailto:[hidden email]>>
> > > >>>>>>
> > > >>>>>> 于2019年1月24日周四
> > > >>>>>>
> > > >>>>>> 下午8:21写道：
> > > >>>>>>
> > > >>>>>> Hi Biao!
> > > >>>>>>
> > > >>>>>> This discussion was stalled because of preparations for
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> open
> > > >>>>>>
> > > >>>>>> sourcing
> > > >>>>>>
> > > >>>>>> & merging Blink. I think before creating the tickets we
> > > >>>>>>
> > > >>>>>> should
> > > >>>>>>
> > > >>>>>> split this
> > > >>>>>>
> > > >>>>>> discussion into topics/areas outlined by Stephan and
> > > >>>>>>
> > > >>>>>> create
> > > >>>>>>
> > > >>>>>> Flips
> > > >>>>>>
> > > >>>>>> for
> > > >>>>>>
> > > >>>>>> that.
> > > >>>>>>
> > > >>>>>> I think there is no chance for this to be completed in
> > > >>>>>>
> > > >>>>>> couple
> > > >>>>>>
> > > >>>>>> of
> > > >>>>>>
> > > >>>>>> remaining
> > > >>>>>>
> > > >>>>>> weeks/1 month before 1.8 feature freeze, however it would
> > > >>>>>>
> > > >>>>>> be
> > > >>>>>>
> > > >>>>>> good
> > > >>>>>>
> > > >>>>>> to aim
> > > >>>>>>
> > > >>>>>> with those changes for 1.9.
> > > >>>>>>
> > > >>>>>> Piotrek
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email] <mailto:
> > > >>>> [hidden email]>> <[hidden email] <mailto:
> [hidden email]
> > >>
> > > >> <
> > > >>>>>>
> > > >>>>>> [hidden email] <mailto:[hidden email]>>
> > > >>>>>>
> > > >>>>>> wrote:
> > > >>>>>>
> > > >>>>>> Hi community,
> > > >>>>>> The summary of Stephan makes a lot sense to me. It is
> > > >>>>>>
> > > >>>>>> much
> > > >>>>>>
> > > >>>>>> clearer
> > > >>>>>>
> > > >>>>>> indeed
> > > >>>>>>
> > > >>>>>> after splitting the complex topic into small ones.
> > > >>>>>> I was wondering is there any detail plan for next step?
> > > >>>>>>
> > > >>>>>> If
> > > >>>>>>
> > > >>>>>> not,
> > > >>>>>>
> > > >>>>>> I
> > > >>>>>>
> > > >>>>>> would
> > > >>>>>>
> > > >>>>>> like to push this thing forward by creating some JIRA
> > > >>>>>>
> > > >>>>>> issues.
> > > >>>>>>
> > > >>>>>> Another question is that should version 1.8 include
> > > >>>>>>
> > > >>>>>> these
> > > >>>>>>
> > > >>>>>> features?
> > > >>>>>>
> > > >>>>>> Stephan Ewen <[hidden email] <mailto:[hidden email]>> <
> > > >>>> [hidden email] <mailto:[hidden email]>> <[hidden email]
> > > <mailto:
> > > >>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> > > >>>> 于2018年12月1日周六
> > > >>>>>>
> > > >>>>>> 上午4:20写道：
> > > >>>>>>
> > > >>>>>> Thanks everyone for the lively discussion. Let me try
> > > >>>>>>
> > > >>>>>> to
> > > >>>>>>
> > > >>>>>> summarize
> > > >>>>>>
> > > >>>>>> where I
> > > >>>>>>
> > > >>>>>> see convergence in the discussion and open issues.
> > > >>>>>> I'll try to group this by design aspect of the source.
> > > >>>>>>
> > > >>>>>> Please
> > > >>>>>>
> > > >>>>>> let me
> > > >>>>>>
> > > >>>>>> know
> > > >>>>>>
> > > >>>>>> if I got things wrong or missed something crucial here.
> > > >>>>>>
> > > >>>>>> For issues 1-3, if the below reflects the state of the
> > > >>>>>>
> > > >>>>>> discussion, I
> > > >>>>>>
> > > >>>>>> would
> > > >>>>>>
> > > >>>>>> try and update the FLIP in the next days.
> > > >>>>>> For the remaining ones we need more discussion.
> > > >>>>>>
> > > >>>>>> I would suggest to fork each of these aspects into a
> > > >>>>>>
> > > >>>>>> separate
> > > >>>>>>
> > > >>>>>> mail
> > > >>>>>>
> > > >>>>>> thread,
> > > >>>>>>
> > > >>>>>> or will loose sight of the individual aspects.
> > > >>>>>>
> > > >>>>>> *(1) Separation of Split Enumerator and Split Reader*
> > > >>>>>>
> > > >>>>>> - All seem to agree this is a good thing
> > > >>>>>> - Split Enumerator could in the end live on JobManager
> > > >>>>>>
> > > >>>>>> (and
> > > >>>>>>
> > > >>>>>> assign
> > > >>>>>>
> > > >>>>>> splits
> > > >>>>>>
> > > >>>>>> via RPC) or in a task (and assign splits via data
> > > >>>>>>
> > > >>>>>> streams)
> > > >>>>>>
> > > >>>>>> - this discussion is orthogonal and should come later,
> > > >>>>>>
> > > >>>>>> when
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> interface
> > > >>>>>>
> > > >>>>>> is agreed upon.
> > > >>>>>>
> > > >>>>>> *(2) Split Readers for one or more splits*
> > > >>>>>>
> > > >>>>>> - Discussion seems to agree that we need to support
> > > >>>>>>
> > > >>>>>> one
> > > >>>>>>
> > > >>>>>> reader
> > > >>>>>>
> > > >>>>>> that
> > > >>>>>>
> > > >>>>>> possibly handles multiple splits concurrently.
> > > >>>>>> - The requirement comes from sources where one
> > > >>>>>>
> > > >>>>>> poll()-style
> > > >>>>>>
> > > >>>>>> call
> > > >>>>>>
> > > >>>>>> fetches
> > > >>>>>>
> > > >>>>>> data from different splits / partitions
> > > >>>>>>    --> example sources that require that would be for
> > > >>>>>>
> > > >>>>>> example
> > > >>>>>>
> > > >>>>>> Kafka,
> > > >>>>>>
> > > >>>>>> Pravega, Pulsar
> > > >>>>>>
> > > >>>>>> - Could have one split reader per source, or multiple
> > > >>>>>>
> > > >>>>>> split
> > > >>>>>>
> > > >>>>>> readers
> > > >>>>>>
> > > >>>>>> that
> > > >>>>>>
> > > >>>>>> share the "poll()" function
> > > >>>>>> - To not make it too complicated, we can start with
> > > >>>>>>
> > > >>>>>> thinking
> > > >>>>>>
> > > >>>>>> about
> > > >>>>>>
> > > >>>>>> one
> > > >>>>>>
> > > >>>>>> split reader for all splits initially and see if that
> > > >>>>>>
> > > >>>>>> covers
> > > >>>>>>
> > > >>>>>> all
> > > >>>>>>
> > > >>>>>> requirements
> > > >>>>>>
> > > >>>>>> *(3) Threading model of the Split Reader*
> > > >>>>>>
> > > >>>>>> - Most active part of the discussion ;-)
> > > >>>>>>
> > > >>>>>> - A non-blocking way for Flink's task code to interact
> > > >>>>>>
> > > >>>>>> with
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> source
> > > >>>>>>
> > > >>>>>> is
> > > >>>>>>
> > > >>>>>> needed in order to a task runtime code based on a
> > > >>>>>> single-threaded/actor-style task design
> > > >>>>>>    --> I personally am a big proponent of that, it will
> > > >>>>>>
> > > >>>>>> help
> > > >>>>>>
> > > >>>>>> with
> > > >>>>>>
> > > >>>>>> well-behaved checkpoints, efficiency, and simpler yet
> > > >>>>>>
> > > >>>>>> more
> > > >>>>>>
> > > >>>>>> robust
> > > >>>>>>
> > > >>>>>> runtime
> > > >>>>>>
> > > >>>>>> code
> > > >>>>>>
> > > >>>>>> - Users care about simple abstraction, so as a
> > > >>>>>>
> > > >>>>>> subclass
> > > >>>>>>
> > > >>>>>> of
> > > >>>>>>
> > > >>>>>> SplitReader
> > > >>>>>>
> > > >>>>>> (non-blocking / async) we need to have a
> > > >>>>>>
> > > >>>>>> BlockingSplitReader
> > > >>>>>>
> > > >>>>>> which
> > > >>>>>>
> > > >>>>>> will
> > > >>>>>>
> > > >>>>>> form the basis of most source implementations.
> > > >>>>>>
> > > >>>>>> BlockingSplitReader
> > > >>>>>>
> > > >>>>>> lets
> > > >>>>>>
> > > >>>>>> users do blocking simple poll() calls.
> > > >>>>>> - The BlockingSplitReader would spawn a thread (or
> > > >>>>>>
> > > >>>>>> more)
> > > >>>>>>
> > > >>>>>> and
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> thread(s) can make blocking calls and hand over data
> > > >>>>>>
> > > >>>>>> buffers
> > > >>>>>>
> > > >>>>>> via
> > > >>>>>>
> > > >>>>>> a
> > > >>>>>>
> > > >>>>>> blocking
> > > >>>>>>
> > > >>>>>> queue
> > > >>>>>> - This should allow us to cover both, a fully async
> > > >>>>>>
> > > >>>>>> runtime,
> > > >>>>>>
> > > >>>>>> and a
> > > >>>>>>
> > > >>>>>> simple
> > > >>>>>>
> > > >>>>>> blocking interface for users.
> > > >>>>>> - This is actually very similar to how the Kafka
> > > >>>>>>
> > > >>>>>> connectors
> > > >>>>>>
> > > >>>>>> work.
> > > >>>>>>
> > > >>>>>> Kafka
> > > >>>>>>
> > > >>>>>> 9+ with one thread, Kafka 8 with multiple threads
> > > >>>>>>
> > > >>>>>> - On the base SplitReader (the async one), the
> > > >>>>>>
> > > >>>>>> non-blocking
> > > >>>>>>
> > > >>>>>> method
> > > >>>>>>
> > > >>>>>> that
> > > >>>>>>
> > > >>>>>> gets the next chunk of data would signal data
> > > >>>>>>
> > > >>>>>> availability
> > > >>>>>>
> > > >>>>>> via
> > > >>>>>>
> > > >>>>>> a
> > > >>>>>>
> > > >>>>>> CompletableFuture, because that gives the best
> > > >>>>>>
> > > >>>>>> flexibility
> > > >>>>>>
> > > >>>>>> (can
> > > >>>>>>
> > > >>>>>> await
> > > >>>>>>
> > > >>>>>> completion or register notification handlers).
> > > >>>>>> - The source task would register a "thenHandle()" (or
> > > >>>>>>
> > > >>>>>> similar)
> > > >>>>>>
> > > >>>>>> on the
> > > >>>>>>
> > > >>>>>> future to put a "take next data" task into the
> > > >>>>>>
> > > >>>>>> actor-style
> > > >>>>>>
> > > >>>>>> mailbox
> > > >>>>>>
> > > >>>>>> *(4) Split Enumeration and Assignment*
> > > >>>>>>
> > > >>>>>> - Splits may be generated lazily, both in cases where
> > > >>>>>>
> > > >>>>>> there
> > > >>>>>>
> > > >>>>>> is a
> > > >>>>>>
> > > >>>>>> limited
> > > >>>>>>
> > > >>>>>> number of splits (but very many), or splits are
> > > >>>>>>
> > > >>>>>> discovered
> > > >>>>>>
> > > >>>>>> over
> > > >>>>>>
> > > >>>>>> time
> > > >>>>>>
> > > >>>>>> - Assignment should also be lazy, to get better load
> > > >>>>>>
> > > >>>>>> balancing
> > > >>>>>>
> > > >>>>>> - Assignment needs support locality preferences
> > > >>>>>>
> > > >>>>>> - Possible design based on discussion so far:
> > > >>>>>>
> > > >>>>>>    --> SplitReader has a method "addSplits(SplitT...)"
> > > >>>>>>
> > > >>>>>> to
> > > >>>>>>
> > > >>>>>> add
> > > >>>>>>
> > > >>>>>> one or
> > > >>>>>>
> > > >>>>>> more
> > > >>>>>>
> > > >>>>>> splits. Some split readers might assume they have only
> > > >>>>>>
> > > >>>>>> one
> > > >>>>>>
> > > >>>>>> split
> > > >>>>>>
> > > >>>>>> ever,
> > > >>>>>>
> > > >>>>>> concurrently, others assume multiple splits. (Note:
> > > >>>>>>
> > > >>>>>> idea
> > > >>>>>>
> > > >>>>>> behind
> > > >>>>>>
> > > >>>>>> being
> > > >>>>>>
> > > >>>>>> able
> > > >>>>>>
> > > >>>>>> to add multiple splits at the same time is to ease
> > > >>>>>>
> > > >>>>>> startup
> > > >>>>>>
> > > >>>>>> where
> > > >>>>>>
> > > >>>>>> multiple
> > > >>>>>>
> > > >>>>>> splits may be assigned instantly.)
> > > >>>>>>    --> SplitReader has a context object on which it can
> > > >>>>>>
> > > >>>>>> call
> > > >>>>>>
> > > >>>>>> indicate
> > > >>>>>>
> > > >>>>>> when
> > > >>>>>>
> > > >>>>>> splits are completed. The enumerator gets that
> > > >>>>>>
> > > >>>>>> notification and
> > > >>>>>>
> > > >>>>>> can
> > > >>>>>>
> > > >>>>>> use
> > > >>>>>>
> > > >>>>>> to
> > > >>>>>>
> > > >>>>>> decide when to assign new splits. This should help both
> > > >>>>>>
> > > >>>>>> in
> > > >>>>>>
> > > >>>>>> cases
> > > >>>>>>
> > > >>>>>> of
> > > >>>>>>
> > > >>>>>> sources
> > > >>>>>>
> > > >>>>>> that take splits lazily (file readers) and in case the
> > > >>>>>>
> > > >>>>>> source
> > > >>>>>>
> > > >>>>>> needs to
> > > >>>>>>
> > > >>>>>> preserve a partial order between splits (Kinesis,
> > > >>>>>>
> > > >>>>>> Pravega,
> > > >>>>>>
> > > >>>>>> Pulsar may
> > > >>>>>>
> > > >>>>>> need
> > > >>>>>>
> > > >>>>>> that).
> > > >>>>>>    --> SplitEnumerator gets notification when
> > > >>>>>>
> > > >>>>>> SplitReaders
> > > >>>>>>
> > > >>>>>> start
> > > >>>>>>
> > > >>>>>> and
> > > >>>>>>
> > > >>>>>> when
> > > >>>>>>
> > > >>>>>> they finish splits. They can decide at that moment to
> > > >>>>>>
> > > >>>>>> push
> > > >>>>>>
> > > >>>>>> more
> > > >>>>>>
> > > >>>>>> splits
> > > >>>>>>
> > > >>>>>> to
> > > >>>>>>
> > > >>>>>> that reader
> > > >>>>>>    --> The SplitEnumerator should probably be aware of
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> source
> > > >>>>>>
> > > >>>>>> parallelism, to build its initial distribution.
> > > >>>>>>
> > > >>>>>> - Open question: Should the source expose something
> > > >>>>>>
> > > >>>>>> like
> > > >>>>>>
> > > >>>>>> "host
> > > >>>>>>
> > > >>>>>> preferences", so that yarn/mesos/k8s can take this into
> > > >>>>>>
> > > >>>>>> account
> > > >>>>>>
> > > >>>>>> when
> > > >>>>>>
> > > >>>>>> selecting a node to start a TM on?
> > > >>>>>>
> > > >>>>>> *(5) Watermarks and event time alignment*
> > > >>>>>>
> > > >>>>>> - Watermark generation, as well as idleness, needs to
> > > >>>>>>
> > > >>>>>> be
> > > >>>>>>
> > > >>>>>> per
> > > >>>>>>
> > > >>>>>> split
> > > >>>>>>
> > > >>>>>> (like
> > > >>>>>>
> > > >>>>>> currently in the Kafka Source, per partition)
> > > >>>>>> - It is desirable to support optional
> > > >>>>>>
> > > >>>>>> event-time-alignment,
> > > >>>>>>
> > > >>>>>> meaning
> > > >>>>>>
> > > >>>>>> that
> > > >>>>>>
> > > >>>>>> splits that are ahead are back-pressured or temporarily
> > > >>>>>>
> > > >>>>>> unsubscribed
> > > >>>>>>
> > > >>>>>> - I think i would be desirable to encapsulate
> > > >>>>>>
> > > >>>>>> watermark
> > > >>>>>>
> > > >>>>>> generation
> > > >>>>>>
> > > >>>>>> logic
> > > >>>>>>
> > > >>>>>> in watermark generators, for a separation of concerns.
> > > >>>>>>
> > > >>>>>> The
> > > >>>>>>
> > > >>>>>> watermark
> > > >>>>>>
> > > >>>>>> generators should run per split.
> > > >>>>>> - Using watermark generators would also help with
> > > >>>>>>
> > > >>>>>> another
> > > >>>>>>
> > > >>>>>> problem of
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> suggested interface, namely supporting non-periodic
> > > >>>>>>
> > > >>>>>> watermarks
> > > >>>>>>
> > > >>>>>> efficiently.
> > > >>>>>>
> > > >>>>>> - Need a way to "dispatch" next record to different
> > > >>>>>>
> > > >>>>>> watermark
> > > >>>>>>
> > > >>>>>> generators
> > > >>>>>>
> > > >>>>>> - Need a way to tell SplitReader to "suspend" a split
> > > >>>>>>
> > > >>>>>> until a
> > > >>>>>>
> > > >>>>>> certain
> > > >>>>>>
> > > >>>>>> watermark is reached (event time backpressure)
> > > >>>>>> - This would in fact be not needed (and thus simpler)
> > > >>>>>>
> > > >>>>>> if
> > > >>>>>>
> > > >>>>>> we
> > > >>>>>>
> > > >>>>>> had
> > > >>>>>>
> > > >>>>>> a
> > > >>>>>>
> > > >>>>>> SplitReader per split and may be a reason to re-open
> > > >>>>>>
> > > >>>>>> that
> > > >>>>>>
> > > >>>>>> discussion
> > > >>>>>>
> > > >>>>>> *(6) Watermarks across splits and in the Split
> > > >>>>>>
> > > >>>>>> Enumerator*
> > > >>>>>>
> > > >>>>>> - The split enumerator may need some watermark
> > > >>>>>>
> > > >>>>>> awareness,
> > > >>>>>>
> > > >>>>>> which
> > > >>>>>>
> > > >>>>>> should
> > > >>>>>>
> > > >>>>>> be
> > > >>>>>>
> > > >>>>>> purely based on split metadata (like create timestamp
> > > >>>>>>
> > > >>>>>> of
> > > >>>>>>
> > > >>>>>> file
> > > >>>>>>
> > > >>>>>> splits)
> > > >>>>>>
> > > >>>>>> - If there are still more splits with overlapping
> > > >>>>>>
> > > >>>>>> event
> > > >>>>>>
> > > >>>>>> time
> > > >>>>>>
> > > >>>>>> range
> > > >>>>>>
> > > >>>>>> for
> > > >>>>>>
> > > >>>>>> a
> > > >>>>>>
> > > >>>>>> split reader, then that split reader should not advance
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> watermark
> > > >>>>>>
> > > >>>>>> within the split beyond the overlap boundary. Otherwise
> > > >>>>>>
> > > >>>>>> future
> > > >>>>>>
> > > >>>>>> splits
> > > >>>>>>
> > > >>>>>> will
> > > >>>>>>
> > > >>>>>> produce late data.
> > > >>>>>>
> > > >>>>>> - One way to approach this could be that the split
> > > >>>>>>
> > > >>>>>> enumerator
> > > >>>>>>
> > > >>>>>> may
> > > >>>>>>
> > > >>>>>> send
> > > >>>>>>
> > > >>>>>> watermarks to the readers, and the readers cannot emit
> > > >>>>>>
> > > >>>>>> watermarks
> > > >>>>>>
> > > >>>>>> beyond
> > > >>>>>>
> > > >>>>>> that received watermark.
> > > >>>>>> - Many split enumerators would simply immediately send
> > > >>>>>>
> > > >>>>>> Long.MAX
> > > >>>>>>
> > > >>>>>> out
> > > >>>>>>
> > > >>>>>> and
> > > >>>>>>
> > > >>>>>> leave the progress purely to the split readers.
> > > >>>>>>
> > > >>>>>> - For event-time alignment / split back pressure, this
> > > >>>>>>
> > > >>>>>> begs
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> question
> > > >>>>>>
> > > >>>>>> how we can avoid deadlocks that may arise when splits
> > > >>>>>>
> > > >>>>>> are
> > > >>>>>>
> > > >>>>>> suspended
> > > >>>>>>
> > > >>>>>> for
> > > >>>>>>
> > > >>>>>> event time back pressure,
> > > >>>>>>
> > > >>>>>> *(7) Batch and streaming Unification*
> > > >>>>>>
> > > >>>>>> - Functionality wise, the above design should support
> > > >>>>>>
> > > >>>>>> both
> > > >>>>>>
> > > >>>>>> - Batch often (mostly) does not care about reading "in
> > > >>>>>>
> > > >>>>>> order"
> > > >>>>>>
> > > >>>>>> and
> > > >>>>>>
> > > >>>>>> generating watermarks
> > > >>>>>>    --> Might use different enumerator logic that is
> > > >>>>>>
> > > >>>>>> more
> > > >>>>>>
> > > >>>>>> locality
> > > >>>>>>
> > > >>>>>> aware
> > > >>>>>>
> > > >>>>>> and ignores event time order
> > > >>>>>>    --> Does not generate watermarks
> > > >>>>>> - Would be great if bounded sources could be
> > > >>>>>>
> > > >>>>>> identified
> > > >>>>>>
> > > >>>>>> at
> > > >>>>>>
> > > >>>>>> compile
> > > >>>>>>
> > > >>>>>> time,
> > > >>>>>>
> > > >>>>>> so that "env.addBoundedSource(...)" is type safe and
> > > >>>>>>
> > > >>>>>> can
> > > >>>>>>
> > > >>>>>> return a
> > > >>>>>>
> > > >>>>>> "BoundedDataStream".
> > > >>>>>> - Possible to defer this discussion until later
> > > >>>>>>
> > > >>>>>> *Miscellaneous Comments*
> > > >>>>>>
> > > >>>>>> - Should the source have a TypeInformation for the
> > > >>>>>>
> > > >>>>>> produced
> > > >>>>>>
> > > >>>>>> type,
> > > >>>>>>
> > > >>>>>> instead
> > > >>>>>>
> > > >>>>>> of a serializer? We need a type information in the
> > > >>>>>>
> > > >>>>>> stream
> > > >>>>>>
> > > >>>>>> anyways, and
> > > >>>>>>
> > > >>>>>> can
> > > >>>>>>
> > > >>>>>> derive the serializer from that. Plus, creating the
> > > >>>>>>
> > > >>>>>> serializer
> > > >>>>>>
> > > >>>>>> should
> > > >>>>>>
> > > >>>>>> respect the ExecutionConfig.
> > > >>>>>>
> > > >>>>>> - The TypeSerializer interface is very powerful but
> > > >>>>>>
> > > >>>>>> also
> > > >>>>>>
> > > >>>>>> not
> > > >>>>>>
> > > >>>>>> easy to
> > > >>>>>>
> > > >>>>>> implement. Its purpose is to handle data super
> > > >>>>>>
> > > >>>>>> efficiently,
> > > >>>>>>
> > > >>>>>> support
> > > >>>>>>
> > > >>>>>> flexible ways of evolution, etc.
> > > >>>>>> For metadata I would suggest to look at the
> > > >>>>>>
> > > >>>>>> SimpleVersionedSerializer
> > > >>>>>>
> > > >>>>>> instead, which is used for example for checkpoint
> > > >>>>>>
> > > >>>>>> master
> > > >>>>>>
> > > >>>>>> hooks,
> > > >>>>>>
> > > >>>>>> or for
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> streaming file sink. I think that is is a good match
> > > >>>>>>
> > > >>>>>> for
> > > >>>>>>
> > > >>>>>> cases
> > > >>>>>>
> > > >>>>>> where
> > > >>>>>>
> > > >>>>>> we
> > > >>>>>>
> > > >>>>>> do
> > > >>>>>>
> > > >>>>>> not need more than ser/deser (no copy, etc.) and don't
> > > >>>>>>
> > > >>>>>> need to
> > > >>>>>>
> > > >>>>>> push
> > > >>>>>>
> > > >>>>>> versioning out of the serialization paths for best
> > > >>>>>>
> > > >>>>>> performance
> > > >>>>>>
> > > >>>>>> (as in
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> TypeSerializer)
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
> > > >>>>>>
> > > >>>>>> [hidden email]>
> > > >>>>>>
> > > >>>>>> wrote:
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> Hi Biao,
> > > >>>>>>
> > > >>>>>> Thanks for the answer!
> > > >>>>>>
> > > >>>>>> So given the multi-threaded readers, now we have as
> > > >>>>>>
> > > >>>>>> open
> > > >>>>>>
> > > >>>>>> questions:
> > > >>>>>>
> > > >>>>>> 1) How do we let the checkpoints pass through our
> > > >>>>>>
> > > >>>>>> multi-threaded
> > > >>>>>>
> > > >>>>>> reader
> > > >>>>>>
> > > >>>>>> operator?
> > > >>>>>>
> > > >>>>>> 2) Do we have separate reader and source operators or
> > > >>>>>>
> > > >>>>>> not? In
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> strategy
> > > >>>>>>
> > > >>>>>> that has a separate source, the source operator has a
> > > >>>>>>
> > > >>>>>> parallelism of
> > > >>>>>>
> > > >>>>>> 1
> > > >>>>>>
> > > >>>>>> and
> > > >>>>>>
> > > >>>>>> is responsible for split recovery only.
> > > >>>>>>
> > > >>>>>> For the first one, given also the constraints
> > > >>>>>>
> > > >>>>>> (blocking,
> > > >>>>>>
> > > >>>>>> finite
> > > >>>>>>
> > > >>>>>> queues,
> > > >>>>>>
> > > >>>>>> etc), I do not have an answer yet.
> > > >>>>>>
> > > >>>>>> For the 2nd, I think that we should go with separate
> > > >>>>>>
> > > >>>>>> operators
> > > >>>>>>
> > > >>>>>> for
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> source and the readers, for the following reasons:
> > > >>>>>>
> > > >>>>>> 1) This is more aligned with a potential future
> > > >>>>>>
> > > >>>>>> improvement
> > > >>>>>>
> > > >>>>>> where the
> > > >>>>>>
> > > >>>>>> split
> > > >>>>>>
> > > >>>>>> discovery becomes a responsibility of the JobManager
> > > >>>>>>
> > > >>>>>> and
> > > >>>>>>
> > > >>>>>> readers are
> > > >>>>>>
> > > >>>>>> pooling more work from the JM.
> > > >>>>>>
> > > >>>>>> 2) The source is going to be the "single point of
> > > >>>>>>
> > > >>>>>> truth".
> > > >>>>>>
> > > >>>>>> It
> > > >>>>>>
> > > >>>>>> will
> > > >>>>>>
> > > >>>>>> know
> > > >>>>>>
> > > >>>>>> what
> > > >>>>>>
> > > >>>>>> has been processed and what not. If the source and the
> > > >>>>>>
> > > >>>>>> readers
> > > >>>>>>
> > > >>>>>> are a
> > > >>>>>>
> > > >>>>>> single
> > > >>>>>>
> > > >>>>>> operator with parallelism > 1, or in general, if the
> > > >>>>>>
> > > >>>>>> split
> > > >>>>>>
> > > >>>>>> discovery
> > > >>>>>>
> > > >>>>>> is
> > > >>>>>>
> > > >>>>>> done by each task individually, then:
> > > >>>>>>   i) we have to have a deterministic scheme for each
> > > >>>>>>
> > > >>>>>> reader to
> > > >>>>>>
> > > >>>>>> assign
> > > >>>>>>
> > > >>>>>> splits to itself (e.g. mod subtaskId). This is not
> > > >>>>>>
> > > >>>>>> necessarily
> > > >>>>>>
> > > >>>>>> trivial
> > > >>>>>>
> > > >>>>>> for
> > > >>>>>>
> > > >>>>>> all sources.
> > > >>>>>>   ii) each reader would have to keep a copy of all its
> > > >>>>>>
> > > >>>>>> processed
> > > >>>>>>
> > > >>>>>> slpits
> > > >>>>>>
> > > >>>>>>   iii) the state has to be a union state with a
> > > >>>>>>
> > > >>>>>> non-trivial
> > > >>>>>>
> > > >>>>>> merging
> > > >>>>>>
> > > >>>>>> logic
> > > >>>>>>
> > > >>>>>> in order to support rescaling.
> > > >>>>>>
> > > >>>>>> Two additional points that you raised above:
> > > >>>>>>
> > > >>>>>> i) The point that you raised that we need to keep all
> > > >>>>>>
> > > >>>>>> splits
> > > >>>>>>
> > > >>>>>> (processed
> > > >>>>>>
> > > >>>>>> and
> > > >>>>>>
> > > >>>>>> not-processed) I think is a bit of a strong
> > > >>>>>>
> > > >>>>>> requirement.
> > > >>>>>>
> > > >>>>>> This
> > > >>>>>>
> > > >>>>>> would
> > > >>>>>>
> > > >>>>>> imply
> > > >>>>>>
> > > >>>>>> that for infinite sources the state will grow
> > > >>>>>>
> > > >>>>>> indefinitely.
> > > >>>>>>
> > > >>>>>> This is
> > > >>>>>>
> > > >>>>>> problem
> > > >>>>>>
> > > >>>>>> is even more pronounced if we do not have a single
> > > >>>>>>
> > > >>>>>> source
> > > >>>>>>
> > > >>>>>> that
> > > >>>>>>
> > > >>>>>> assigns
> > > >>>>>>
> > > >>>>>> splits to readers, as each reader will have its own
> > > >>>>>>
> > > >>>>>> copy
> > > >>>>>>
> > > >>>>>> of
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> state.
> > > >>>>>>
> > > >>>>>> ii) it is true that for finite sources we need to
> > > >>>>>>
> > > >>>>>> somehow
> > > >>>>>>
> > > >>>>>> not
> > > >>>>>>
> > > >>>>>> close
> > > >>>>>>
> > > >>>>>> the
> > > >>>>>>
> > > >>>>>> readers when the source/split discoverer finishes. The
> > > >>>>>> ContinuousFileReaderOperator has a work-around for
> > > >>>>>>
> > > >>>>>> that.
> > > >>>>>>
> > > >>>>>> It is
> > > >>>>>>
> > > >>>>>> not
> > > >>>>>>
> > > >>>>>> elegant,
> > > >>>>>>
> > > >>>>>> and checkpoints are not emitted after closing the
> > > >>>>>>
> > > >>>>>> source,
> > > >>>>>>
> > > >>>>>> but
> > > >>>>>>
> > > >>>>>> this, I
> > > >>>>>>
> > > >>>>>> believe, is a bigger problem which requires more
> > > >>>>>>
> > > >>>>>> changes
> > > >>>>>>
> > > >>>>>> than
> > > >>>>>>
> > > >>>>>> just
> > > >>>>>>
> > > >>>>>> refactoring the source interface.
> > > >>>>>>
> > > >>>>>> Cheers,
> > > >>>>>> Kostas
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> --
> > > >>>>>> Best, Jingsong Lee
> > > >>>>
> > > >>>>
> > > >>>
> > > >>
> > > >>
> > > >> --
> > > >> Best, Jingsong Lee
> > > >>
> > > >
> > >
> > >
> >
>

[Timo Walther-2]

Hi Becket,

regarding *Option 3* I think we can relax the constraints for env.source():

// MySource can be bounded or unbounded
DataStream<Type> dataStream = env.source(mySource);

// MySource must be bounded, otherwise throws exception.
BoundedDataStream<Type> boundedDataStream = env.boundedSource(mySource);

Bounded is just a special case of unbounded and every bounded source can
also be treated as an unbounded source. This would unify the API if
people don't need a bounded operation. It also addresses Jark's concerns.

Regards,
Timo


On 18.12.19 14:16, Becket Qin wrote:

> Hi Jark,
>
> Please see the reply below:
>
> Regarding to option#3, my concern is that if we don't support streaming
>> mode for bounded source,
>> how could we create a testing source for streaming mode? Currently, all the
>> testing source for streaming
>> are bounded, so that the integration test will finish finally.
>
>
> An UNBOUNDED source does not mean it will never stops. It simply indicates
> that the source *may* run forever, so the runtime needs to be prepared for
> that, but the task may still stop at some point when it hits some
> source-specific condition. So an UNBOUNDED testing source can still stop at
> some point if needed.
>
> Regarding to Source#getRecordOrder(), could we have a implicit contract
>> that unbounded source should
>> already read in order (i.e. reading partitions in parallel), for bounded
>> source the order is not mandatory.
>
>
>
>> This is also the behaviors of the current sources.
>
> 1) a source can't guarantee it reads in strict order, because the producer
>> may produce data not in order.
>> 2) *Bounded-StrictOrder* is not necessary, because batch can reorder data.
>
>
> It is true that sometimes the source cannot guarantee the record order, but
> sometimes it can. Right now, even for stream processing, there is no
> processing order guarantee. For example, a join operator may emit a later
> record which successfully found a join match earlier.
> Event order is one of the most important requirements for event processing,
> a clear order guarantee would be necessary. That said, I agree that right
> now even if the sources provide the record order requirement, the runtime
> is not able to guarantee that out of the box. So I am OK if we add the
> record order to the Source later. But we should avoid misleading users to
> make them think the processing order is guaranteed when using the unbounded
> runtime.
>
> Thanks,
>
> Jiangjie (Becket) Qin
>
> On Wed, Dec 18, 2019 at 10:29 AM Jark Wu <[hidden email]> wrote:
>
>> Hi Becket,
>>
>> That's great we have reached a consensus on Source#getBoundedness().
>>
>> Regarding to option#3, my concern is that if we don't support streaming
>> mode for bounded source,
>> how could we create a testing source for streaming mode? Currently, all the
>> testing source for streaming
>> are bounded, so that the integration test will finish finally.
>>
>> Regarding to Source#getRecordOrder(), could we have a implicit contract
>> that unbounded source should
>> already read in order (i.e. reading partitions in parallel), for bounded
>> source the order is not mandatory.
>> This is also the behaviors of the current sources.
>> 1) a source can't guarantee it reads in strict order, because the producer
>> may produce data not in order.
>> 2) *Bounded-StrictOrder* is not necessary, because batch can reorder data.
>>
>> Best,
>> Jark
>>
>>
>>
>> On Tue, 17 Dec 2019 at 22:03, Becket Qin <[hidden email]> wrote:
>>
>>> Hi folks,
>>>
>>> Thanks for the comments. I am convinced that the Source API should not
>> take
>>> boundedness as a parameter after it is constructed. What Timo and Dawid
>>> suggested sounds a reasonable solution to me. So the Source API would
>>> become:
>>>
>>> Source {
>>>      Boundedness getBoundedness();
>>> }
>>>
>>> Assuming the above Source API, in addition to the two options mentioned
>> in
>>> earlier emails, I am thinking of another option:
>>>
>>> *Option 3:*
>>> // MySource must be unbounded, otherwise throws exception.
>>> DataStream<Type> dataStream = env.source(mySource);
>>>
>>> // MySource must be bounded, otherwise throws exception.
>>> BoundedDataStream<Type> boundedDataStream = env.boundedSource(mySource);
>>>
>>> The pros of this API are:
>>>     a) It fits the requirements from Table / SQL well.
>>>     b) DataStream users still have type safety (option 2 only has partial
>>> type safety).
>>>     c) Cristal clear boundedness from the API which makes DataStream join
>> /
>>> connect easy to reason about.
>>> The caveats I see,
>>>     a) It is inconsistent with Table since Table has one unified
>> interface.
>>>     b) No streaming mode for bounded source.
>>>
>>> @Stephan Ewen <[hidden email]> @Aljoscha Krettek
>>> <[hidden email]> what do you think of the approach?
>>>
>>>
>>> Orthogonal to the above API, I am wondering whether boundedness is the
>> only
>>> dimension needed to describe the characteristic of the Source behavior.
>> We
>>> may also need to have another dimension of *record order*.
>>>
>>> For example, when a file source is reading from a directory with bounded
>>> records, it may have two ways to read.
>>> 1. Read files in parallel.
>>> 2. Read files in the chronological order.
>>> In both cases, the file source is a Bounded Source. However, the
>> processing
>>> requirement for downstream may be different. In the first case, the
>>> record processing and result emitting order does not matter, e.g. word
>>> count. In the second case, the records may have to be processed in the
>>> order they were read, e.g. change log processing.
>>>
>>> If the Source only has a getBoundedness() method, the downstream
>> processors
>>> would not know whether the records emitted from the Source should be
>>> processed in order or not. So combining the boundedness and record order,
>>> we will have four scenarios:
>>>
>>> *Bounded-StrictOrder*:     A segment of change log.
>>> *Bounded-Random*:          Batch Word Count.
>>> *Unbounded-StrictOrder*: An infinite change log.
>>> *Unbounded-Random*:     Streaming Word Count.
>>>
>>> Option 2 mentioned in the previous email was kind of trying to handle the
>>> Bounded-StrictOrder case by creating a DataStream from a bounded source,
>>> which actually does not work.
>>> It looks that we do not have strict order support in some operators at
>> this
>>> point, e.g. join. But we may still want to add the semantic to the Source
>>> first so later on we don't need to change all the source implementations,
>>> especially given that many of them will be implemented by 3rd party.
>>>
>>> Given that, we need another dimension of *Record Order* in the Source.
>> More
>>> specifically, the API would become:
>>>
>>> Source {
>>>      Boundedness getBoundedness();
>>>      RecordOrder getRecordOrder();
>>> }
>>>
>>> public enum RecordOrder {
>>>      /** The record in the DataStream must be processed in its strict
>> order
>>> for correctness. */
>>>      STRICT,
>>>      /** The record in the DataStream can be processed in arbitrary order.
>>> */
>>>      RANDOM;
>>> }
>>>
>>> Any thoughts?
>>>
>>> Thanks,
>>>
>>> Jiangjie (Becket) Qin
>>>
>>> On Tue, Dec 17, 2019 at 3:44 PM Timo Walther <[hidden email]> wrote:
>>>
>>>> Hi Becket,
>>>>
>>>> I completely agree with Dawid's suggestion. The information about the
>>>> boundedness should come out of the source. Because most of the
>> streaming
>>>> sources can be made bounded based on some connector specific criterion.
>>>> In Kafka, it would be an end offset or end timestamp but in any case
>>>> having just a env.boundedSource() is not enough because parameters for
>>>> making the source bounded are missing.
>>>>
>>>> I suggest to have a simple `isBounded(): Boolean` flag in every source
>>>> that might be influenced by a connector builder as Dawid mentioned.
>>>>
>>>> For type safety during programming, we can still go with *Final state
>>>> 1*. By having a env.source() vs env.boundedSource(). The latter would
>>>> just enforce that the boolean flag is set to `true` and could make
>>>> bounded operations available (if we need that actually).
>>>>
>>>> However, I don't think that we should start making a unified Table API
>>>> ununified again. Boundedness is an optimization property. Every bounded
>>>> operation can also executed in an unbounded way using
>> updates/retraction
>>>> or watermarks.
>>>>
>>>> Regards,
>>>> Timo
>>>>
>>>>
>>>> On 15.12.19 14:22, Becket Qin wrote:
>>>>> Hi Dawid and Jark,
>>>>>
>>>>> I think the discussion ultimately boils down to the question that
>> which
>>>> one
>>>>> of the following two final states do we want? Once we make this
>>> decision,
>>>>> everything else can be naturally derived.
>>>>>
>>>>> *Final state 1*: Separate API for bounded / unbounded DataStream &
>>> Table.
>>>>> That means any code users write will be valid at the point when they
>>>> write
>>>>> the code. This is similar to having type safety check at programming
>>>> time.
>>>>> For example,
>>>>>
>>>>> BoundedDataStream extends DataStream {
>>>>> // Operations only available for bounded data.
>>>>> BoundedDataStream sort(...);
>>>>>
>>>>> // Interaction with another BoundedStream returns a Bounded stream.
>>>>> BoundedJoinedDataStream join(BoundedDataStream other)
>>>>>
>>>>> // Interaction with another unbounded stream returns an unbounded
>>> stream.
>>>>> JoinedDataStream join(DataStream other)
>>>>> }
>>>>>
>>>>> BoundedTable extends Table {
>>>>>     // Bounded only operation.
>>>>> BoundedTable sort(...);
>>>>>
>>>>> // Interaction with another BoundedTable returns a BoundedTable.
>>>>> BoundedTable join(BoundedTable other)
>>>>>
>>>>> // Interaction with another unbounded table returns an unbounded
>> table.
>>>>> Table join(Table other)
>>>>> }
>>>>>
>>>>> *Final state 2*: One unified API for bounded / unbounded DataStream /
>>>>> Table.
>>>>> That unified API may throw exception at DAG compilation time if an
>>>> invalid
>>>>> operation is tried. This is what Table API currently follows.
>>>>>
>>>>> DataStream {
>>>>> // Throws exception if the DataStream is unbounded.
>>>>> DataStream sort();
>>>>> // Get boundedness.
>>>>> Boundedness getBoundedness();
>>>>> }
>>>>>
>>>>> Table {
>>>>> // Throws exception if the table has infinite rows.
>>>>> Table orderBy();
>>>>>
>>>>> // Get boundedness.
>>>>> Boundedness getBoundedness();
>>>>> }
>>>>>
>>>>> >From what I understand, there is no consensus so far on this decision
>>>> yet.
>>>>> Whichever final state we choose, we need to make it consistent across
>>> the
>>>>> entire project. We should avoid the case that Table follows one final
>>>> state
>>>>> while DataStream follows another. Some arguments I am aware of from
>>> both
>>>>> sides so far are following:
>>>>>
>>>>> Arguments for final state 1:
>>>>> 1a) Clean API with method safety check at programming time.
>>>>> 1b) (Counter 2b) Although SQL does not have programming time error
>>>> check, SQL
>>>>> is not really a "programming language" per se. So SQL can be
>> different
>>>> from
>>>>> Table and DataStream.
>>>>> 1c)  Although final state 2 seems making it easier for SQL to use
>> given
>>>> it
>>>>> is more "config based" than "parameter based", final state 1 can
>>> probably
>>>>> also meet what SQL wants by wrapping the Source in TableSource /
>>>>> TableSourceFactory API if needed.
>>>>>
>>>>> Arguments for final state 2:
>>>>> 2a) The Source API itself seems already sort of following the unified
>>> API
>>>>> pattern.
>>>>> 2b) There is no "programming time" method error check in SQL case, so
>>> we
>>>>> cannot really achieve final state 1 across the board.
>>>>> 2c) It is an easier path given our current status, i.e. Table is
>>> already
>>>>> following final state 2.
>>>>> 2d) Users can always explicitly check the boundedness if they want
>> to.
>>>>>
>>>>> As I mentioned earlier, my initial thought was also to have a
>>>>> "configuration based" Source rather than a "parameter based" Source.
>> So
>>>> it
>>>>> is completely possible that I missed some important consideration or
>>>> design
>>>>> principles that we want to enforce for the project. It would be good
>>>>> if @Stephan
>>>>> Ewen <[hidden email]> and @Aljoscha Krettek <
>>>> [hidden email]> can
>>>>> also provide more thoughts on this.
>>>>>
>>>>>
>>>>> Re: Jingsong
>>>>>
>>>>> As you said, there are some batched system source, like parquet/orc
>>>> source.
>>>>>> Could we have the batch emit interface to improve performance? The
>>>> queue of
>>>>>> per record may cause performance degradation.
>>>>>
>>>>>
>>>>> The current interface does not necessarily cause performance problem
>>> in a
>>>>> multi-threading case. In fact, the base implementation allows
>>>> SplitReaders
>>>>> to add a batch <E> of records<T> to the records queue<E>, so each
>>> element
>>>>> in the records queue would be a batch <E>. In this case, when the
>> main
>>>>> thread polls records, it will take a batch <E> of records <T> from
>> the
>>>>> shared records queue and process the records <T> in a batch manner.
>>>>>
>>>>> Thanks,
>>>>>
>>>>> Jiangjie (Becket) Qin
>>>>>
>>>>> On Thu, Dec 12, 2019 at 1:29 PM Jingsong Li <[hidden email]>
>>>> wrote:
>>>>>
>>>>>> Hi Becket,
>>>>>>
>>>>>> I also have some performance concerns too.
>>>>>>
>>>>>> If I understand correctly, SourceOutput will emit data per record
>> into
>>>> the
>>>>>> queue? I'm worried about the multithreading performance of this
>> queue.
>>>>>>
>>>>>>> One example is some batched messaging systems which only have an
>>> offset
>>>>>> for the entire batch instead of individual messages in the batch.
>>>>>>
>>>>>> As you said, there are some batched system source, like parquet/orc
>>>> source.
>>>>>> Could we have the batch emit interface to improve performance? The
>>>> queue of
>>>>>> per record may cause performance degradation.
>>>>>>
>>>>>> Best,
>>>>>> Jingsong Lee
>>>>>>
>>>>>> On Thu, Dec 12, 2019 at 9:15 AM Jark Wu <[hidden email]> wrote:
>>>>>>
>>>>>>> Hi Becket,
>>>>>>>
>>>>>>> I think Dawid explained things clearly and makes a lot of sense.
>>>>>>> I'm also in favor of #2, because #1 doesn't work for our future
>>> unified
>>>>>>> envrionment.
>>>>>>>
>>>>>>> You can see the vision in this documentation [1]. In the future, we
>>>> would
>>>>>>> like to
>>>>>>> drop the global streaming/batch mode in SQL (i.e.
>>>>>>> EnvironmentSettings#inStreamingMode/inBatchMode).
>>>>>>> A source is bounded or unbounded once defined, so queries can be
>>>> inferred
>>>>>>> from source to run
>>>>>>> in streaming or batch or hybrid mode. However, in #1, we will lose
>>> this
>>>>>>> ability because the framework
>>>>>>> doesn't know whether the source is bounded or unbounded.
>>>>>>>
>>>>>>> Best,
>>>>>>> Jark
>>>>>>>
>>>>>>>
>>>>>>> [1]:
>>>>>>>
>>>>>>>
>>>>>>
>>>>
>>>
>> https://docs.google.com/document/d/1yrKXEIRATfxHJJ0K3t6wUgXAtZq8D-XgvEnvl2uUcr0/edit#heading=h.v4ib17buma1p
>>>>>>>
>>>>>>> On Wed, 11 Dec 2019 at 20:52, Piotr Nowojski <[hidden email]>
>>>>>> wrote:
>>>>>>>
>>>>>>>> Hi,
>>>>>>>>
>>>>>>>> Regarding the:
>>>>>>>>
>>>>>>>> Collection<E> getNextRecords()
>>>>>>>>
>>>>>>>> I’m pretty sure such design would unfortunately impact the
>>> performance
>>>>>>>> (accessing and potentially creating the collection on the hot
>> path).
>>>>>>>>
>>>>>>>> Also the
>>>>>>>>
>>>>>>>> InputStatus emitNext(DataOutput<T> output) throws Exception;
>>>>>>>> or
>>>>>>>> Status pollNext(SourceOutput<T> sourceOutput) throws Exception;
>>>>>>>>
>>>>>>>> Gives us some opportunities in the future, to allow Source hot
>>> looping
>>>>>>>> inside, until it receives some signal “please exit because of some
>>>>>>> reasons”
>>>>>>>> (output collector could return such hint upon collecting the
>>> result).
>>>>>> But
>>>>>>>> that’s another topic outside of this FLIP’s scope.
>>>>>>>>
>>>>>>>> Piotrek
>>>>>>>>
>>>>>>>>> On 11 Dec 2019, at 10:41, Till Rohrmann <[hidden email]>
>>>>>> wrote:
>>>>>>>>>
>>>>>>>>> Hi Becket,
>>>>>>>>>
>>>>>>>>> quick clarification from my side because I think you
>> misunderstood
>>> my
>>>>>>>>> question. I did not suggest to let the SourceReader return only a
>>>>>>> single
>>>>>>>>> record at a time when calling getNextRecords. As the return type
>>>>>>>> indicates,
>>>>>>>>> the method can return an arbitrary number of records.
>>>>>>>>>
>>>>>>>>> Cheers,
>>>>>>>>> Till
>>>>>>>>>
>>>>>>>>> On Wed, Dec 11, 2019 at 10:13 AM Dawid Wysakowicz <
>>>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>>>> wrote:
>>>>>>>>>
>>>>>>>>>> Hi Becket,
>>>>>>>>>>
>>>>>>>>>> Issue #1 - Design of Source interface
>>>>>>>>>>
>>>>>>>>>> I mentioned the lack of a method like
>>>>>>>> Source#createEnumerator(Boundedness
>>>>>>>>>> boundedness, SplitEnumeratorContext context), because without
>> the
>>>>>>>> current
>>>>>>>>>> proposal is not complete/does not work.
>>>>>>>>>>
>>>>>>>>>> If we say that boundedness is an intrinsic property of a source
>>> imo
>>>>>> we
>>>>>>>>>> don't need the Source#createEnumerator(Boundedness boundedness,
>>>>>>>>>> SplitEnumeratorContext context) method.
>>>>>>>>>>
>>>>>>>>>> Assuming a source from my previous example:
>>>>>>>>>>
>>>>>>>>>> Source source = KafkaSource.builder()
>>>>>>>>>>    ...
>>>>>>>>>>    .untilTimestamp(...)
>>>>>>>>>>    .build()
>>>>>>>>>>
>>>>>>>>>> Would the enumerator differ if created like
>>>>>>>>>> source.createEnumerator(CONTINUOUS_UNBOUNDED, ...) vs source
>>>>>>>>>> .createEnumerator(BOUNDED, ...)? I know I am repeating myself,
>> but
>>>>>>> this
>>>>>>>> is
>>>>>>>>>> the part that my opinion differ the most from the current
>>> proposal.
>>>>>> I
>>>>>>>>>> really think it should always be the source that tells if it is
>>>>>>> bounded
>>>>>>>> or
>>>>>>>>>> not. In the current proposal methods
>> continousSource/boundedSource
>>>>>>>> somewhat
>>>>>>>>>> reconfigure the source, which I think is misleading.
>>>>>>>>>>
>>>>>>>>>> I think a call like:
>>>>>>>>>>
>>>>>>>>>> Source source = KafkaSource.builder()
>>>>>>>>>>    ...
>>>>>>>>>>    .readContinously() / readUntilLatestOffset() /
>>> readUntilTimestamp
>>>> /
>>>>>>>> readUntilOffsets / ...
>>>>>>>>>>    .build()
>>>>>>>>>>
>>>>>>>>>> is way cleaner (and expressive) than
>>>>>>>>>>
>>>>>>>>>> Source source = KafkaSource.builder()
>>>>>>>>>>    ...
>>>>>>>>>>    .build()
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> env.continousSource(source) // which actually underneath would
>>> call
>>>>>>>> createEnumerator(CONTINUOUS, ctx) which would be equivalent to
>>>>>>>> source.readContinously().createEnumerator(ctx)
>>>>>>>>>> // or
>>>>>>>>>> env.boundedSource(source) // which actually underneath would
>> call
>>>>>>>> createEnumerator(BOUNDED, ctx) which would be equivalent to
>>>>>>>> source.readUntilLatestOffset().createEnumerator(ctx)
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> Sorry for the comparison, but to me it seems there is too much
>>> magic
>>>>>>>>>> happening underneath those two calls.
>>>>>>>>>>
>>>>>>>>>> I really believe the Source interface should have getBoundedness
>>>>>>> method
>>>>>>>>>> instead of (supportBoundedness) + createEnumerator(Boundedness,
>>> ...)
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> Issue #2 - Design of
>>>>>>>>>> ExecutionEnvironment#source()/continuousSource()/boundedSource()
>>>>>>>>>>
>>>>>>>>>> As you might have guessed I am slightly in favor of option #2
>>>>>>> modified.
>>>>>>>>>> Yes I am aware every step of the dag would have to be able to
>> say
>>> if
>>>>>>> it
>>>>>>>> is
>>>>>>>>>> bounded or not. I have a feeling it would be easier to express
>>> cross
>>>>>>>>>> bounded/unbounded operations, but I must admit I have not
>> thought
>>> it
>>>>>>>>>> through thoroughly, In the spirit of batch is just a special
>> case
>>> of
>>>>>>>>>> streaming I thought BoundedStream would extend from DataStream.
>>>>>>> Correct
>>>>>>>> me
>>>>>>>>>> if I am wrong. In such a setup the cross bounded/unbounded
>>> operation
>>>>>>>> could
>>>>>>>>>> be expressed quite easily I think:
>>>>>>>>>>
>>>>>>>>>> DataStream {
>>>>>>>>>>    DataStream join(DataStream, ...); // we could not really tell
>> if
>>>>>> the
>>>>>>>> result is bounded or not, but because bounded stream is a special
>>> case
>>>>>> of
>>>>>>>> unbounded the API object is correct, irrespective if the left or
>>> right
>>>>>>> side
>>>>>>>> of the join is bounded
>>>>>>>>>> }
>>>>>>>>>>
>>>>>>>>>> BoundedStream extends DataStream {
>>>>>>>>>>    BoundedStream join(BoundedStream, ...); // only if both sides
>>> are
>>>>>>>> bounded the result can be bounded as well. However we do have
>> access
>>>> to
>>>>>>> the
>>>>>>>> DataStream#join here, so you can still join with a DataStream
>>>>>>>>>> }
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On the other hand I also see benefits of two completely
>> disjointed
>>>>>>> APIs,
>>>>>>>>>> as we could prohibit some streaming calls in the bounded API. I
>>>>>> can't
>>>>>>>> think
>>>>>>>>>> of any unbounded operators that could not be implemented for
>>> bounded
>>>>>>>> stream.
>>>>>>>>>>
>>>>>>>>>> Besides I think we both agree we don't like the method:
>>>>>>>>>>
>>>>>>>>>> DataStream boundedStream(Source)
>>>>>>>>>>
>>>>>>>>>> suggested in the current state of the FLIP. Do we ? :)
>>>>>>>>>>
>>>>>>>>>> Best,
>>>>>>>>>>
>>>>>>>>>> Dawid
>>>>>>>>>>
>>>>>>>>>> On 10/12/2019 18:57, Becket Qin wrote:
>>>>>>>>>>
>>>>>>>>>> Hi folks,
>>>>>>>>>>
>>>>>>>>>> Thanks for the discussion, great feedback. Also thanks Dawid for
>>> the
>>>>>>>>>> explanation, it is much clearer now.
>>>>>>>>>>
>>>>>>>>>> One thing that is indeed missing from the FLIP is how the
>>>>>> boundedness
>>>>>>> is
>>>>>>>>>> passed to the Source implementation. So the API should be
>>>>>>>>>> Source#createEnumerator(Boundedness boundedness,
>>>>>>> SplitEnumeratorContext
>>>>>>>>>> context)
>>>>>>>>>> And we can probably remove the
>>> Source#supportBoundedness(Boundedness
>>>>>>>>>> boundedness) method.
>>>>>>>>>>
>>>>>>>>>> Assuming we have that, we are essentially choosing from one of
>> the
>>>>>>>>>> following two options:
>>>>>>>>>>
>>>>>>>>>> Option 1:
>>>>>>>>>> // The source is continuous source, and only unbounded
>> operations
>>>>>> can
>>>>>>> be
>>>>>>>>>> performed.
>>>>>>>>>> DataStream<Type> datastream = env.continuousSource(someSource);
>>>>>>>>>>
>>>>>>>>>> // The source is bounded source, both bounded and unbounded
>>>>>> operations
>>>>>>>> can
>>>>>>>>>> be performed.
>>>>>>>>>> BoundedDataStream<Type> boundedDataStream =
>>>>>>>> env.boundedSource(someSource);
>>>>>>>>>>
>>>>>>>>>>    - Pros:
>>>>>>>>>>         a) explicit boundary between bounded / unbounded streams,
>>> it
>>>>>> is
>>>>>>>>>> quite simple and clear to the users.
>>>>>>>>>>    - Cons:
>>>>>>>>>>         a) For applications that do not involve bounded
>> operations,
>>>>>> they
>>>>>>>>>> still have to call different API to distinguish bounded /
>>> unbounded
>>>>>>>> streams.
>>>>>>>>>>         b) No support for bounded stream to run in a streaming
>>>> runtime
>>>>>>>>>> setting, i.e. scheduling and operators behaviors.
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> Option 2:
>>>>>>>>>> // The source is either bounded or unbounded, but only unbounded
>>>>>>>> operations
>>>>>>>>>> could be performed on the returned DataStream.
>>>>>>>>>> DataStream<Type> dataStream = env.source(someSource);
>>>>>>>>>>
>>>>>>>>>> // The source must be a bounded source, otherwise exception is
>>>>>> thrown.
>>>>>>>>>> BoundedDataStream<Type> boundedDataStream =
>>>>>>>>>> env.boundedSource(boundedSource);
>>>>>>>>>>
>>>>>>>>>> The pros and cons are exactly the opposite of option 1.
>>>>>>>>>>    - Pros:
>>>>>>>>>>         a) For applications that do not involve bounded
>> operations,
>>>>>> they
>>>>>>>>>> still have to call different API to distinguish bounded /
>>> unbounded
>>>>>>>> streams.
>>>>>>>>>>         b) Support for bounded stream to run in a streaming
>> runtime
>>>>>>>> setting,
>>>>>>>>>> i.e. scheduling and operators behaviors.
>>>>>>>>>>    - Cons:
>>>>>>>>>>         a) Bounded / unbounded streams are kind of mixed, i.e.
>>> given
>>>> a
>>>>>>>>>> DataStream, it is not clear whether it is bounded or not, unless
>>> you
>>>>>>>> have
>>>>>>>>>> the access to its source.
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> If we only think from the Source API perspective, option 2
>> seems a
>>>>>>>> better
>>>>>>>>>> choice because functionality wise it is a superset of option 1,
>> at
>>>>>> the
>>>>>>>> cost
>>>>>>>>>> of some seemingly acceptable ambiguity in the DataStream API.
>>>>>>>>>> But if we look at the DataStream API as a whole, option 1 seems
>> a
>>>>>>>> clearer
>>>>>>>>>> choice. For example, some times a library may have to know
>>> whether a
>>>>>>>>>> certain task will finish or not. And it would be difficult to
>> tell
>>>>>> if
>>>>>>>> the
>>>>>>>>>> input is a DataStream, unless additional information is provided
>>> all
>>>>>>> the
>>>>>>>>>> way from the Source. One possible solution is to have a
>> *modified
>>>>>>>> option 2*
>>>>>>>>>> which adds a method to the DataStream API to indicate
>> boundedness,
>>>>>>> such
>>>>>>>> as
>>>>>>>>>> getBoundedness(). It would solve the problem with a potential
>>>>>>> confusion
>>>>>>>> of
>>>>>>>>>> what is difference between a DataStream with
>> getBoundedness()=true
>>>>>>> and a
>>>>>>>>>> BoundedDataStream. But that seems not super difficult to
>> explain.
>>>>>>>>>>
>>>>>>>>>> So from API's perspective, I don't have a strong opinion between
>>>>>>>> *option 1*
>>>>>>>>>> and *modified option 2. *I like the cleanness of option 1, but
>>>>>>> modified
>>>>>>>>>> option 2 would be more attractive if we have concrete use case
>> for
>>>>>> the
>>>>>>>>>> "Bounded stream with unbounded streaming runtime settings".
>>>>>>>>>>
>>>>>>>>>> Re: Till
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> Maybe this has already been asked before but I was wondering why
>>> the
>>>>>>>>>> SourceReader interface has the method pollNext which hands the
>>>>>>>>>> responsibility of outputting elements to the SourceReader
>>>>>>>> implementation?
>>>>>>>>>> Has this been done for backwards compatibility reasons with the
>>> old
>>>>>>>> source
>>>>>>>>>> interface? If not, then one could define a Collection<E>
>>>>>>>> getNextRecords()
>>>>>>>>>> method which returns the currently retrieved records and then
>> the
>>>>>>> caller
>>>>>>>>>> emits them outside of the SourceReader. That way the interface
>>> would
>>>>>>> not
>>>>>>>>>> allow to implement an outputting loop where we never hand back
>>>>>> control
>>>>>>>> to
>>>>>>>>>> the caller. At the moment, this contract can be easily broken
>> and
>>> is
>>>>>>>> only
>>>>>>>>>> mentioned loosely in the JavaDocs.
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> The primary reason we handover the SourceOutput to the
>>> SourceReader
>>>>>> is
>>>>>>>>>> because sometimes it is difficult for a SourceReader to emit one
>>>>>>> record
>>>>>>>> at
>>>>>>>>>> a time. One example is some batched messaging systems which only
>>>>>> have
>>>>>>> an
>>>>>>>>>> offset for the entire batch instead of individual messages in
>> the
>>>>>>>> batch. In
>>>>>>>>>> that case, returning one record at a time would leave the
>>>>>> SourceReader
>>>>>>>> in
>>>>>>>>>> an uncheckpointable state because they can only checkpoint at
>> the
>>>>>>> batch
>>>>>>>>>> boundaries.
>>>>>>>>>>
>>>>>>>>>> Thanks,
>>>>>>>>>>
>>>>>>>>>> Jiangjie (Becket) Qin
>>>>>>>>>>
>>>>>>>>>> On Tue, Dec 10, 2019 at 5:33 PM Till Rohrmann <
>>> [hidden email]
>>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
>>>>>>>> [hidden email]>> wrote:
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> Hi everyone,
>>>>>>>>>>
>>>>>>>>>> thanks for drafting this FLIP. It reads very well.
>>>>>>>>>>
>>>>>>>>>> Concerning Dawid's proposal, I tend to agree. The boundedness
>>> could
>>>>>>> come
>>>>>>>>>> from the source and tell the system how to treat the operator
>>>>>>>> (scheduling
>>>>>>>>>> wise). From a user's perspective it should be fine to get back a
>>>>>>>> DataStream
>>>>>>>>>> when calling env.source(boundedSource) if he does not need
>> special
>>>>>>>>>> operations defined on a BoundedDataStream. If he needs this,
>> then
>>>>>> one
>>>>>>>> could
>>>>>>>>>> use the method BoundedDataStream
>> env.boundedSource(boundedSource).
>>>>>>>>>>
>>>>>>>>>> If possible, we could enforce the proper usage of
>>>>>> env.boundedSource()
>>>>>>> by
>>>>>>>>>> introducing a BoundedSource type so that one cannot pass an
>>>>>>>>>> unbounded source to it. That way users would not be able to
>> shoot
>>>>>>>>>> themselves in the foot.
>>>>>>>>>>
>>>>>>>>>> Maybe this has already been asked before but I was wondering why
>>> the
>>>>>>>>>> SourceReader interface has the method pollNext which hands the
>>>>>>>>>> responsibility of outputting elements to the SourceReader
>>>>>>>> implementation?
>>>>>>>>>> Has this been done for backwards compatibility reasons with the
>>> old
>>>>>>>> source
>>>>>>>>>> interface? If not, then one could define a Collection<E>
>>>>>>>> getNextRecords()
>>>>>>>>>> method which returns the currently retrieved records and then
>> the
>>>>>>> caller
>>>>>>>>>> emits them outside of the SourceReader. That way the interface
>>> would
>>>>>>> not
>>>>>>>>>> allow to implement an outputting loop where we never hand back
>>>>>> control
>>>>>>>> to
>>>>>>>>>> the caller. At the moment, this contract can be easily broken
>> and
>>> is
>>>>>>>> only
>>>>>>>>>> mentioned loosely in the JavaDocs.
>>>>>>>>>>
>>>>>>>>>> Cheers,
>>>>>>>>>> Till
>>>>>>>>>>
>>>>>>>>>> On Tue, Dec 10, 2019 at 7:49 AM Jingsong Li <
>>> [hidden email]
>>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
>>>>>>>> [hidden email]>>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> Hi all,
>>>>>>>>>>
>>>>>>>>>> I think current design is good.
>>>>>>>>>>
>>>>>>>>>> My understanding is:
>>>>>>>>>>
>>>>>>>>>> For execution mode: bounded mode and continuous mode, It's
>> totally
>>>>>>>>>> different. I don't think we have the ability to integrate the
>> two
>>>>>>> models
>>>>>>>>>>
>>>>>>>>>> at
>>>>>>>>>>
>>>>>>>>>> present. It's about scheduling, memory, algorithms, States, etc.
>>> we
>>>>>>>>>> shouldn't confuse them.
>>>>>>>>>>
>>>>>>>>>> For source capabilities: only bounded, only continuous, both
>>> bounded
>>>>>>> and
>>>>>>>>>> continuous.
>>>>>>>>>> I think Kafka is a source that can be ran both bounded
>>>>>>>>>> and continuous execution mode.
>>>>>>>>>> And Kafka with end offset should be ran both bounded
>>>>>>>>>> and continuous execution mode.  Using apache Beam with Flink
>>>>>> runner, I
>>>>>>>>>>
>>>>>>>>>> used
>>>>>>>>>>
>>>>>>>>>> to run a "bounded" Kafka in streaming mode. For our previous
>>>>>>> DataStream,
>>>>>>>>>>
>>>>>>>>>> it
>>>>>>>>>>
>>>>>>>>>> is not necessarily required that the source cannot be bounded.
>>>>>>>>>>
>>>>>>>>>> So it is my thought for Dawid's question:
>>>>>>>>>> 1.pass a bounded source to continuousSource() +1
>>>>>>>>>> 2.pass a continuous source to boundedSource() -1, should throw
>>>>>>>> exception.
>>>>>>>>>>
>>>>>>>>>> In StreamExecutionEnvironment, continuousSource and
>> boundedSource
>>>>>>> define
>>>>>>>>>> the execution mode. It defines a clear boundary of execution
>> mode.
>>>>>>>>>>
>>>>>>>>>> Best,
>>>>>>>>>> Jingsong Lee
>>>>>>>>>>
>>>>>>>>>> On Tue, Dec 10, 2019 at 10:37 AM Jark Wu <[hidden email]
>>> <mailto:
>>>>>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
>>>> wrote:
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> I agree with Dawid's point that the boundedness information
>> should
>>>>>>> come
>>>>>>>>>> from the source itself (e.g. the end timestamp), not through
>>>>>>>>>> env.boundedSouce()/continuousSource().
>>>>>>>>>> I think if we want to support something like `env.source()` that
>>>>>>> derive
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> execution mode from source, `supportsBoundedness(Boundedness)`
>>>>>>>>>> method is not enough, because we don't know whether it is
>> bounded
>>> or
>>>>>>>>>>
>>>>>>>>>> not.
>>>>>>>>>>
>>>>>>>>>> Best,
>>>>>>>>>> Jark
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <
>>>>>> [hidden email]
>>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
>>>>>>>> [hidden email]>>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> One more thing. In the current proposal, with the
>>>>>>>>>> supportsBoundedness(Boundedness) method and the boundedness
>> coming
>>>>>>>>>>
>>>>>>>>>> from
>>>>>>>>>>
>>>>>>>>>> either continuousSource or boundedSource I could not find how
>> this
>>>>>>>>>> information is fed back to the SplitEnumerator.
>>>>>>>>>>
>>>>>>>>>> Best,
>>>>>>>>>>
>>>>>>>>>> Dawid
>>>>>>>>>>
>>>>>>>>>> On 09/12/2019 13:52, Becket Qin wrote:
>>>>>>>>>>
>>>>>>>>>> Hi Dawid,
>>>>>>>>>>
>>>>>>>>>> Thanks for the comments. This actually brings another relevant
>>>>>>>>>>
>>>>>>>>>> question
>>>>>>>>>>
>>>>>>>>>> about what does a "bounded source" imply. I actually had the
>> same
>>>>>>>>>> impression when I look at the Source API. Here is what I
>>> understand
>>>>>>>>>>
>>>>>>>>>> after
>>>>>>>>>>
>>>>>>>>>> some discussion with Stephan. The bounded source has the
>> following
>>>>>>>>>>
>>>>>>>>>> impacts.
>>>>>>>>>>
>>>>>>>>>> 1. API validity.
>>>>>>>>>> - A bounded source generates a bounded stream so some operations
>>>>>>>>>>
>>>>>>>>>> that
>>>>>>>>>>
>>>>>>>>>> only
>>>>>>>>>>
>>>>>>>>>> works for bounded records would be performed, e.g. sort.
>>>>>>>>>> - To expose these bounded stream only APIs, there are two
>> options:
>>>>>>>>>>       a. Add them to the DataStream API and throw exception if a
>>>>>>>>>>
>>>>>>>>>> method
>>>>>>>>>>
>>>>>>>>>> is
>>>>>>>>>>
>>>>>>>>>> called on an unbounded stream.
>>>>>>>>>>       b. Create a BoundedDataStream class which is returned from
>>>>>>>>>> env.boundedSource(), while DataStream is returned from
>>>>>>>>>>
>>>>>>>>>> env.continousSource().
>>>>>>>>>>
>>>>>>>>>> Note that this cannot be done by having single
>>>>>>>>>>
>>>>>>>>>> env.source(theSource)
>>>>>>>>>>
>>>>>>>>>> even
>>>>>>>>>>
>>>>>>>>>> the Source has a getBoundedness() method.
>>>>>>>>>>
>>>>>>>>>> 2. Scheduling
>>>>>>>>>> - A bounded source could be computed stage by stage without
>>>>>>>>>>
>>>>>>>>>> bringing
>>>>>>>>>>
>>>>>>>>>> up
>>>>>>>>>>
>>>>>>>>>> all
>>>>>>>>>>
>>>>>>>>>> the tasks at the same time.
>>>>>>>>>>
>>>>>>>>>> 3. Operator behaviors
>>>>>>>>>> - A bounded source indicates the records are finite so some
>>>>>>>>>>
>>>>>>>>>> operators
>>>>>>>>>>
>>>>>>>>>> can
>>>>>>>>>>
>>>>>>>>>> wait until it receives all the records before it starts the
>>>>>>>>>>
>>>>>>>>>> processing.
>>>>>>>>>>
>>>>>>>>>> In the above impact, only 1 is relevant to the API design. And
>> the
>>>>>>>>>>
>>>>>>>>>> current
>>>>>>>>>>
>>>>>>>>>> proposal in FLIP-27 is following 1.b.
>>>>>>>>>>
>>>>>>>>>> // boundedness depends of source property, imo this should
>> always
>>>>>>>>>>
>>>>>>>>>> be
>>>>>>>>>>
>>>>>>>>>> preferred
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> DataStream<MyType> stream = env.source(theSource);
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> In your proposal, does DataStream have bounded stream only
>>> methods?
>>>>>>>>>>
>>>>>>>>>> It
>>>>>>>>>>
>>>>>>>>>> looks it should have, otherwise passing a bounded Source to
>>>>>>>>>>
>>>>>>>>>> env.source()
>>>>>>>>>>
>>>>>>>>>> would be confusing. In that case, we will essentially do 1.a if
>> an
>>>>>>>>>> unbounded Source is created from env.source(unboundedSource).
>>>>>>>>>>
>>>>>>>>>> If we have the methods only supported for bounded streams in
>>>>>>>>>>
>>>>>>>>>> DataStream,
>>>>>>>>>>
>>>>>>>>>> it
>>>>>>>>>>
>>>>>>>>>> seems a little weird to have a separate BoundedDataStream
>>>>>>>>>>
>>>>>>>>>> interface.
>>>>>>>>>>
>>>>>>>>>> Am I understand it correctly?
>>>>>>>>>>
>>>>>>>>>> Thanks,
>>>>>>>>>>
>>>>>>>>>> Jiangjie (Becket) Qin
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <
>>>>>>>>>>
>>>>>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>>>>>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> Hi all,
>>>>>>>>>>
>>>>>>>>>> Really well written proposal and very important one. I must
>> admit
>>>>>>>>>>
>>>>>>>>>> I
>>>>>>>>>>
>>>>>>>>>> have
>>>>>>>>>>
>>>>>>>>>> not understood all the intricacies of it yet.
>>>>>>>>>>
>>>>>>>>>> One question I have though is about where does the information
>>>>>>>>>>
>>>>>>>>>> about
>>>>>>>>>>
>>>>>>>>>> boundedness come from. I think in most cases it is a property of
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> source. As you described it might be e.g. end offset, a flag
>>>>>>>>>>
>>>>>>>>>> should
>>>>>>>>>>
>>>>>>>>>> it
>>>>>>>>>>
>>>>>>>>>> monitor new splits etc. I think it would be a really nice use
>> case
>>>>>>>>>>
>>>>>>>>>> to
>>>>>>>>>>
>>>>>>>>>> be
>>>>>>>>>>
>>>>>>>>>> able to say:
>>>>>>>>>>
>>>>>>>>>> new KafkaSource().readUntil(long timestamp),
>>>>>>>>>>
>>>>>>>>>> which could work as an "end offset". Moreover I think all
>> Bounded
>>>>>>>>>>
>>>>>>>>>> sources
>>>>>>>>>>
>>>>>>>>>> support continuous mode, but no intrinsically continuous source
>>>>>>>>>>
>>>>>>>>>> support
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> Bounded mode. If I understood the proposal correctly it suggest
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> boundedness sort of "comes" from the outside of the source, from
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> invokation of either boundedStream or continousSource.
>>>>>>>>>>
>>>>>>>>>> I am wondering if it would make sense to actually change the
>>>>>>>>>>
>>>>>>>>>> method
>>>>>>>>>>
>>>>>>>>>> boolean Source#supportsBoundedness(Boundedness)
>>>>>>>>>>
>>>>>>>>>> to
>>>>>>>>>>
>>>>>>>>>> Boundedness Source#getBoundedness().
>>>>>>>>>>
>>>>>>>>>> As for the methods #boundedSource, #continousSource, assuming
>> the
>>>>>>>>>> boundedness is property of the source they do not affect how the
>>>>>>>>>>
>>>>>>>>>> enumerator
>>>>>>>>>>
>>>>>>>>>> works, but mostly how the dag is scheduled, right? I am not
>>>>>>>>>>
>>>>>>>>>> against
>>>>>>>>>>
>>>>>>>>>> those
>>>>>>>>>>
>>>>>>>>>> methods, but I think it is a very specific use case to actually
>>>>>>>>>>
>>>>>>>>>> override
>>>>>>>>>>
>>>>>>>>>> the property of the source. In general I would expect users to
>>>>>>>>>>
>>>>>>>>>> only
>>>>>>>>>>
>>>>>>>>>> call
>>>>>>>>>>
>>>>>>>>>> env.source(theSource), where the source tells if it is bounded
>> or
>>>>>>>>>>
>>>>>>>>>> not. I
>>>>>>>>>>
>>>>>>>>>> would suggest considering following set of methods:
>>>>>>>>>>
>>>>>>>>>> // boundedness depends of source property, imo this should
>> always
>>>>>>>>>>
>>>>>>>>>> be
>>>>>>>>>>
>>>>>>>>>> preferred
>>>>>>>>>>
>>>>>>>>>> DataStream<MyType> stream = env.source(theSource);
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> // always continous execution, whether bounded or unbounded
>> source
>>>>>>>>>>
>>>>>>>>>> DataStream<MyType> boundedStream =
>> env.continousSource(theSource);
>>>>>>>>>>
>>>>>>>>>> // imo this would make sense if the BoundedDataStream provides
>>>>>>>>>>
>>>>>>>>>> additional features unavailable for continous mode
>>>>>>>>>>
>>>>>>>>>> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> Best,
>>>>>>>>>>
>>>>>>>>>> Dawid
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On 04/12/2019 11:25, Stephan Ewen wrote:
>>>>>>>>>>
>>>>>>>>>> Thanks, Becket, for updating this.
>>>>>>>>>>
>>>>>>>>>> I agree with moving the aspects you mentioned into separate
>> FLIPs
>>>>>>>>>>
>>>>>>>>>> -
>>>>>>>>>>
>>>>>>>>>> this
>>>>>>>>>>
>>>>>>>>>> one way becoming unwieldy in size.
>>>>>>>>>>
>>>>>>>>>> +1 to the FLIP in its current state. Its a very detailed
>> write-up,
>>>>>>>>>>
>>>>>>>>>> nicely
>>>>>>>>>>
>>>>>>>>>> done!
>>>>>>>>>>
>>>>>>>>>> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]
>>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
>>>>>>>> [hidden email]>>
>>>>>>>>>>
>>>>>>>>>> <
>>>>>>>>>>
>>>>>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
>>>>>>>>>>
>>>>>>>>>> Hi all,
>>>>>>>>>>
>>>>>>>>>> Sorry for the long belated update. I have updated FLIP-27 wiki
>>>>>>>>>>
>>>>>>>>>> page
>>>>>>>>>>
>>>>>>>>>> with
>>>>>>>>>>
>>>>>>>>>> the latest proposals. Some noticeable changes include:
>>>>>>>>>> 1. A new generic communication mechanism between SplitEnumerator
>>>>>>>>>>
>>>>>>>>>> and
>>>>>>>>>>
>>>>>>>>>> SourceReader.
>>>>>>>>>> 2. Some detail API method signature changes.
>>>>>>>>>>
>>>>>>>>>> We left a few things out of this FLIP and will address them in
>>>>>>>>>>
>>>>>>>>>> separate
>>>>>>>>>>
>>>>>>>>>> FLIPs. Including:
>>>>>>>>>> 1. Per split event time.
>>>>>>>>>> 2. Event time alignment.
>>>>>>>>>> 3. Fine grained failover for SplitEnumerator failure.
>>>>>>>>>>
>>>>>>>>>> Please let us know if you have any question.
>>>>>>>>>>
>>>>>>>>>> Thanks,
>>>>>>>>>>
>>>>>>>>>> Jiangjie (Becket) Qin
>>>>>>>>>>
>>>>>>>>>> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]
>>>>>>> <mailto:
>>>>>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
>>>>>>>>>>
>>>>>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
>>>>>>>>>>
>>>>>>>>>> Hi  Łukasz!
>>>>>>>>>>
>>>>>>>>>> Becket and me are working hard on figuring out the last details
>>>>>>>>>>
>>>>>>>>>> and
>>>>>>>>>>
>>>>>>>>>> implementing the first PoC. We would update the FLIP hopefully
>>>>>>>>>>
>>>>>>>>>> next
>>>>>>>>>>
>>>>>>>>>> week.
>>>>>>>>>>
>>>>>>>>>> There is a fair chance that a first version of this will be in
>>>>>>>>>>
>>>>>>>>>> 1.10,
>>>>>>>>>>
>>>>>>>>>> but
>>>>>>>>>>
>>>>>>>>>> I
>>>>>>>>>>
>>>>>>>>>> think it will take another release to battle test it and migrate
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> connectors.
>>>>>>>>>>
>>>>>>>>>> Best,
>>>>>>>>>> Stephan
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <
>> [hidden email]
>>>>>>>> <mailto:[hidden email]>
>>>>>>>>>>
>>>>>>>>>> <
>>>>>>>>>>
>>>>>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>>>>>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>> Hi,
>>>>>>>>>>
>>>>>>>>>> This proposal looks very promising for us. Do you have any plans
>>>>>>>>>>
>>>>>>>>>> in
>>>>>>>>>>
>>>>>>>>>> which
>>>>>>>>>>
>>>>>>>>>> Flink release it is going to be released? We are thinking on
>>>>>>>>>>
>>>>>>>>>> using a
>>>>>>>>>>
>>>>>>>>>> Data
>>>>>>>>>>
>>>>>>>>>> Set API for our future use cases but on the other hand Data Set
>>>>>>>>>>
>>>>>>>>>> API
>>>>>>>>>>
>>>>>>>>>> is
>>>>>>>>>>
>>>>>>>>>> going to be deprecated so using proposed bounded data streams
>>>>>>>>>>
>>>>>>>>>> solution
>>>>>>>>>>
>>>>>>>>>> could be more viable in the long term.
>>>>>>>>>>
>>>>>>>>>> Thanks,
>>>>>>>>>> Łukasz
>>>>>>>>>>
>>>>>>>>>> On 2019/10/01 15:48:03, Thomas Weise <[hidden email]
>>>>>> <mailto:
>>>>>>>> [hidden email]>> <[hidden email] <mailto:
>>>>>>>> [hidden email]>> <
>>>>>>>>>>
>>>>>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
>>>>>>>>>>
>>>>>>>>>> Thanks for putting together this proposal!
>>>>>>>>>>
>>>>>>>>>> I see that the "Per Split Event Time" and "Event Time Alignment"
>>>>>>>>>>
>>>>>>>>>> sections
>>>>>>>>>>
>>>>>>>>>> are still TBD.
>>>>>>>>>>
>>>>>>>>>> It would probably be good to flesh those out a bit before
>>>>>>>>>>
>>>>>>>>>> proceeding
>>>>>>>>>>
>>>>>>>>>> too
>>>>>>>>>>
>>>>>>>>>> far
>>>>>>>>>>
>>>>>>>>>> as the event time alignment will probably influence the
>>>>>>>>>>
>>>>>>>>>> interaction
>>>>>>>>>>
>>>>>>>>>> with
>>>>>>>>>>
>>>>>>>>>> the split reader, specifically ReaderStatus
>>>>>>>>>>
>>>>>>>>>> emitNext(SourceOutput<E>
>>>>>>>>>>
>>>>>>>>>> output).
>>>>>>>>>>
>>>>>>>>>> We currently have only one implementation for event time
>> alignment
>>>>>>>>>>
>>>>>>>>>> in
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> Kinesis consumer. The synchronization in that case takes place
>> as
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> last
>>>>>>>>>>
>>>>>>>>>> step before records are emitted downstream (RecordEmitter). With
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> currently proposed interfaces, the equivalent can be implemented
>>>>>>>>>>
>>>>>>>>>> in
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> reader loop, although note that in the Kinesis consumer the per
>>>>>>>>>>
>>>>>>>>>> shard
>>>>>>>>>>
>>>>>>>>>> threads push records.
>>>>>>>>>>
>>>>>>>>>> Synchronization has not been implemented for the Kafka consumer
>>>>>>>>>>
>>>>>>>>>> yet.
>>>>>>>>>>
>>>>>>>>>> https://issues.apache.org/jira/browse/FLINK-12675 <
>>>>>>>> https://issues.apache.org/jira/browse/FLINK-12675>
>>>>>>>>>>
>>>>>>>>>> When I looked at it, I realized that the implementation will
>> look
>>>>>>>>>>
>>>>>>>>>> quite
>>>>>>>>>>
>>>>>>>>>> different
>>>>>>>>>> from Kinesis because it needs to take place in the pull part,
>>>>>>>>>>
>>>>>>>>>> where
>>>>>>>>>>
>>>>>>>>>> records
>>>>>>>>>>
>>>>>>>>>> are taken from the Kafka client. Due to the multiplexing it
>> cannot
>>>>>>>>>>
>>>>>>>>>> be
>>>>>>>>>>
>>>>>>>>>> done
>>>>>>>>>>
>>>>>>>>>> by blocking the split thread like it currently works for
>> Kinesis.
>>>>>>>>>>
>>>>>>>>>> Reading
>>>>>>>>>>
>>>>>>>>>> from individual Kafka partitions needs to be controlled via
>>>>>>>>>>
>>>>>>>>>> pause/resume
>>>>>>>>>>
>>>>>>>>>> on the Kafka client.
>>>>>>>>>>
>>>>>>>>>> To take on that responsibility the split thread would need to be
>>>>>>>>>>
>>>>>>>>>> aware
>>>>>>>>>>
>>>>>>>>>> of
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>> watermarks or at least whether it should or should not continue
>> to
>>>>>>>>>>
>>>>>>>>>> consume
>>>>>>>>>>
>>>>>>>>>> a given split and this may require a different SourceReader or
>>>>>>>>>>
>>>>>>>>>> SourceOutput
>>>>>>>>>>
>>>>>>>>>> interface.
>>>>>>>>>>
>>>>>>>>>> Thanks,
>>>>>>>>>> Thomas
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email]
>>>>>> <mailto:
>>>>>>>> [hidden email]>> <[hidden email] <mailto:
>> [hidden email]
>>>>>
>>>>>> <
>>>>>>>>>>
>>>>>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
>>>>>>>>>>
>>>>>>>>>> Hi Stephan,
>>>>>>>>>>
>>>>>>>>>> Thank you for feedback!
>>>>>>>>>> Will take a look at your branch before public discussing.
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]
>>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
>>> [hidden email]
>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> <
>>>>>>>>>>
>>>>>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>>>>>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>> Hi Biao!
>>>>>>>>>>
>>>>>>>>>> Thanks for reviving this. I would like to join this discussion,
>>>>>>>>>>
>>>>>>>>>> but
>>>>>>>>>>
>>>>>>>>>> am
>>>>>>>>>>
>>>>>>>>>> quite occupied with the 1.9 release, so can we maybe pause this
>>>>>>>>>>
>>>>>>>>>> discussion
>>>>>>>>>>
>>>>>>>>>> for a week or so?
>>>>>>>>>>
>>>>>>>>>> In the meantime I can share some suggestion based on prior
>>>>>>>>>>
>>>>>>>>>> experiments:
>>>>>>>>>>
>>>>>>>>>> How to do watermarks / timestamp extractors in a simpler and
>> more
>>>>>>>>>>
>>>>>>>>>> flexible
>>>>>>>>>>
>>>>>>>>>> way. I think that part is quite promising should be part of the
>>>>>>>>>>
>>>>>>>>>> new
>>>>>>>>>>
>>>>>>>>>> source
>>>>>>>>>>
>>>>>>>>>> interface.
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>
>>>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
>>>>>>>> <
>>>>>>>>
>>>>>>>
>>>>>>
>>>>
>>>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>
>>>
>> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
>>>>>>>> <
>>>>>>>>
>>>>>>>
>>>>>>
>>>>
>>>
>> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> Some experiments on how to build the source reader and its
>>>>>>>>>>
>>>>>>>>>> library
>>>>>>>>>>
>>>>>>>>>> for
>>>>>>>>>>
>>>>>>>>>> common threading/split patterns:
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>
>>>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
>>>>>>>> <
>>>>>>>>
>>>>>>>
>>>>>>
>>>>
>>>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> Best,
>>>>>>>>>> Stephan
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]
>>>>>>> <mailto:
>>>>>>>> [hidden email]>> <[hidden email] <mailto:
>> [hidden email]
>>>>>
>>>>>> <
>>>>>>>>>>
>>>>>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>>>>>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>> Hi devs,
>>>>>>>>>>
>>>>>>>>>> Since 1.9 is nearly released, I think we could get back to
>>>>>>>>>>
>>>>>>>>>> FLIP-27.
>>>>>>>>>>
>>>>>>>>>> I
>>>>>>>>>>
>>>>>>>>>> believe it should be included in 1.10.
>>>>>>>>>>
>>>>>>>>>> There are so many things mentioned in document of FLIP-27. [1] I
>>>>>>>>>>
>>>>>>>>>> think
>>>>>>>>>>
>>>>>>>>>> we'd better discuss them separately. However the wiki is not a
>>>>>>>>>>
>>>>>>>>>> good
>>>>>>>>>>
>>>>>>>>>> place
>>>>>>>>>>
>>>>>>>>>> to discuss. I wrote google doc about SplitReader API which
>>>>>>>>>>
>>>>>>>>>> misses
>>>>>>>>>>
>>>>>>>>>> some
>>>>>>>>>>
>>>>>>>>>> details in the document. [2]
>>>>>>>>>>
>>>>>>>>>> 1.
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>
>>>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
>>>>>>>> <
>>>>>>>>
>>>>>>>
>>>>>>
>>>>
>>>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> 2.
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>
>>>
>> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
>>>>>>>> <
>>>>>>>>
>>>>>>>
>>>>>>
>>>>
>>>
>> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> CC Stephan, Aljoscha, Piotrek, Becket
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email]
>>>>>> <mailto:
>>>>>>>> [hidden email]>> <[hidden email] <mailto:
>> [hidden email]
>>>>>
>>>>>> <
>>>>>>>>>>
>>>>>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>>>>>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>> Hi Steven,
>>>>>>>>>> Thank you for the feedback. Please take a look at the document
>>>>>>>>>>
>>>>>>>>>> FLIP-27
>>>>>>>>>>
>>>>>>>>>> <
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>
>>>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
>>>>>>>> <
>>>>>>>>
>>>>>>>
>>>>>>
>>>>
>>>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> which
>>>>>>>>>>
>>>>>>>>>> is updated recently. A lot of details of enumerator were added
>>>>>>>>>>
>>>>>>>>>> in
>>>>>>>>>>
>>>>>>>>>> this
>>>>>>>>>>
>>>>>>>>>> document. I think it would help.
>>>>>>>>>>
>>>>>>>>>> Steven Wu <[hidden email] <mailto:[hidden email]>>
>> <
>>>>>>>> [hidden email] <mailto:[hidden email]>> <
>>>>>>> [hidden email]
>>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
>>>>>>>> [hidden email]>>
>>>>>>>>>>
>>>>>>>>>> 于2019年3月28日周四
>>>>>>>>>>
>>>>>>>>>> 下午12:52写道：
>>>>>>>>>>
>>>>>>>>>> This proposal mentioned that SplitEnumerator might run on the
>>>>>>>>>> JobManager or
>>>>>>>>>> in a single task on a TaskManager.
>>>>>>>>>>
>>>>>>>>>> if enumerator is a single task on a taskmanager, then the job
>>>>>>>>>>
>>>>>>>>>> DAG
>>>>>>>>>>
>>>>>>>>>> can
>>>>>>>>>>
>>>>>>>>>> never
>>>>>>>>>> been embarrassingly parallel anymore. That will nullify the
>>>>>>>>>>
>>>>>>>>>> leverage
>>>>>>>>>>
>>>>>>>>>> of
>>>>>>>>>>
>>>>>>>>>> fine-grained recovery for embarrassingly parallel jobs.
>>>>>>>>>>
>>>>>>>>>> It's not clear to me what's the implication of running
>>>>>>>>>>
>>>>>>>>>> enumerator
>>>>>>>>>>
>>>>>>>>>> on
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> jobmanager. So I will leave that out for now.
>>>>>>>>>>
>>>>>>>>>> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email]
>>>>>> <mailto:
>>>>>>>> [hidden email]>> <[hidden email] <mailto:
>> [hidden email]
>>>>>
>>>>>> <
>>>>>>>>>>
>>>>>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>>>>>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>> Hi Stephan & Piotrek,
>>>>>>>>>>
>>>>>>>>>> Thank you for feedback.
>>>>>>>>>>
>>>>>>>>>> It seems that there are a lot of things to do in community.
>>>>>>>>>>
>>>>>>>>>> I
>>>>>>>>>>
>>>>>>>>>> am
>>>>>>>>>>
>>>>>>>>>> just
>>>>>>>>>>
>>>>>>>>>> afraid that this discussion may be forgotten since there so
>>>>>>>>>>
>>>>>>>>>> many
>>>>>>>>>>
>>>>>>>>>> proposals
>>>>>>>>>>
>>>>>>>>>> recently.
>>>>>>>>>> Anyway, wish to see the split topics soon :)
>>>>>>>>>>
>>>>>>>>>> Piotr Nowojski <[hidden email] <mailto:
>>> [hidden email]
>>>>>>>>
>>>>>>> <
>>>>>>>> [hidden email] <mailto:[hidden email]>> <
>>>>>>>> [hidden email] <mailto:[hidden email]>> <
>>>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>>>>>
>>>>>>>>>> 于2019年1月24日周四
>>>>>>>>>>
>>>>>>>>>> 下午8:21写道：
>>>>>>>>>>
>>>>>>>>>> Hi Biao!
>>>>>>>>>>
>>>>>>>>>> This discussion was stalled because of preparations for
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> open
>>>>>>>>>>
>>>>>>>>>> sourcing
>>>>>>>>>>
>>>>>>>>>> & merging Blink. I think before creating the tickets we
>>>>>>>>>>
>>>>>>>>>> should
>>>>>>>>>>
>>>>>>>>>> split this
>>>>>>>>>>
>>>>>>>>>> discussion into topics/areas outlined by Stephan and
>>>>>>>>>>
>>>>>>>>>> create
>>>>>>>>>>
>>>>>>>>>> Flips
>>>>>>>>>>
>>>>>>>>>> for
>>>>>>>>>>
>>>>>>>>>> that.
>>>>>>>>>>
>>>>>>>>>> I think there is no chance for this to be completed in
>>>>>>>>>>
>>>>>>>>>> couple
>>>>>>>>>>
>>>>>>>>>> of
>>>>>>>>>>
>>>>>>>>>> remaining
>>>>>>>>>>
>>>>>>>>>> weeks/1 month before 1.8 feature freeze, however it would
>>>>>>>>>>
>>>>>>>>>> be
>>>>>>>>>>
>>>>>>>>>> good
>>>>>>>>>>
>>>>>>>>>> to aim
>>>>>>>>>>
>>>>>>>>>> with those changes for 1.9.
>>>>>>>>>>
>>>>>>>>>> Piotrek
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email] <mailto:
>>>>>>>> [hidden email]>> <[hidden email] <mailto:
>> [hidden email]
>>>>>
>>>>>> <
>>>>>>>>>>
>>>>>>>>>> [hidden email] <mailto:[hidden email]>>
>>>>>>>>>>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>> Hi community,
>>>>>>>>>> The summary of Stephan makes a lot sense to me. It is
>>>>>>>>>>
>>>>>>>>>> much
>>>>>>>>>>
>>>>>>>>>> clearer
>>>>>>>>>>
>>>>>>>>>> indeed
>>>>>>>>>>
>>>>>>>>>> after splitting the complex topic into small ones.
>>>>>>>>>> I was wondering is there any detail plan for next step?
>>>>>>>>>>
>>>>>>>>>> If
>>>>>>>>>>
>>>>>>>>>> not,
>>>>>>>>>>
>>>>>>>>>> I
>>>>>>>>>>
>>>>>>>>>> would
>>>>>>>>>>
>>>>>>>>>> like to push this thing forward by creating some JIRA
>>>>>>>>>>
>>>>>>>>>> issues.
>>>>>>>>>>
>>>>>>>>>> Another question is that should version 1.8 include
>>>>>>>>>>
>>>>>>>>>> these
>>>>>>>>>>
>>>>>>>>>> features?
>>>>>>>>>>
>>>>>>>>>> Stephan Ewen <[hidden email] <mailto:[hidden email]>> <
>>>>>>>> [hidden email] <mailto:[hidden email]>> <[hidden email]
>>>> <mailto:
>>>>>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
>>>>>>>> 于2018年12月1日周六
>>>>>>>>>>
>>>>>>>>>> 上午4:20写道：
>>>>>>>>>>
>>>>>>>>>> Thanks everyone for the lively discussion. Let me try
>>>>>>>>>>
>>>>>>>>>> to
>>>>>>>>>>
>>>>>>>>>> summarize
>>>>>>>>>>
>>>>>>>>>> where I
>>>>>>>>>>
>>>>>>>>>> see convergence in the discussion and open issues.
>>>>>>>>>> I'll try to group this by design aspect of the source.
>>>>>>>>>>
>>>>>>>>>> Please
>>>>>>>>>>
>>>>>>>>>> let me
>>>>>>>>>>
>>>>>>>>>> know
>>>>>>>>>>
>>>>>>>>>> if I got things wrong or missed something crucial here.
>>>>>>>>>>
>>>>>>>>>> For issues 1-3, if the below reflects the state of the
>>>>>>>>>>
>>>>>>>>>> discussion, I
>>>>>>>>>>
>>>>>>>>>> would
>>>>>>>>>>
>>>>>>>>>> try and update the FLIP in the next days.
>>>>>>>>>> For the remaining ones we need more discussion.
>>>>>>>>>>
>>>>>>>>>> I would suggest to fork each of these aspects into a
>>>>>>>>>>
>>>>>>>>>> separate
>>>>>>>>>>
>>>>>>>>>> mail
>>>>>>>>>>
>>>>>>>>>> thread,
>>>>>>>>>>
>>>>>>>>>> or will loose sight of the individual aspects.
>>>>>>>>>>
>>>>>>>>>> *(1) Separation of Split Enumerator and Split Reader*
>>>>>>>>>>
>>>>>>>>>> - All seem to agree this is a good thing
>>>>>>>>>> - Split Enumerator could in the end live on JobManager
>>>>>>>>>>
>>>>>>>>>> (and
>>>>>>>>>>
>>>>>>>>>> assign
>>>>>>>>>>
>>>>>>>>>> splits
>>>>>>>>>>
>>>>>>>>>> via RPC) or in a task (and assign splits via data
>>>>>>>>>>
>>>>>>>>>> streams)
>>>>>>>>>>
>>>>>>>>>> - this discussion is orthogonal and should come later,
>>>>>>>>>>
>>>>>>>>>> when
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> interface
>>>>>>>>>>
>>>>>>>>>> is agreed upon.
>>>>>>>>>>
>>>>>>>>>> *(2) Split Readers for one or more splits*
>>>>>>>>>>
>>>>>>>>>> - Discussion seems to agree that we need to support
>>>>>>>>>>
>>>>>>>>>> one
>>>>>>>>>>
>>>>>>>>>> reader
>>>>>>>>>>
>>>>>>>>>> that
>>>>>>>>>>
>>>>>>>>>> possibly handles multiple splits concurrently.
>>>>>>>>>> - The requirement comes from sources where one
>>>>>>>>>>
>>>>>>>>>> poll()-style
>>>>>>>>>>
>>>>>>>>>> call
>>>>>>>>>>
>>>>>>>>>> fetches
>>>>>>>>>>
>>>>>>>>>> data from different splits / partitions
>>>>>>>>>>     --> example sources that require that would be for
>>>>>>>>>>
>>>>>>>>>> example
>>>>>>>>>>
>>>>>>>>>> Kafka,
>>>>>>>>>>
>>>>>>>>>> Pravega, Pulsar
>>>>>>>>>>
>>>>>>>>>> - Could have one split reader per source, or multiple
>>>>>>>>>>
>>>>>>>>>> split
>>>>>>>>>>
>>>>>>>>>> readers
>>>>>>>>>>
>>>>>>>>>> that
>>>>>>>>>>
>>>>>>>>>> share the "poll()" function
>>>>>>>>>> - To not make it too complicated, we can start with
>>>>>>>>>>
>>>>>>>>>> thinking
>>>>>>>>>>
>>>>>>>>>> about
>>>>>>>>>>
>>>>>>>>>> one
>>>>>>>>>>
>>>>>>>>>> split reader for all splits initially and see if that
>>>>>>>>>>
>>>>>>>>>> covers
>>>>>>>>>>
>>>>>>>>>> all
>>>>>>>>>>
>>>>>>>>>> requirements
>>>>>>>>>>
>>>>>>>>>> *(3) Threading model of the Split Reader*
>>>>>>>>>>
>>>>>>>>>> - Most active part of the discussion ;-)
>>>>>>>>>>
>>>>>>>>>> - A non-blocking way for Flink's task code to interact
>>>>>>>>>>
>>>>>>>>>> with
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> source
>>>>>>>>>>
>>>>>>>>>> is
>>>>>>>>>>
>>>>>>>>>> needed in order to a task runtime code based on a
>>>>>>>>>> single-threaded/actor-style task design
>>>>>>>>>>     --> I personally am a big proponent of that, it will
>>>>>>>>>>
>>>>>>>>>> help
>>>>>>>>>>
>>>>>>>>>> with
>>>>>>>>>>
>>>>>>>>>> well-behaved checkpoints, efficiency, and simpler yet
>>>>>>>>>>
>>>>>>>>>> more
>>>>>>>>>>
>>>>>>>>>> robust
>>>>>>>>>>
>>>>>>>>>> runtime
>>>>>>>>>>
>>>>>>>>>> code
>>>>>>>>>>
>>>>>>>>>> - Users care about simple abstraction, so as a
>>>>>>>>>>
>>>>>>>>>> subclass
>>>>>>>>>>
>>>>>>>>>> of
>>>>>>>>>>
>>>>>>>>>> SplitReader
>>>>>>>>>>
>>>>>>>>>> (non-blocking / async) we need to have a
>>>>>>>>>>
>>>>>>>>>> BlockingSplitReader
>>>>>>>>>>
>>>>>>>>>> which
>>>>>>>>>>
>>>>>>>>>> will
>>>>>>>>>>
>>>>>>>>>> form the basis of most source implementations.
>>>>>>>>>>
>>>>>>>>>> BlockingSplitReader
>>>>>>>>>>
>>>>>>>>>> lets
>>>>>>>>>>
>>>>>>>>>> users do blocking simple poll() calls.
>>>>>>>>>> - The BlockingSplitReader would spawn a thread (or
>>>>>>>>>>
>>>>>>>>>> more)
>>>>>>>>>>
>>>>>>>>>> and
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> thread(s) can make blocking calls and hand over data
>>>>>>>>>>
>>>>>>>>>> buffers
>>>>>>>>>>
>>>>>>>>>> via
>>>>>>>>>>
>>>>>>>>>> a
>>>>>>>>>>
>>>>>>>>>> blocking
>>>>>>>>>>
>>>>>>>>>> queue
>>>>>>>>>> - This should allow us to cover both, a fully async
>>>>>>>>>>
>>>>>>>>>> runtime,
>>>>>>>>>>
>>>>>>>>>> and a
>>>>>>>>>>
>>>>>>>>>> simple
>>>>>>>>>>
>>>>>>>>>> blocking interface for users.
>>>>>>>>>> - This is actually very similar to how the Kafka
>>>>>>>>>>
>>>>>>>>>> connectors
>>>>>>>>>>
>>>>>>>>>> work.
>>>>>>>>>>
>>>>>>>>>> Kafka
>>>>>>>>>>
>>>>>>>>>> 9+ with one thread, Kafka 8 with multiple threads
>>>>>>>>>>
>>>>>>>>>> - On the base SplitReader (the async one), the
>>>>>>>>>>
>>>>>>>>>> non-blocking
>>>>>>>>>>
>>>>>>>>>> method
>>>>>>>>>>
>>>>>>>>>> that
>>>>>>>>>>
>>>>>>>>>> gets the next chunk of data would signal data
>>>>>>>>>>
>>>>>>>>>> availability
>>>>>>>>>>
>>>>>>>>>> via
>>>>>>>>>>
>>>>>>>>>> a
>>>>>>>>>>
>>>>>>>>>> CompletableFuture, because that gives the best
>>>>>>>>>>
>>>>>>>>>> flexibility
>>>>>>>>>>
>>>>>>>>>> (can
>>>>>>>>>>
>>>>>>>>>> await
>>>>>>>>>>
>>>>>>>>>> completion or register notification handlers).
>>>>>>>>>> - The source task would register a "thenHandle()" (or
>>>>>>>>>>
>>>>>>>>>> similar)
>>>>>>>>>>
>>>>>>>>>> on the
>>>>>>>>>>
>>>>>>>>>> future to put a "take next data" task into the
>>>>>>>>>>
>>>>>>>>>> actor-style
>>>>>>>>>>
>>>>>>>>>> mailbox
>>>>>>>>>>
>>>>>>>>>> *(4) Split Enumeration and Assignment*
>>>>>>>>>>
>>>>>>>>>> - Splits may be generated lazily, both in cases where
>>>>>>>>>>
>>>>>>>>>> there
>>>>>>>>>>
>>>>>>>>>> is a
>>>>>>>>>>
>>>>>>>>>> limited
>>>>>>>>>>
>>>>>>>>>> number of splits (but very many), or splits are
>>>>>>>>>>
>>>>>>>>>> discovered
>>>>>>>>>>
>>>>>>>>>> over
>>>>>>>>>>
>>>>>>>>>> time
>>>>>>>>>>
>>>>>>>>>> - Assignment should also be lazy, to get better load
>>>>>>>>>>
>>>>>>>>>> balancing
>>>>>>>>>>
>>>>>>>>>> - Assignment needs support locality preferences
>>>>>>>>>>
>>>>>>>>>> - Possible design based on discussion so far:
>>>>>>>>>>
>>>>>>>>>>     --> SplitReader has a method "addSplits(SplitT...)"
>>>>>>>>>>
>>>>>>>>>> to
>>>>>>>>>>
>>>>>>>>>> add
>>>>>>>>>>
>>>>>>>>>> one or
>>>>>>>>>>
>>>>>>>>>> more
>>>>>>>>>>
>>>>>>>>>> splits. Some split readers might assume they have only
>>>>>>>>>>
>>>>>>>>>> one
>>>>>>>>>>
>>>>>>>>>> split
>>>>>>>>>>
>>>>>>>>>> ever,
>>>>>>>>>>
>>>>>>>>>> concurrently, others assume multiple splits. (Note:
>>>>>>>>>>
>>>>>>>>>> idea
>>>>>>>>>>
>>>>>>>>>> behind
>>>>>>>>>>
>>>>>>>>>> being
>>>>>>>>>>
>>>>>>>>>> able
>>>>>>>>>>
>>>>>>>>>> to add multiple splits at the same time is to ease
>>>>>>>>>>
>>>>>>>>>> startup
>>>>>>>>>>
>>>>>>>>>> where
>>>>>>>>>>
>>>>>>>>>> multiple
>>>>>>>>>>
>>>>>>>>>> splits may be assigned instantly.)
>>>>>>>>>>     --> SplitReader has a context object on which it can
>>>>>>>>>>
>>>>>>>>>> call
>>>>>>>>>>
>>>>>>>>>> indicate
>>>>>>>>>>
>>>>>>>>>> when
>>>>>>>>>>
>>>>>>>>>> splits are completed. The enumerator gets that
>>>>>>>>>>
>>>>>>>>>> notification and
>>>>>>>>>>
>>>>>>>>>> can
>>>>>>>>>>
>>>>>>>>>> use
>>>>>>>>>>
>>>>>>>>>> to
>>>>>>>>>>
>>>>>>>>>> decide when to assign new splits. This should help both
>>>>>>>>>>
>>>>>>>>>> in
>>>>>>>>>>
>>>>>>>>>> cases
>>>>>>>>>>
>>>>>>>>>> of
>>>>>>>>>>
>>>>>>>>>> sources
>>>>>>>>>>
>>>>>>>>>> that take splits lazily (file readers) and in case the
>>>>>>>>>>
>>>>>>>>>> source
>>>>>>>>>>
>>>>>>>>>> needs to
>>>>>>>>>>
>>>>>>>>>> preserve a partial order between splits (Kinesis,
>>>>>>>>>>
>>>>>>>>>> Pravega,
>>>>>>>>>>
>>>>>>>>>> Pulsar may
>>>>>>>>>>
>>>>>>>>>> need
>>>>>>>>>>
>>>>>>>>>> that).
>>>>>>>>>>     --> SplitEnumerator gets notification when
>>>>>>>>>>
>>>>>>>>>> SplitReaders
>>>>>>>>>>
>>>>>>>>>> start
>>>>>>>>>>
>>>>>>>>>> and
>>>>>>>>>>
>>>>>>>>>> when
>>>>>>>>>>
>>>>>>>>>> they finish splits. They can decide at that moment to
>>>>>>>>>>
>>>>>>>>>> push
>>>>>>>>>>
>>>>>>>>>> more
>>>>>>>>>>
>>>>>>>>>> splits
>>>>>>>>>>
>>>>>>>>>> to
>>>>>>>>>>
>>>>>>>>>> that reader
>>>>>>>>>>     --> The SplitEnumerator should probably be aware of
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> source
>>>>>>>>>>
>>>>>>>>>> parallelism, to build its initial distribution.
>>>>>>>>>>
>>>>>>>>>> - Open question: Should the source expose something
>>>>>>>>>>
>>>>>>>>>> like
>>>>>>>>>>
>>>>>>>>>> "host
>>>>>>>>>>
>>>>>>>>>> preferences", so that yarn/mesos/k8s can take this into
>>>>>>>>>>
>>>>>>>>>> account
>>>>>>>>>>
>>>>>>>>>> when
>>>>>>>>>>
>>>>>>>>>> selecting a node to start a TM on?
>>>>>>>>>>
>>>>>>>>>> *(5) Watermarks and event time alignment*
>>>>>>>>>>
>>>>>>>>>> - Watermark generation, as well as idleness, needs to
>>>>>>>>>>
>>>>>>>>>> be
>>>>>>>>>>
>>>>>>>>>> per
>>>>>>>>>>
>>>>>>>>>> split
>>>>>>>>>>
>>>>>>>>>> (like
>>>>>>>>>>
>>>>>>>>>> currently in the Kafka Source, per partition)
>>>>>>>>>> - It is desirable to support optional
>>>>>>>>>>
>>>>>>>>>> event-time-alignment,
>>>>>>>>>>
>>>>>>>>>> meaning
>>>>>>>>>>
>>>>>>>>>> that
>>>>>>>>>>
>>>>>>>>>> splits that are ahead are back-pressured or temporarily
>>>>>>>>>>
>>>>>>>>>> unsubscribed
>>>>>>>>>>
>>>>>>>>>> - I think i would be desirable to encapsulate
>>>>>>>>>>
>>>>>>>>>> watermark
>>>>>>>>>>
>>>>>>>>>> generation
>>>>>>>>>>
>>>>>>>>>> logic
>>>>>>>>>>
>>>>>>>>>> in watermark generators, for a separation of concerns.
>>>>>>>>>>
>>>>>>>>>> The
>>>>>>>>>>
>>>>>>>>>> watermark
>>>>>>>>>>
>>>>>>>>>> generators should run per split.
>>>>>>>>>> - Using watermark generators would also help with
>>>>>>>>>>
>>>>>>>>>> another
>>>>>>>>>>
>>>>>>>>>> problem of
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> suggested interface, namely supporting non-periodic
>>>>>>>>>>
>>>>>>>>>> watermarks
>>>>>>>>>>
>>>>>>>>>> efficiently.
>>>>>>>>>>
>>>>>>>>>> - Need a way to "dispatch" next record to different
>>>>>>>>>>
>>>>>>>>>> watermark
>>>>>>>>>>
>>>>>>>>>> generators
>>>>>>>>>>
>>>>>>>>>> - Need a way to tell SplitReader to "suspend" a split
>>>>>>>>>>
>>>>>>>>>> until a
>>>>>>>>>>
>>>>>>>>>> certain
>>>>>>>>>>
>>>>>>>>>> watermark is reached (event time backpressure)
>>>>>>>>>> - This would in fact be not needed (and thus simpler)
>>>>>>>>>>
>>>>>>>>>> if
>>>>>>>>>>
>>>>>>>>>> we
>>>>>>>>>>
>>>>>>>>>> had
>>>>>>>>>>
>>>>>>>>>> a
>>>>>>>>>>
>>>>>>>>>> SplitReader per split and may be a reason to re-open
>>>>>>>>>>
>>>>>>>>>> that
>>>>>>>>>>
>>>>>>>>>> discussion
>>>>>>>>>>
>>>>>>>>>> *(6) Watermarks across splits and in the Split
>>>>>>>>>>
>>>>>>>>>> Enumerator*
>>>>>>>>>>
>>>>>>>>>> - The split enumerator may need some watermark
>>>>>>>>>>
>>>>>>>>>> awareness,
>>>>>>>>>>
>>>>>>>>>> which
>>>>>>>>>>
>>>>>>>>>> should
>>>>>>>>>>
>>>>>>>>>> be
>>>>>>>>>>
>>>>>>>>>> purely based on split metadata (like create timestamp
>>>>>>>>>>
>>>>>>>>>> of
>>>>>>>>>>
>>>>>>>>>> file
>>>>>>>>>>
>>>>>>>>>> splits)
>>>>>>>>>>
>>>>>>>>>> - If there are still more splits with overlapping
>>>>>>>>>>
>>>>>>>>>> event
>>>>>>>>>>
>>>>>>>>>> time
>>>>>>>>>>
>>>>>>>>>> range
>>>>>>>>>>
>>>>>>>>>> for
>>>>>>>>>>
>>>>>>>>>> a
>>>>>>>>>>
>>>>>>>>>> split reader, then that split reader should not advance
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> watermark
>>>>>>>>>>
>>>>>>>>>> within the split beyond the overlap boundary. Otherwise
>>>>>>>>>>
>>>>>>>>>> future
>>>>>>>>>>
>>>>>>>>>> splits
>>>>>>>>>>
>>>>>>>>>> will
>>>>>>>>>>
>>>>>>>>>> produce late data.
>>>>>>>>>>
>>>>>>>>>> - One way to approach this could be that the split
>>>>>>>>>>
>>>>>>>>>> enumerator
>>>>>>>>>>
>>>>>>>>>> may
>>>>>>>>>>
>>>>>>>>>> send
>>>>>>>>>>
>>>>>>>>>> watermarks to the readers, and the readers cannot emit
>>>>>>>>>>
>>>>>>>>>> watermarks
>>>>>>>>>>
>>>>>>>>>> beyond
>>>>>>>>>>
>>>>>>>>>> that received watermark.
>>>>>>>>>> - Many split enumerators would simply immediately send
>>>>>>>>>>
>>>>>>>>>> Long.MAX
>>>>>>>>>>
>>>>>>>>>> out
>>>>>>>>>>
>>>>>>>>>> and
>>>>>>>>>>
>>>>>>>>>> leave the progress purely to the split readers.
>>>>>>>>>>
>>>>>>>>>> - For event-time alignment / split back pressure, this
>>>>>>>>>>
>>>>>>>>>> begs
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> question
>>>>>>>>>>
>>>>>>>>>> how we can avoid deadlocks that may arise when splits
>>>>>>>>>>
>>>>>>>>>> are
>>>>>>>>>>
>>>>>>>>>> suspended
>>>>>>>>>>
>>>>>>>>>> for
>>>>>>>>>>
>>>>>>>>>> event time back pressure,
>>>>>>>>>>
>>>>>>>>>> *(7) Batch and streaming Unification*
>>>>>>>>>>
>>>>>>>>>> - Functionality wise, the above design should support
>>>>>>>>>>
>>>>>>>>>> both
>>>>>>>>>>
>>>>>>>>>> - Batch often (mostly) does not care about reading "in
>>>>>>>>>>
>>>>>>>>>> order"
>>>>>>>>>>
>>>>>>>>>> and
>>>>>>>>>>
>>>>>>>>>> generating watermarks
>>>>>>>>>>     --> Might use different enumerator logic that is
>>>>>>>>>>
>>>>>>>>>> more
>>>>>>>>>>
>>>>>>>>>> locality
>>>>>>>>>>
>>>>>>>>>> aware
>>>>>>>>>>
>>>>>>>>>> and ignores event time order
>>>>>>>>>>     --> Does not generate watermarks
>>>>>>>>>> - Would be great if bounded sources could be
>>>>>>>>>>
>>>>>>>>>> identified
>>>>>>>>>>
>>>>>>>>>> at
>>>>>>>>>>
>>>>>>>>>> compile
>>>>>>>>>>
>>>>>>>>>> time,
>>>>>>>>>>
>>>>>>>>>> so that "env.addBoundedSource(...)" is type safe and
>>>>>>>>>>
>>>>>>>>>> can
>>>>>>>>>>
>>>>>>>>>> return a
>>>>>>>>>>
>>>>>>>>>> "BoundedDataStream".
>>>>>>>>>> - Possible to defer this discussion until later
>>>>>>>>>>
>>>>>>>>>> *Miscellaneous Comments*
>>>>>>>>>>
>>>>>>>>>> - Should the source have a TypeInformation for the
>>>>>>>>>>
>>>>>>>>>> produced
>>>>>>>>>>
>>>>>>>>>> type,
>>>>>>>>>>
>>>>>>>>>> instead
>>>>>>>>>>
>>>>>>>>>> of a serializer? We need a type information in the
>>>>>>>>>>
>>>>>>>>>> stream
>>>>>>>>>>
>>>>>>>>>> anyways, and
>>>>>>>>>>
>>>>>>>>>> can
>>>>>>>>>>
>>>>>>>>>> derive the serializer from that. Plus, creating the
>>>>>>>>>>
>>>>>>>>>> serializer
>>>>>>>>>>
>>>>>>>>>> should
>>>>>>>>>>
>>>>>>>>>> respect the ExecutionConfig.
>>>>>>>>>>
>>>>>>>>>> - The TypeSerializer interface is very powerful but
>>>>>>>>>>
>>>>>>>>>> also
>>>>>>>>>>
>>>>>>>>>> not
>>>>>>>>>>
>>>>>>>>>> easy to
>>>>>>>>>>
>>>>>>>>>> implement. Its purpose is to handle data super
>>>>>>>>>>
>>>>>>>>>> efficiently,
>>>>>>>>>>
>>>>>>>>>> support
>>>>>>>>>>
>>>>>>>>>> flexible ways of evolution, etc.
>>>>>>>>>> For metadata I would suggest to look at the
>>>>>>>>>>
>>>>>>>>>> SimpleVersionedSerializer
>>>>>>>>>>
>>>>>>>>>> instead, which is used for example for checkpoint
>>>>>>>>>>
>>>>>>>>>> master
>>>>>>>>>>
>>>>>>>>>> hooks,
>>>>>>>>>>
>>>>>>>>>> or for
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> streaming file sink. I think that is is a good match
>>>>>>>>>>
>>>>>>>>>> for
>>>>>>>>>>
>>>>>>>>>> cases
>>>>>>>>>>
>>>>>>>>>> where
>>>>>>>>>>
>>>>>>>>>> we
>>>>>>>>>>
>>>>>>>>>> do
>>>>>>>>>>
>>>>>>>>>> not need more than ser/deser (no copy, etc.) and don't
>>>>>>>>>>
>>>>>>>>>> need to
>>>>>>>>>>
>>>>>>>>>> push
>>>>>>>>>>
>>>>>>>>>> versioning out of the serialization paths for best
>>>>>>>>>>
>>>>>>>>>> performance
>>>>>>>>>>
>>>>>>>>>> (as in
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> TypeSerializer)
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
>>>>>>>>>>
>>>>>>>>>> [hidden email]>
>>>>>>>>>>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> Hi Biao,
>>>>>>>>>>
>>>>>>>>>> Thanks for the answer!
>>>>>>>>>>
>>>>>>>>>> So given the multi-threaded readers, now we have as
>>>>>>>>>>
>>>>>>>>>> open
>>>>>>>>>>
>>>>>>>>>> questions:
>>>>>>>>>>
>>>>>>>>>> 1) How do we let the checkpoints pass through our
>>>>>>>>>>
>>>>>>>>>> multi-threaded
>>>>>>>>>>
>>>>>>>>>> reader
>>>>>>>>>>
>>>>>>>>>> operator?
>>>>>>>>>>
>>>>>>>>>> 2) Do we have separate reader and source operators or
>>>>>>>>>>
>>>>>>>>>> not? In
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> strategy
>>>>>>>>>>
>>>>>>>>>> that has a separate source, the source operator has a
>>>>>>>>>>
>>>>>>>>>> parallelism of
>>>>>>>>>>
>>>>>>>>>> 1
>>>>>>>>>>
>>>>>>>>>> and
>>>>>>>>>>
>>>>>>>>>> is responsible for split recovery only.
>>>>>>>>>>
>>>>>>>>>> For the first one, given also the constraints
>>>>>>>>>>
>>>>>>>>>> (blocking,
>>>>>>>>>>
>>>>>>>>>> finite
>>>>>>>>>>
>>>>>>>>>> queues,
>>>>>>>>>>
>>>>>>>>>> etc), I do not have an answer yet.
>>>>>>>>>>
>>>>>>>>>> For the 2nd, I think that we should go with separate
>>>>>>>>>>
>>>>>>>>>> operators
>>>>>>>>>>
>>>>>>>>>> for
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> source and the readers, for the following reasons:
>>>>>>>>>>
>>>>>>>>>> 1) This is more aligned with a potential future
>>>>>>>>>>
>>>>>>>>>> improvement
>>>>>>>>>>
>>>>>>>>>> where the
>>>>>>>>>>
>>>>>>>>>> split
>>>>>>>>>>
>>>>>>>>>> discovery becomes a responsibility of the JobManager
>>>>>>>>>>
>>>>>>>>>> and
>>>>>>>>>>
>>>>>>>>>> readers are
>>>>>>>>>>
>>>>>>>>>> pooling more work from the JM.
>>>>>>>>>>
>>>>>>>>>> 2) The source is going to be the "single point of
>>>>>>>>>>
>>>>>>>>>> truth".
>>>>>>>>>>
>>>>>>>>>> It
>>>>>>>>>>
>>>>>>>>>> will
>>>>>>>>>>
>>>>>>>>>> know
>>>>>>>>>>
>>>>>>>>>> what
>>>>>>>>>>
>>>>>>>>>> has been processed and what not. If the source and the
>>>>>>>>>>
>>>>>>>>>> readers
>>>>>>>>>>
>>>>>>>>>> are a
>>>>>>>>>>
>>>>>>>>>> single
>>>>>>>>>>
>>>>>>>>>> operator with parallelism > 1, or in general, if the
>>>>>>>>>>
>>>>>>>>>> split
>>>>>>>>>>
>>>>>>>>>> discovery
>>>>>>>>>>
>>>>>>>>>> is
>>>>>>>>>>
>>>>>>>>>> done by each task individually, then:
>>>>>>>>>>    i) we have to have a deterministic scheme for each
>>>>>>>>>>
>>>>>>>>>> reader to
>>>>>>>>>>
>>>>>>>>>> assign
>>>>>>>>>>
>>>>>>>>>> splits to itself (e.g. mod subtaskId). This is not
>>>>>>>>>>
>>>>>>>>>> necessarily
>>>>>>>>>>
>>>>>>>>>> trivial
>>>>>>>>>>
>>>>>>>>>> for
>>>>>>>>>>
>>>>>>>>>> all sources.
>>>>>>>>>>    ii) each reader would have to keep a copy of all its
>>>>>>>>>>
>>>>>>>>>> processed
>>>>>>>>>>
>>>>>>>>>> slpits
>>>>>>>>>>
>>>>>>>>>>    iii) the state has to be a union state with a
>>>>>>>>>>
>>>>>>>>>> non-trivial
>>>>>>>>>>
>>>>>>>>>> merging
>>>>>>>>>>
>>>>>>>>>> logic
>>>>>>>>>>
>>>>>>>>>> in order to support rescaling.
>>>>>>>>>>
>>>>>>>>>> Two additional points that you raised above:
>>>>>>>>>>
>>>>>>>>>> i) The point that you raised that we need to keep all
>>>>>>>>>>
>>>>>>>>>> splits
>>>>>>>>>>
>>>>>>>>>> (processed
>>>>>>>>>>
>>>>>>>>>> and
>>>>>>>>>>
>>>>>>>>>> not-processed) I think is a bit of a strong
>>>>>>>>>>
>>>>>>>>>> requirement.
>>>>>>>>>>
>>>>>>>>>> This
>>>>>>>>>>
>>>>>>>>>> would
>>>>>>>>>>
>>>>>>>>>> imply
>>>>>>>>>>
>>>>>>>>>> that for infinite sources the state will grow
>>>>>>>>>>
>>>>>>>>>> indefinitely.
>>>>>>>>>>
>>>>>>>>>> This is
>>>>>>>>>>
>>>>>>>>>> problem
>>>>>>>>>>
>>>>>>>>>> is even more pronounced if we do not have a single
>>>>>>>>>>
>>>>>>>>>> source
>>>>>>>>>>
>>>>>>>>>> that
>>>>>>>>>>
>>>>>>>>>> assigns
>>>>>>>>>>
>>>>>>>>>> splits to readers, as each reader will have its own
>>>>>>>>>>
>>>>>>>>>> copy
>>>>>>>>>>
>>>>>>>>>> of
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> state.
>>>>>>>>>>
>>>>>>>>>> ii) it is true that for finite sources we need to
>>>>>>>>>>
>>>>>>>>>> somehow
>>>>>>>>>>
>>>>>>>>>> not
>>>>>>>>>>
>>>>>>>>>> close
>>>>>>>>>>
>>>>>>>>>> the
>>>>>>>>>>
>>>>>>>>>> readers when the source/split discoverer finishes. The
>>>>>>>>>> ContinuousFileReaderOperator has a work-around for
>>>>>>>>>>
>>>>>>>>>> that.
>>>>>>>>>>
>>>>>>>>>> It is
>>>>>>>>>>
>>>>>>>>>> not
>>>>>>>>>>
>>>>>>>>>> elegant,
>>>>>>>>>>
>>>>>>>>>> and checkpoints are not emitted after closing the
>>>>>>>>>>
>>>>>>>>>> source,
>>>>>>>>>>
>>>>>>>>>> but
>>>>>>>>>>
>>>>>>>>>> this, I
>>>>>>>>>>
>>>>>>>>>> believe, is a bigger problem which requires more
>>>>>>>>>>
>>>>>>>>>> changes
>>>>>>>>>>
>>>>>>>>>> than
>>>>>>>>>>
>>>>>>>>>> just
>>>>>>>>>>
>>>>>>>>>> refactoring the source interface.
>>>>>>>>>>
>>>>>>>>>> Cheers,
>>>>>>>>>> Kostas
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> --
>>>>>>>>>> Best, Jingsong Lee
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>>
>>>>>> --
>>>>>> Best, Jingsong Lee
>>>>>>
>>>>>
>>>>
>>>>
>>>
>>
>

[Becket Qin]

Hi Timo,

Bounded is just a special case of unbounded and every bounded source can
> also be treated as an unbounded source. This would unify the API if
> people don't need a bounded operation.


With option 3 users can still get a unified API with something like below:

DataStream boundedStream = env.boundedSource(boundedSource);
DataStream unboundedStream = env.source(unboundedSource);

So in both cases, users can still use a unified DataStream without touching
the bounded stream only methods.
By "unify the API if people don't need the bounded operation". Do you
expect a DataStream with a Bounded source to have the batch operators and
scheduler settings as well?


If we allow DataStream from BOUNDED source, we will essentially pick "*modified
option 2*".

// The source is either bounded or unbounded, but only unbounded operations
> could be performed on the returned DataStream.
> DataStream<Type> dataStream = env.source(someSource);


> // The source must be a bounded source, otherwise exception is thrown.
> BoundedDataStream<Type> boundedDataStream =
> env.boundedSource(boundedSource);



// Add the following method to DataStream

Boundedness DataStream#getBoundedness();


From pure logical perspective, Boundedness and runtime settings
(Stream/Batch) are two orthogonal dimensions. And are specified in the
following way.

*Boundedness* - defined by the source: BOUNDED / UNBOUNDED.
*Running mode* - defined by the API class: DataStream (Streaming mode) /
BoundedDataStream (batch mode).

Excluding the UNBOUNDED-batch combination, the "*modified option 2"* covers
the rest three combination. Compared with "*modified option 2*", the main
benefit of option 3 is its simplicity and clearness, by tying boundedness
to running mode and giving up BOUNDED-streaming combination.

Just to be clear, I am fine with either option. But I would like to
understand a bit more about the bounded-streaming use case and when users
would prefer this over bounded-batch case, and whether the added value
justifies the additional complexity in the API. Two cases I can think of
are:
1. The records in DataStream will be processed in order, while
BoundedDataStream processes records without order guarantee.
2. DataStream emits intermediate results when processing a finite dataset,
while BoundedDataStream only emit the final result. In any case, it could
be supported by an UNBOUNDED source stopping at some point.

Case 1 is actually misleading because DataStream in general doesn't really
support in-order process.
Case 2 seems a rare use case because the instantaneous intermediate result
seems difficult to reason about. In any case, this can be supported by an
UNBOUNDED source that stops at some point.

Is there other use cases for bounded-streaming combination I missed? I am a
little hesitating to put the testing requirement here because ideally I'd
avoid having public APIs for testing purpose only. And this could be
resolved by having a UNBOUNDED source stopping at some point as well.

Sorry for the long discussion, but I would really like to make an API
decision after knowing all the pros and cons.

Thanks,

Jiangjie (Becket) Qin







On Thu, Dec 19, 2019 at 6:19 PM Timo Walther <[hidden email]> wrote:

> Hi Becket,
>
> regarding *Option 3* I think we can relax the constraints for env.source():
>
> // MySource can be bounded or unbounded
> DataStream<Type> dataStream = env.source(mySource);
>
> // MySource must be bounded, otherwise throws exception.
> BoundedDataStream<Type> boundedDataStream = env.boundedSource(mySource);
>
> Bounded is just a special case of unbounded and every bounded source can
> also be treated as an unbounded source. This would unify the API if
> people don't need a bounded operation. It also addresses Jark's concerns.
>
> Regards,
> Timo
>
>
> On 18.12.19 14:16, Becket Qin wrote:
> > Hi Jark,
> >
> > Please see the reply below:
> >
> > Regarding to option#3, my concern is that if we don't support streaming
> >> mode for bounded source,
> >> how could we create a testing source for streaming mode? Currently, all
> the
> >> testing source for streaming
> >> are bounded, so that the integration test will finish finally.
> >
> >
> > An UNBOUNDED source does not mean it will never stops. It simply
> indicates
> > that the source *may* run forever, so the runtime needs to be prepared
> for
> > that, but the task may still stop at some point when it hits some
> > source-specific condition. So an UNBOUNDED testing source can still stop
> at
> > some point if needed.
> >
> > Regarding to Source#getRecordOrder(), could we have a implicit contract
> >> that unbounded source should
> >> already read in order (i.e. reading partitions in parallel), for bounded
> >> source the order is not mandatory.
> >
> >
> >
> >> This is also the behaviors of the current sources.
> >
> > 1) a source can't guarantee it reads in strict order, because the
> producer
> >> may produce data not in order.
> >> 2) *Bounded-StrictOrder* is not necessary, because batch can reorder
> data.
> >
> >
> > It is true that sometimes the source cannot guarantee the record order,
> but
> > sometimes it can. Right now, even for stream processing, there is no
> > processing order guarantee. For example, a join operator may emit a later
> > record which successfully found a join match earlier.
> > Event order is one of the most important requirements for event
> processing,
> > a clear order guarantee would be necessary. That said, I agree that right
> > now even if the sources provide the record order requirement, the runtime
> > is not able to guarantee that out of the box. So I am OK if we add the
> > record order to the Source later. But we should avoid misleading users to
> > make them think the processing order is guaranteed when using the
> unbounded
> > runtime.
> >
> > Thanks,
> >
> > Jiangjie (Becket) Qin
> >
> > On Wed, Dec 18, 2019 at 10:29 AM Jark Wu <[hidden email]> wrote:
> >
> >> Hi Becket,
> >>
> >> That's great we have reached a consensus on Source#getBoundedness().
> >>
> >> Regarding to option#3, my concern is that if we don't support streaming
> >> mode for bounded source,
> >> how could we create a testing source for streaming mode? Currently, all
> the
> >> testing source for streaming
> >> are bounded, so that the integration test will finish finally.
> >>
> >> Regarding to Source#getRecordOrder(), could we have a implicit contract
> >> that unbounded source should
> >> already read in order (i.e. reading partitions in parallel), for bounded
> >> source the order is not mandatory.
> >> This is also the behaviors of the current sources.
> >> 1) a source can't guarantee it reads in strict order, because the
> producer
> >> may produce data not in order.
> >> 2) *Bounded-StrictOrder* is not necessary, because batch can reorder
> data.
> >>
> >> Best,
> >> Jark
> >>
> >>
> >>
> >> On Tue, 17 Dec 2019 at 22:03, Becket Qin <[hidden email]> wrote:
> >>
> >>> Hi folks,
> >>>
> >>> Thanks for the comments. I am convinced that the Source API should not
> >> take
> >>> boundedness as a parameter after it is constructed. What Timo and Dawid
> >>> suggested sounds a reasonable solution to me. So the Source API would
> >>> become:
> >>>
> >>> Source {
> >>>      Boundedness getBoundedness();
> >>> }
> >>>
> >>> Assuming the above Source API, in addition to the two options mentioned
> >> in
> >>> earlier emails, I am thinking of another option:
> >>>
> >>> *Option 3:*
> >>> // MySource must be unbounded, otherwise throws exception.
> >>> DataStream<Type> dataStream = env.source(mySource);
> >>>
> >>> // MySource must be bounded, otherwise throws exception.
> >>> BoundedDataStream<Type> boundedDataStream =
> env.boundedSource(mySource);
> >>>
> >>> The pros of this API are:
> >>>     a) It fits the requirements from Table / SQL well.
> >>>     b) DataStream users still have type safety (option 2 only has
> partial
> >>> type safety).
> >>>     c) Cristal clear boundedness from the API which makes DataStream
> join
> >> /
> >>> connect easy to reason about.
> >>> The caveats I see,
> >>>     a) It is inconsistent with Table since Table has one unified
> >> interface.
> >>>     b) No streaming mode for bounded source.
> >>>
> >>> @Stephan Ewen <[hidden email]> @Aljoscha Krettek
> >>> <[hidden email]> what do you think of the approach?
> >>>
> >>>
> >>> Orthogonal to the above API, I am wondering whether boundedness is the
> >> only
> >>> dimension needed to describe the characteristic of the Source behavior.
> >> We
> >>> may also need to have another dimension of *record order*.
> >>>
> >>> For example, when a file source is reading from a directory with
> bounded
> >>> records, it may have two ways to read.
> >>> 1. Read files in parallel.
> >>> 2. Read files in the chronological order.
> >>> In both cases, the file source is a Bounded Source. However, the
> >> processing
> >>> requirement for downstream may be different. In the first case, the
> >>> record processing and result emitting order does not matter, e.g. word
> >>> count. In the second case, the records may have to be processed in the
> >>> order they were read, e.g. change log processing.
> >>>
> >>> If the Source only has a getBoundedness() method, the downstream
> >> processors
> >>> would not know whether the records emitted from the Source should be
> >>> processed in order or not. So combining the boundedness and record
> order,
> >>> we will have four scenarios:
> >>>
> >>> *Bounded-StrictOrder*:     A segment of change log.
> >>> *Bounded-Random*:          Batch Word Count.
> >>> *Unbounded-StrictOrder*: An infinite change log.
> >>> *Unbounded-Random*:     Streaming Word Count.
> >>>
> >>> Option 2 mentioned in the previous email was kind of trying to handle
> the
> >>> Bounded-StrictOrder case by creating a DataStream from a bounded
> source,
> >>> which actually does not work.
> >>> It looks that we do not have strict order support in some operators at
> >> this
> >>> point, e.g. join. But we may still want to add the semantic to the
> Source
> >>> first so later on we don't need to change all the source
> implementations,
> >>> especially given that many of them will be implemented by 3rd party.
> >>>
> >>> Given that, we need another dimension of *Record Order* in the Source.
> >> More
> >>> specifically, the API would become:
> >>>
> >>> Source {
> >>>      Boundedness getBoundedness();
> >>>      RecordOrder getRecordOrder();
> >>> }
> >>>
> >>> public enum RecordOrder {
> >>>      /** The record in the DataStream must be processed in its strict
> >> order
> >>> for correctness. */
> >>>      STRICT,
> >>>      /** The record in the DataStream can be processed in arbitrary
> order.
> >>> */
> >>>      RANDOM;
> >>> }
> >>>
> >>> Any thoughts?
> >>>
> >>> Thanks,
> >>>
> >>> Jiangjie (Becket) Qin
> >>>
> >>> On Tue, Dec 17, 2019 at 3:44 PM Timo Walther <[hidden email]>
> wrote:
> >>>
> >>>> Hi Becket,
> >>>>
> >>>> I completely agree with Dawid's suggestion. The information about the
> >>>> boundedness should come out of the source. Because most of the
> >> streaming
> >>>> sources can be made bounded based on some connector specific
> criterion.
> >>>> In Kafka, it would be an end offset or end timestamp but in any case
> >>>> having just a env.boundedSource() is not enough because parameters for
> >>>> making the source bounded are missing.
> >>>>
> >>>> I suggest to have a simple `isBounded(): Boolean` flag in every source
> >>>> that might be influenced by a connector builder as Dawid mentioned.
> >>>>
> >>>> For type safety during programming, we can still go with *Final state
> >>>> 1*. By having a env.source() vs env.boundedSource(). The latter would
> >>>> just enforce that the boolean flag is set to `true` and could make
> >>>> bounded operations available (if we need that actually).
> >>>>
> >>>> However, I don't think that we should start making a unified Table API
> >>>> ununified again. Boundedness is an optimization property. Every
> bounded
> >>>> operation can also executed in an unbounded way using
> >> updates/retraction
> >>>> or watermarks.
> >>>>
> >>>> Regards,
> >>>> Timo
> >>>>
> >>>>
> >>>> On 15.12.19 14:22, Becket Qin wrote:
> >>>>> Hi Dawid and Jark,
> >>>>>
> >>>>> I think the discussion ultimately boils down to the question that
> >> which
> >>>> one
> >>>>> of the following two final states do we want? Once we make this
> >>> decision,
> >>>>> everything else can be naturally derived.
> >>>>>
> >>>>> *Final state 1*: Separate API for bounded / unbounded DataStream &
> >>> Table.
> >>>>> That means any code users write will be valid at the point when they
> >>>> write
> >>>>> the code. This is similar to having type safety check at programming
> >>>> time.
> >>>>> For example,
> >>>>>
> >>>>> BoundedDataStream extends DataStream {
> >>>>> // Operations only available for bounded data.
> >>>>> BoundedDataStream sort(...);
> >>>>>
> >>>>> // Interaction with another BoundedStream returns a Bounded stream.
> >>>>> BoundedJoinedDataStream join(BoundedDataStream other)
> >>>>>
> >>>>> // Interaction with another unbounded stream returns an unbounded
> >>> stream.
> >>>>> JoinedDataStream join(DataStream other)
> >>>>> }
> >>>>>
> >>>>> BoundedTable extends Table {
> >>>>>     // Bounded only operation.
> >>>>> BoundedTable sort(...);
> >>>>>
> >>>>> // Interaction with another BoundedTable returns a BoundedTable.
> >>>>> BoundedTable join(BoundedTable other)
> >>>>>
> >>>>> // Interaction with another unbounded table returns an unbounded
> >> table.
> >>>>> Table join(Table other)
> >>>>> }
> >>>>>
> >>>>> *Final state 2*: One unified API for bounded / unbounded DataStream /
> >>>>> Table.
> >>>>> That unified API may throw exception at DAG compilation time if an
> >>>> invalid
> >>>>> operation is tried. This is what Table API currently follows.
> >>>>>
> >>>>> DataStream {
> >>>>> // Throws exception if the DataStream is unbounded.
> >>>>> DataStream sort();
> >>>>> // Get boundedness.
> >>>>> Boundedness getBoundedness();
> >>>>> }
> >>>>>
> >>>>> Table {
> >>>>> // Throws exception if the table has infinite rows.
> >>>>> Table orderBy();
> >>>>>
> >>>>> // Get boundedness.
> >>>>> Boundedness getBoundedness();
> >>>>> }
> >>>>>
> >>>>> >From what I understand, there is no consensus so far on this
> decision
> >>>> yet.
> >>>>> Whichever final state we choose, we need to make it consistent across
> >>> the
> >>>>> entire project. We should avoid the case that Table follows one final
> >>>> state
> >>>>> while DataStream follows another. Some arguments I am aware of from
> >>> both
> >>>>> sides so far are following:
> >>>>>
> >>>>> Arguments for final state 1:
> >>>>> 1a) Clean API with method safety check at programming time.
> >>>>> 1b) (Counter 2b) Although SQL does not have programming time error
> >>>> check, SQL
> >>>>> is not really a "programming language" per se. So SQL can be
> >> different
> >>>> from
> >>>>> Table and DataStream.
> >>>>> 1c)  Although final state 2 seems making it easier for SQL to use
> >> given
> >>>> it
> >>>>> is more "config based" than "parameter based", final state 1 can
> >>> probably
> >>>>> also meet what SQL wants by wrapping the Source in TableSource /
> >>>>> TableSourceFactory API if needed.
> >>>>>
> >>>>> Arguments for final state 2:
> >>>>> 2a) The Source API itself seems already sort of following the unified
> >>> API
> >>>>> pattern.
> >>>>> 2b) There is no "programming time" method error check in SQL case, so
> >>> we
> >>>>> cannot really achieve final state 1 across the board.
> >>>>> 2c) It is an easier path given our current status, i.e. Table is
> >>> already
> >>>>> following final state 2.
> >>>>> 2d) Users can always explicitly check the boundedness if they want
> >> to.
> >>>>>
> >>>>> As I mentioned earlier, my initial thought was also to have a
> >>>>> "configuration based" Source rather than a "parameter based" Source.
> >> So
> >>>> it
> >>>>> is completely possible that I missed some important consideration or
> >>>> design
> >>>>> principles that we want to enforce for the project. It would be good
> >>>>> if @Stephan
> >>>>> Ewen <[hidden email]> and @Aljoscha Krettek <
> >>>> [hidden email]> can
> >>>>> also provide more thoughts on this.
> >>>>>
> >>>>>
> >>>>> Re: Jingsong
> >>>>>
> >>>>> As you said, there are some batched system source, like parquet/orc
> >>>> source.
> >>>>>> Could we have the batch emit interface to improve performance? The
> >>>> queue of
> >>>>>> per record may cause performance degradation.
> >>>>>
> >>>>>
> >>>>> The current interface does not necessarily cause performance problem
> >>> in a
> >>>>> multi-threading case. In fact, the base implementation allows
> >>>> SplitReaders
> >>>>> to add a batch <E> of records<T> to the records queue<E>, so each
> >>> element
> >>>>> in the records queue would be a batch <E>. In this case, when the
> >> main
> >>>>> thread polls records, it will take a batch <E> of records <T> from
> >> the
> >>>>> shared records queue and process the records <T> in a batch manner.
> >>>>>
> >>>>> Thanks,
> >>>>>
> >>>>> Jiangjie (Becket) Qin
> >>>>>
> >>>>> On Thu, Dec 12, 2019 at 1:29 PM Jingsong Li <[hidden email]>
> >>>> wrote:
> >>>>>
> >>>>>> Hi Becket,
> >>>>>>
> >>>>>> I also have some performance concerns too.
> >>>>>>
> >>>>>> If I understand correctly, SourceOutput will emit data per record
> >> into
> >>>> the
> >>>>>> queue? I'm worried about the multithreading performance of this
> >> queue.
> >>>>>>
> >>>>>>> One example is some batched messaging systems which only have an
> >>> offset
> >>>>>> for the entire batch instead of individual messages in the batch.
> >>>>>>
> >>>>>> As you said, there are some batched system source, like parquet/orc
> >>>> source.
> >>>>>> Could we have the batch emit interface to improve performance? The
> >>>> queue of
> >>>>>> per record may cause performance degradation.
> >>>>>>
> >>>>>> Best,
> >>>>>> Jingsong Lee
> >>>>>>
> >>>>>> On Thu, Dec 12, 2019 at 9:15 AM Jark Wu <[hidden email]> wrote:
> >>>>>>
> >>>>>>> Hi Becket,
> >>>>>>>
> >>>>>>> I think Dawid explained things clearly and makes a lot of sense.
> >>>>>>> I'm also in favor of #2, because #1 doesn't work for our future
> >>> unified
> >>>>>>> envrionment.
> >>>>>>>
> >>>>>>> You can see the vision in this documentation [1]. In the future, we
> >>>> would
> >>>>>>> like to
> >>>>>>> drop the global streaming/batch mode in SQL (i.e.
> >>>>>>> EnvironmentSettings#inStreamingMode/inBatchMode).
> >>>>>>> A source is bounded or unbounded once defined, so queries can be
> >>>> inferred
> >>>>>>> from source to run
> >>>>>>> in streaming or batch or hybrid mode. However, in #1, we will lose
> >>> this
> >>>>>>> ability because the framework
> >>>>>>> doesn't know whether the source is bounded or unbounded.
> >>>>>>>
> >>>>>>> Best,
> >>>>>>> Jark
> >>>>>>>
> >>>>>>>
> >>>>>>> [1]:
> >>>>>>>
> >>>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://docs.google.com/document/d/1yrKXEIRATfxHJJ0K3t6wUgXAtZq8D-XgvEnvl2uUcr0/edit#heading=h.v4ib17buma1p
> >>>>>>>
> >>>>>>> On Wed, 11 Dec 2019 at 20:52, Piotr Nowojski <[hidden email]>
> >>>>>> wrote:
> >>>>>>>
> >>>>>>>> Hi,
> >>>>>>>>
> >>>>>>>> Regarding the:
> >>>>>>>>
> >>>>>>>> Collection<E> getNextRecords()
> >>>>>>>>
> >>>>>>>> I’m pretty sure such design would unfortunately impact the
> >>> performance
> >>>>>>>> (accessing and potentially creating the collection on the hot
> >> path).
> >>>>>>>>
> >>>>>>>> Also the
> >>>>>>>>
> >>>>>>>> InputStatus emitNext(DataOutput<T> output) throws Exception;
> >>>>>>>> or
> >>>>>>>> Status pollNext(SourceOutput<T> sourceOutput) throws Exception;
> >>>>>>>>
> >>>>>>>> Gives us some opportunities in the future, to allow Source hot
> >>> looping
> >>>>>>>> inside, until it receives some signal “please exit because of some
> >>>>>>> reasons”
> >>>>>>>> (output collector could return such hint upon collecting the
> >>> result).
> >>>>>> But
> >>>>>>>> that’s another topic outside of this FLIP’s scope.
> >>>>>>>>
> >>>>>>>> Piotrek
> >>>>>>>>
> >>>>>>>>> On 11 Dec 2019, at 10:41, Till Rohrmann <[hidden email]>
> >>>>>> wrote:
> >>>>>>>>>
> >>>>>>>>> Hi Becket,
> >>>>>>>>>
> >>>>>>>>> quick clarification from my side because I think you
> >> misunderstood
> >>> my
> >>>>>>>>> question. I did not suggest to let the SourceReader return only a
> >>>>>>> single
> >>>>>>>>> record at a time when calling getNextRecords. As the return type
> >>>>>>>> indicates,
> >>>>>>>>> the method can return an arbitrary number of records.
> >>>>>>>>>
> >>>>>>>>> Cheers,
> >>>>>>>>> Till
> >>>>>>>>>
> >>>>>>>>> On Wed, Dec 11, 2019 at 10:13 AM Dawid Wysakowicz <
> >>>>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>>>> wrote:
> >>>>>>>>>
> >>>>>>>>>> Hi Becket,
> >>>>>>>>>>
> >>>>>>>>>> Issue #1 - Design of Source interface
> >>>>>>>>>>
> >>>>>>>>>> I mentioned the lack of a method like
> >>>>>>>> Source#createEnumerator(Boundedness
> >>>>>>>>>> boundedness, SplitEnumeratorContext context), because without
> >> the
> >>>>>>>> current
> >>>>>>>>>> proposal is not complete/does not work.
> >>>>>>>>>>
> >>>>>>>>>> If we say that boundedness is an intrinsic property of a source
> >>> imo
> >>>>>> we
> >>>>>>>>>> don't need the Source#createEnumerator(Boundedness boundedness,
> >>>>>>>>>> SplitEnumeratorContext context) method.
> >>>>>>>>>>
> >>>>>>>>>> Assuming a source from my previous example:
> >>>>>>>>>>
> >>>>>>>>>> Source source = KafkaSource.builder()
> >>>>>>>>>>    ...
> >>>>>>>>>>    .untilTimestamp(...)
> >>>>>>>>>>    .build()
> >>>>>>>>>>
> >>>>>>>>>> Would the enumerator differ if created like
> >>>>>>>>>> source.createEnumerator(CONTINUOUS_UNBOUNDED, ...) vs source
> >>>>>>>>>> .createEnumerator(BOUNDED, ...)? I know I am repeating myself,
> >> but
> >>>>>>> this
> >>>>>>>> is
> >>>>>>>>>> the part that my opinion differ the most from the current
> >>> proposal.
> >>>>>> I
> >>>>>>>>>> really think it should always be the source that tells if it is
> >>>>>>> bounded
> >>>>>>>> or
> >>>>>>>>>> not. In the current proposal methods
> >> continousSource/boundedSource
> >>>>>>>> somewhat
> >>>>>>>>>> reconfigure the source, which I think is misleading.
> >>>>>>>>>>
> >>>>>>>>>> I think a call like:
> >>>>>>>>>>
> >>>>>>>>>> Source source = KafkaSource.builder()
> >>>>>>>>>>    ...
> >>>>>>>>>>    .readContinously() / readUntilLatestOffset() /
> >>> readUntilTimestamp
> >>>> /
> >>>>>>>> readUntilOffsets / ...
> >>>>>>>>>>    .build()
> >>>>>>>>>>
> >>>>>>>>>> is way cleaner (and expressive) than
> >>>>>>>>>>
> >>>>>>>>>> Source source = KafkaSource.builder()
> >>>>>>>>>>    ...
> >>>>>>>>>>    .build()
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> env.continousSource(source) // which actually underneath would
> >>> call
> >>>>>>>> createEnumerator(CONTINUOUS, ctx) which would be equivalent to
> >>>>>>>> source.readContinously().createEnumerator(ctx)
> >>>>>>>>>> // or
> >>>>>>>>>> env.boundedSource(source) // which actually underneath would
> >> call
> >>>>>>>> createEnumerator(BOUNDED, ctx) which would be equivalent to
> >>>>>>>> source.readUntilLatestOffset().createEnumerator(ctx)
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> Sorry for the comparison, but to me it seems there is too much
> >>> magic
> >>>>>>>>>> happening underneath those two calls.
> >>>>>>>>>>
> >>>>>>>>>> I really believe the Source interface should have getBoundedness
> >>>>>>> method
> >>>>>>>>>> instead of (supportBoundedness) + createEnumerator(Boundedness,
> >>> ...)
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> Issue #2 - Design of
> >>>>>>>>>> ExecutionEnvironment#source()/continuousSource()/boundedSource()
> >>>>>>>>>>
> >>>>>>>>>> As you might have guessed I am slightly in favor of option #2
> >>>>>>> modified.
> >>>>>>>>>> Yes I am aware every step of the dag would have to be able to
> >> say
> >>> if
> >>>>>>> it
> >>>>>>>> is
> >>>>>>>>>> bounded or not. I have a feeling it would be easier to express
> >>> cross
> >>>>>>>>>> bounded/unbounded operations, but I must admit I have not
> >> thought
> >>> it
> >>>>>>>>>> through thoroughly, In the spirit of batch is just a special
> >> case
> >>> of
> >>>>>>>>>> streaming I thought BoundedStream would extend from DataStream.
> >>>>>>> Correct
> >>>>>>>> me
> >>>>>>>>>> if I am wrong. In such a setup the cross bounded/unbounded
> >>> operation
> >>>>>>>> could
> >>>>>>>>>> be expressed quite easily I think:
> >>>>>>>>>>
> >>>>>>>>>> DataStream {
> >>>>>>>>>>    DataStream join(DataStream, ...); // we could not really tell
> >> if
> >>>>>> the
> >>>>>>>> result is bounded or not, but because bounded stream is a special
> >>> case
> >>>>>> of
> >>>>>>>> unbounded the API object is correct, irrespective if the left or
> >>> right
> >>>>>>> side
> >>>>>>>> of the join is bounded
> >>>>>>>>>> }
> >>>>>>>>>>
> >>>>>>>>>> BoundedStream extends DataStream {
> >>>>>>>>>>    BoundedStream join(BoundedStream, ...); // only if both sides
> >>> are
> >>>>>>>> bounded the result can be bounded as well. However we do have
> >> access
> >>>> to
> >>>>>>> the
> >>>>>>>> DataStream#join here, so you can still join with a DataStream
> >>>>>>>>>> }
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> On the other hand I also see benefits of two completely
> >> disjointed
> >>>>>>> APIs,
> >>>>>>>>>> as we could prohibit some streaming calls in the bounded API. I
> >>>>>> can't
> >>>>>>>> think
> >>>>>>>>>> of any unbounded operators that could not be implemented for
> >>> bounded
> >>>>>>>> stream.
> >>>>>>>>>>
> >>>>>>>>>> Besides I think we both agree we don't like the method:
> >>>>>>>>>>
> >>>>>>>>>> DataStream boundedStream(Source)
> >>>>>>>>>>
> >>>>>>>>>> suggested in the current state of the FLIP. Do we ? :)
> >>>>>>>>>>
> >>>>>>>>>> Best,
> >>>>>>>>>>
> >>>>>>>>>> Dawid
> >>>>>>>>>>
> >>>>>>>>>> On 10/12/2019 18:57, Becket Qin wrote:
> >>>>>>>>>>
> >>>>>>>>>> Hi folks,
> >>>>>>>>>>
> >>>>>>>>>> Thanks for the discussion, great feedback. Also thanks Dawid for
> >>> the
> >>>>>>>>>> explanation, it is much clearer now.
> >>>>>>>>>>
> >>>>>>>>>> One thing that is indeed missing from the FLIP is how the
> >>>>>> boundedness
> >>>>>>> is
> >>>>>>>>>> passed to the Source implementation. So the API should be
> >>>>>>>>>> Source#createEnumerator(Boundedness boundedness,
> >>>>>>> SplitEnumeratorContext
> >>>>>>>>>> context)
> >>>>>>>>>> And we can probably remove the
> >>> Source#supportBoundedness(Boundedness
> >>>>>>>>>> boundedness) method.
> >>>>>>>>>>
> >>>>>>>>>> Assuming we have that, we are essentially choosing from one of
> >> the
> >>>>>>>>>> following two options:
> >>>>>>>>>>
> >>>>>>>>>> Option 1:
> >>>>>>>>>> // The source is continuous source, and only unbounded
> >> operations
> >>>>>> can
> >>>>>>> be
> >>>>>>>>>> performed.
> >>>>>>>>>> DataStream<Type> datastream = env.continuousSource(someSource);
> >>>>>>>>>>
> >>>>>>>>>> // The source is bounded source, both bounded and unbounded
> >>>>>> operations
> >>>>>>>> can
> >>>>>>>>>> be performed.
> >>>>>>>>>> BoundedDataStream<Type> boundedDataStream =
> >>>>>>>> env.boundedSource(someSource);
> >>>>>>>>>>
> >>>>>>>>>>    - Pros:
> >>>>>>>>>>         a) explicit boundary between bounded / unbounded
> streams,
> >>> it
> >>>>>> is
> >>>>>>>>>> quite simple and clear to the users.
> >>>>>>>>>>    - Cons:
> >>>>>>>>>>         a) For applications that do not involve bounded
> >> operations,
> >>>>>> they
> >>>>>>>>>> still have to call different API to distinguish bounded /
> >>> unbounded
> >>>>>>>> streams.
> >>>>>>>>>>         b) No support for bounded stream to run in a streaming
> >>>> runtime
> >>>>>>>>>> setting, i.e. scheduling and operators behaviors.
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> Option 2:
> >>>>>>>>>> // The source is either bounded or unbounded, but only unbounded
> >>>>>>>> operations
> >>>>>>>>>> could be performed on the returned DataStream.
> >>>>>>>>>> DataStream<Type> dataStream = env.source(someSource);
> >>>>>>>>>>
> >>>>>>>>>> // The source must be a bounded source, otherwise exception is
> >>>>>> thrown.
> >>>>>>>>>> BoundedDataStream<Type> boundedDataStream =
> >>>>>>>>>> env.boundedSource(boundedSource);
> >>>>>>>>>>
> >>>>>>>>>> The pros and cons are exactly the opposite of option 1.
> >>>>>>>>>>    - Pros:
> >>>>>>>>>>         a) For applications that do not involve bounded
> >> operations,
> >>>>>> they
> >>>>>>>>>> still have to call different API to distinguish bounded /
> >>> unbounded
> >>>>>>>> streams.
> >>>>>>>>>>         b) Support for bounded stream to run in a streaming
> >> runtime
> >>>>>>>> setting,
> >>>>>>>>>> i.e. scheduling and operators behaviors.
> >>>>>>>>>>    - Cons:
> >>>>>>>>>>         a) Bounded / unbounded streams are kind of mixed, i.e.
> >>> given
> >>>> a
> >>>>>>>>>> DataStream, it is not clear whether it is bounded or not, unless
> >>> you
> >>>>>>>> have
> >>>>>>>>>> the access to its source.
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> If we only think from the Source API perspective, option 2
> >> seems a
> >>>>>>>> better
> >>>>>>>>>> choice because functionality wise it is a superset of option 1,
> >> at
> >>>>>> the
> >>>>>>>> cost
> >>>>>>>>>> of some seemingly acceptable ambiguity in the DataStream API.
> >>>>>>>>>> But if we look at the DataStream API as a whole, option 1 seems
> >> a
> >>>>>>>> clearer
> >>>>>>>>>> choice. For example, some times a library may have to know
> >>> whether a
> >>>>>>>>>> certain task will finish or not. And it would be difficult to
> >> tell
> >>>>>> if
> >>>>>>>> the
> >>>>>>>>>> input is a DataStream, unless additional information is provided
> >>> all
> >>>>>>> the
> >>>>>>>>>> way from the Source. One possible solution is to have a
> >> *modified
> >>>>>>>> option 2*
> >>>>>>>>>> which adds a method to the DataStream API to indicate
> >> boundedness,
> >>>>>>> such
> >>>>>>>> as
> >>>>>>>>>> getBoundedness(). It would solve the problem with a potential
> >>>>>>> confusion
> >>>>>>>> of
> >>>>>>>>>> what is difference between a DataStream with
> >> getBoundedness()=true
> >>>>>>> and a
> >>>>>>>>>> BoundedDataStream. But that seems not super difficult to
> >> explain.
> >>>>>>>>>>
> >>>>>>>>>> So from API's perspective, I don't have a strong opinion between
> >>>>>>>> *option 1*
> >>>>>>>>>> and *modified option 2. *I like the cleanness of option 1, but
> >>>>>>> modified
> >>>>>>>>>> option 2 would be more attractive if we have concrete use case
> >> for
> >>>>>> the
> >>>>>>>>>> "Bounded stream with unbounded streaming runtime settings".
> >>>>>>>>>>
> >>>>>>>>>> Re: Till
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> Maybe this has already been asked before but I was wondering why
> >>> the
> >>>>>>>>>> SourceReader interface has the method pollNext which hands the
> >>>>>>>>>> responsibility of outputting elements to the SourceReader
> >>>>>>>> implementation?
> >>>>>>>>>> Has this been done for backwards compatibility reasons with the
> >>> old
> >>>>>>>> source
> >>>>>>>>>> interface? If not, then one could define a Collection<E>
> >>>>>>>> getNextRecords()
> >>>>>>>>>> method which returns the currently retrieved records and then
> >> the
> >>>>>>> caller
> >>>>>>>>>> emits them outside of the SourceReader. That way the interface
> >>> would
> >>>>>>> not
> >>>>>>>>>> allow to implement an outputting loop where we never hand back
> >>>>>> control
> >>>>>>>> to
> >>>>>>>>>> the caller. At the moment, this contract can be easily broken
> >> and
> >>> is
> >>>>>>>> only
> >>>>>>>>>> mentioned loosely in the JavaDocs.
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> The primary reason we handover the SourceOutput to the
> >>> SourceReader
> >>>>>> is
> >>>>>>>>>> because sometimes it is difficult for a SourceReader to emit one
> >>>>>>> record
> >>>>>>>> at
> >>>>>>>>>> a time. One example is some batched messaging systems which only
> >>>>>> have
> >>>>>>> an
> >>>>>>>>>> offset for the entire batch instead of individual messages in
> >> the
> >>>>>>>> batch. In
> >>>>>>>>>> that case, returning one record at a time would leave the
> >>>>>> SourceReader
> >>>>>>>> in
> >>>>>>>>>> an uncheckpointable state because they can only checkpoint at
> >> the
> >>>>>>> batch
> >>>>>>>>>> boundaries.
> >>>>>>>>>>
> >>>>>>>>>> Thanks,
> >>>>>>>>>>
> >>>>>>>>>> Jiangjie (Becket) Qin
> >>>>>>>>>>
> >>>>>>>>>> On Tue, Dec 10, 2019 at 5:33 PM Till Rohrmann <
> >>> [hidden email]
> >>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> >>>>>>>> [hidden email]>> wrote:
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> Hi everyone,
> >>>>>>>>>>
> >>>>>>>>>> thanks for drafting this FLIP. It reads very well.
> >>>>>>>>>>
> >>>>>>>>>> Concerning Dawid's proposal, I tend to agree. The boundedness
> >>> could
> >>>>>>> come
> >>>>>>>>>> from the source and tell the system how to treat the operator
> >>>>>>>> (scheduling
> >>>>>>>>>> wise). From a user's perspective it should be fine to get back a
> >>>>>>>> DataStream
> >>>>>>>>>> when calling env.source(boundedSource) if he does not need
> >> special
> >>>>>>>>>> operations defined on a BoundedDataStream. If he needs this,
> >> then
> >>>>>> one
> >>>>>>>> could
> >>>>>>>>>> use the method BoundedDataStream
> >> env.boundedSource(boundedSource).
> >>>>>>>>>>
> >>>>>>>>>> If possible, we could enforce the proper usage of
> >>>>>> env.boundedSource()
> >>>>>>> by
> >>>>>>>>>> introducing a BoundedSource type so that one cannot pass an
> >>>>>>>>>> unbounded source to it. That way users would not be able to
> >> shoot
> >>>>>>>>>> themselves in the foot.
> >>>>>>>>>>
> >>>>>>>>>> Maybe this has already been asked before but I was wondering why
> >>> the
> >>>>>>>>>> SourceReader interface has the method pollNext which hands the
> >>>>>>>>>> responsibility of outputting elements to the SourceReader
> >>>>>>>> implementation?
> >>>>>>>>>> Has this been done for backwards compatibility reasons with the
> >>> old
> >>>>>>>> source
> >>>>>>>>>> interface? If not, then one could define a Collection<E>
> >>>>>>>> getNextRecords()
> >>>>>>>>>> method which returns the currently retrieved records and then
> >> the
> >>>>>>> caller
> >>>>>>>>>> emits them outside of the SourceReader. That way the interface
> >>> would
> >>>>>>> not
> >>>>>>>>>> allow to implement an outputting loop where we never hand back
> >>>>>> control
> >>>>>>>> to
> >>>>>>>>>> the caller. At the moment, this contract can be easily broken
> >> and
> >>> is
> >>>>>>>> only
> >>>>>>>>>> mentioned loosely in the JavaDocs.
> >>>>>>>>>>
> >>>>>>>>>> Cheers,
> >>>>>>>>>> Till
> >>>>>>>>>>
> >>>>>>>>>> On Tue, Dec 10, 2019 at 7:49 AM Jingsong Li <
> >>> [hidden email]
> >>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> >>>>>>>> [hidden email]>>
> >>>>>>>>>> wrote:
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> Hi all,
> >>>>>>>>>>
> >>>>>>>>>> I think current design is good.
> >>>>>>>>>>
> >>>>>>>>>> My understanding is:
> >>>>>>>>>>
> >>>>>>>>>> For execution mode: bounded mode and continuous mode, It's
> >> totally
> >>>>>>>>>> different. I don't think we have the ability to integrate the
> >> two
> >>>>>>> models
> >>>>>>>>>>
> >>>>>>>>>> at
> >>>>>>>>>>
> >>>>>>>>>> present. It's about scheduling, memory, algorithms, States, etc.
> >>> we
> >>>>>>>>>> shouldn't confuse them.
> >>>>>>>>>>
> >>>>>>>>>> For source capabilities: only bounded, only continuous, both
> >>> bounded
> >>>>>>> and
> >>>>>>>>>> continuous.
> >>>>>>>>>> I think Kafka is a source that can be ran both bounded
> >>>>>>>>>> and continuous execution mode.
> >>>>>>>>>> And Kafka with end offset should be ran both bounded
> >>>>>>>>>> and continuous execution mode.  Using apache Beam with Flink
> >>>>>> runner, I
> >>>>>>>>>>
> >>>>>>>>>> used
> >>>>>>>>>>
> >>>>>>>>>> to run a "bounded" Kafka in streaming mode. For our previous
> >>>>>>> DataStream,
> >>>>>>>>>>
> >>>>>>>>>> it
> >>>>>>>>>>
> >>>>>>>>>> is not necessarily required that the source cannot be bounded.
> >>>>>>>>>>
> >>>>>>>>>> So it is my thought for Dawid's question:
> >>>>>>>>>> 1.pass a bounded source to continuousSource() +1
> >>>>>>>>>> 2.pass a continuous source to boundedSource() -1, should throw
> >>>>>>>> exception.
> >>>>>>>>>>
> >>>>>>>>>> In StreamExecutionEnvironment, continuousSource and
> >> boundedSource
> >>>>>>> define
> >>>>>>>>>> the execution mode. It defines a clear boundary of execution
> >> mode.
> >>>>>>>>>>
> >>>>>>>>>> Best,
> >>>>>>>>>> Jingsong Lee
> >>>>>>>>>>
> >>>>>>>>>> On Tue, Dec 10, 2019 at 10:37 AM Jark Wu <[hidden email]
> >>> <mailto:
> >>>>>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> >>>> wrote:
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> I agree with Dawid's point that the boundedness information
> >> should
> >>>>>>> come
> >>>>>>>>>> from the source itself (e.g. the end timestamp), not through
> >>>>>>>>>> env.boundedSouce()/continuousSource().
> >>>>>>>>>> I think if we want to support something like `env.source()` that
> >>>>>>> derive
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> execution mode from source, `supportsBoundedness(Boundedness)`
> >>>>>>>>>> method is not enough, because we don't know whether it is
> >> bounded
> >>> or
> >>>>>>>>>>
> >>>>>>>>>> not.
> >>>>>>>>>>
> >>>>>>>>>> Best,
> >>>>>>>>>> Jark
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <
> >>>>>> [hidden email]
> >>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> >>>>>>>> [hidden email]>>
> >>>>>>>>>> wrote:
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> One more thing. In the current proposal, with the
> >>>>>>>>>> supportsBoundedness(Boundedness) method and the boundedness
> >> coming
> >>>>>>>>>>
> >>>>>>>>>> from
> >>>>>>>>>>
> >>>>>>>>>> either continuousSource or boundedSource I could not find how
> >> this
> >>>>>>>>>> information is fed back to the SplitEnumerator.
> >>>>>>>>>>
> >>>>>>>>>> Best,
> >>>>>>>>>>
> >>>>>>>>>> Dawid
> >>>>>>>>>>
> >>>>>>>>>> On 09/12/2019 13:52, Becket Qin wrote:
> >>>>>>>>>>
> >>>>>>>>>> Hi Dawid,
> >>>>>>>>>>
> >>>>>>>>>> Thanks for the comments. This actually brings another relevant
> >>>>>>>>>>
> >>>>>>>>>> question
> >>>>>>>>>>
> >>>>>>>>>> about what does a "bounded source" imply. I actually had the
> >> same
> >>>>>>>>>> impression when I look at the Source API. Here is what I
> >>> understand
> >>>>>>>>>>
> >>>>>>>>>> after
> >>>>>>>>>>
> >>>>>>>>>> some discussion with Stephan. The bounded source has the
> >> following
> >>>>>>>>>>
> >>>>>>>>>> impacts.
> >>>>>>>>>>
> >>>>>>>>>> 1. API validity.
> >>>>>>>>>> - A bounded source generates a bounded stream so some operations
> >>>>>>>>>>
> >>>>>>>>>> that
> >>>>>>>>>>
> >>>>>>>>>> only
> >>>>>>>>>>
> >>>>>>>>>> works for bounded records would be performed, e.g. sort.
> >>>>>>>>>> - To expose these bounded stream only APIs, there are two
> >> options:
> >>>>>>>>>>       a. Add them to the DataStream API and throw exception if a
> >>>>>>>>>>
> >>>>>>>>>> method
> >>>>>>>>>>
> >>>>>>>>>> is
> >>>>>>>>>>
> >>>>>>>>>> called on an unbounded stream.
> >>>>>>>>>>       b. Create a BoundedDataStream class which is returned from
> >>>>>>>>>> env.boundedSource(), while DataStream is returned from
> >>>>>>>>>>
> >>>>>>>>>> env.continousSource().
> >>>>>>>>>>
> >>>>>>>>>> Note that this cannot be done by having single
> >>>>>>>>>>
> >>>>>>>>>> env.source(theSource)
> >>>>>>>>>>
> >>>>>>>>>> even
> >>>>>>>>>>
> >>>>>>>>>> the Source has a getBoundedness() method.
> >>>>>>>>>>
> >>>>>>>>>> 2. Scheduling
> >>>>>>>>>> - A bounded source could be computed stage by stage without
> >>>>>>>>>>
> >>>>>>>>>> bringing
> >>>>>>>>>>
> >>>>>>>>>> up
> >>>>>>>>>>
> >>>>>>>>>> all
> >>>>>>>>>>
> >>>>>>>>>> the tasks at the same time.
> >>>>>>>>>>
> >>>>>>>>>> 3. Operator behaviors
> >>>>>>>>>> - A bounded source indicates the records are finite so some
> >>>>>>>>>>
> >>>>>>>>>> operators
> >>>>>>>>>>
> >>>>>>>>>> can
> >>>>>>>>>>
> >>>>>>>>>> wait until it receives all the records before it starts the
> >>>>>>>>>>
> >>>>>>>>>> processing.
> >>>>>>>>>>
> >>>>>>>>>> In the above impact, only 1 is relevant to the API design. And
> >> the
> >>>>>>>>>>
> >>>>>>>>>> current
> >>>>>>>>>>
> >>>>>>>>>> proposal in FLIP-27 is following 1.b.
> >>>>>>>>>>
> >>>>>>>>>> // boundedness depends of source property, imo this should
> >> always
> >>>>>>>>>>
> >>>>>>>>>> be
> >>>>>>>>>>
> >>>>>>>>>> preferred
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> DataStream<MyType> stream = env.source(theSource);
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> In your proposal, does DataStream have bounded stream only
> >>> methods?
> >>>>>>>>>>
> >>>>>>>>>> It
> >>>>>>>>>>
> >>>>>>>>>> looks it should have, otherwise passing a bounded Source to
> >>>>>>>>>>
> >>>>>>>>>> env.source()
> >>>>>>>>>>
> >>>>>>>>>> would be confusing. In that case, we will essentially do 1.a if
> >> an
> >>>>>>>>>> unbounded Source is created from env.source(unboundedSource).
> >>>>>>>>>>
> >>>>>>>>>> If we have the methods only supported for bounded streams in
> >>>>>>>>>>
> >>>>>>>>>> DataStream,
> >>>>>>>>>>
> >>>>>>>>>> it
> >>>>>>>>>>
> >>>>>>>>>> seems a little weird to have a separate BoundedDataStream
> >>>>>>>>>>
> >>>>>>>>>> interface.
> >>>>>>>>>>
> >>>>>>>>>> Am I understand it correctly?
> >>>>>>>>>>
> >>>>>>>>>> Thanks,
> >>>>>>>>>>
> >>>>>>>>>> Jiangjie (Becket) Qin
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <
> >>>>>>>>>>
> >>>>>>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>>>>>
> >>>>>>>>>> wrote:
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> Hi all,
> >>>>>>>>>>
> >>>>>>>>>> Really well written proposal and very important one. I must
> >> admit
> >>>>>>>>>>
> >>>>>>>>>> I
> >>>>>>>>>>
> >>>>>>>>>> have
> >>>>>>>>>>
> >>>>>>>>>> not understood all the intricacies of it yet.
> >>>>>>>>>>
> >>>>>>>>>> One question I have though is about where does the information
> >>>>>>>>>>
> >>>>>>>>>> about
> >>>>>>>>>>
> >>>>>>>>>> boundedness come from. I think in most cases it is a property of
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> source. As you described it might be e.g. end offset, a flag
> >>>>>>>>>>
> >>>>>>>>>> should
> >>>>>>>>>>
> >>>>>>>>>> it
> >>>>>>>>>>
> >>>>>>>>>> monitor new splits etc. I think it would be a really nice use
> >> case
> >>>>>>>>>>
> >>>>>>>>>> to
> >>>>>>>>>>
> >>>>>>>>>> be
> >>>>>>>>>>
> >>>>>>>>>> able to say:
> >>>>>>>>>>
> >>>>>>>>>> new KafkaSource().readUntil(long timestamp),
> >>>>>>>>>>
> >>>>>>>>>> which could work as an "end offset". Moreover I think all
> >> Bounded
> >>>>>>>>>>
> >>>>>>>>>> sources
> >>>>>>>>>>
> >>>>>>>>>> support continuous mode, but no intrinsically continuous source
> >>>>>>>>>>
> >>>>>>>>>> support
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> Bounded mode. If I understood the proposal correctly it suggest
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> boundedness sort of "comes" from the outside of the source, from
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> invokation of either boundedStream or continousSource.
> >>>>>>>>>>
> >>>>>>>>>> I am wondering if it would make sense to actually change the
> >>>>>>>>>>
> >>>>>>>>>> method
> >>>>>>>>>>
> >>>>>>>>>> boolean Source#supportsBoundedness(Boundedness)
> >>>>>>>>>>
> >>>>>>>>>> to
> >>>>>>>>>>
> >>>>>>>>>> Boundedness Source#getBoundedness().
> >>>>>>>>>>
> >>>>>>>>>> As for the methods #boundedSource, #continousSource, assuming
> >> the
> >>>>>>>>>> boundedness is property of the source they do not affect how the
> >>>>>>>>>>
> >>>>>>>>>> enumerator
> >>>>>>>>>>
> >>>>>>>>>> works, but mostly how the dag is scheduled, right? I am not
> >>>>>>>>>>
> >>>>>>>>>> against
> >>>>>>>>>>
> >>>>>>>>>> those
> >>>>>>>>>>
> >>>>>>>>>> methods, but I think it is a very specific use case to actually
> >>>>>>>>>>
> >>>>>>>>>> override
> >>>>>>>>>>
> >>>>>>>>>> the property of the source. In general I would expect users to
> >>>>>>>>>>
> >>>>>>>>>> only
> >>>>>>>>>>
> >>>>>>>>>> call
> >>>>>>>>>>
> >>>>>>>>>> env.source(theSource), where the source tells if it is bounded
> >> or
> >>>>>>>>>>
> >>>>>>>>>> not. I
> >>>>>>>>>>
> >>>>>>>>>> would suggest considering following set of methods:
> >>>>>>>>>>
> >>>>>>>>>> // boundedness depends of source property, imo this should
> >> always
> >>>>>>>>>>
> >>>>>>>>>> be
> >>>>>>>>>>
> >>>>>>>>>> preferred
> >>>>>>>>>>
> >>>>>>>>>> DataStream<MyType> stream = env.source(theSource);
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> // always continous execution, whether bounded or unbounded
> >> source
> >>>>>>>>>>
> >>>>>>>>>> DataStream<MyType> boundedStream =
> >> env.continousSource(theSource);
> >>>>>>>>>>
> >>>>>>>>>> // imo this would make sense if the BoundedDataStream provides
> >>>>>>>>>>
> >>>>>>>>>> additional features unavailable for continous mode
> >>>>>>>>>>
> >>>>>>>>>> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> Best,
> >>>>>>>>>>
> >>>>>>>>>> Dawid
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> On 04/12/2019 11:25, Stephan Ewen wrote:
> >>>>>>>>>>
> >>>>>>>>>> Thanks, Becket, for updating this.
> >>>>>>>>>>
> >>>>>>>>>> I agree with moving the aspects you mentioned into separate
> >> FLIPs
> >>>>>>>>>>
> >>>>>>>>>> -
> >>>>>>>>>>
> >>>>>>>>>> this
> >>>>>>>>>>
> >>>>>>>>>> one way becoming unwieldy in size.
> >>>>>>>>>>
> >>>>>>>>>> +1 to the FLIP in its current state. Its a very detailed
> >> write-up,
> >>>>>>>>>>
> >>>>>>>>>> nicely
> >>>>>>>>>>
> >>>>>>>>>> done!
> >>>>>>>>>>
> >>>>>>>>>> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <[hidden email]
> >>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> >>>>>>>> [hidden email]>>
> >>>>>>>>>>
> >>>>>>>>>> <
> >>>>>>>>>>
> >>>>>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> >>>>>>>>>>
> >>>>>>>>>> Hi all,
> >>>>>>>>>>
> >>>>>>>>>> Sorry for the long belated update. I have updated FLIP-27 wiki
> >>>>>>>>>>
> >>>>>>>>>> page
> >>>>>>>>>>
> >>>>>>>>>> with
> >>>>>>>>>>
> >>>>>>>>>> the latest proposals. Some noticeable changes include:
> >>>>>>>>>> 1. A new generic communication mechanism between SplitEnumerator
> >>>>>>>>>>
> >>>>>>>>>> and
> >>>>>>>>>>
> >>>>>>>>>> SourceReader.
> >>>>>>>>>> 2. Some detail API method signature changes.
> >>>>>>>>>>
> >>>>>>>>>> We left a few things out of this FLIP and will address them in
> >>>>>>>>>>
> >>>>>>>>>> separate
> >>>>>>>>>>
> >>>>>>>>>> FLIPs. Including:
> >>>>>>>>>> 1. Per split event time.
> >>>>>>>>>> 2. Event time alignment.
> >>>>>>>>>> 3. Fine grained failover for SplitEnumerator failure.
> >>>>>>>>>>
> >>>>>>>>>> Please let us know if you have any question.
> >>>>>>>>>>
> >>>>>>>>>> Thanks,
> >>>>>>>>>>
> >>>>>>>>>> Jiangjie (Becket) Qin
> >>>>>>>>>>
> >>>>>>>>>> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]
> >>>>>>> <mailto:
> >>>>>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>> <
> >>>>>>>>>>
> >>>>>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> >>>>>>>>>>
> >>>>>>>>>> Hi  Łukasz!
> >>>>>>>>>>
> >>>>>>>>>> Becket and me are working hard on figuring out the last details
> >>>>>>>>>>
> >>>>>>>>>> and
> >>>>>>>>>>
> >>>>>>>>>> implementing the first PoC. We would update the FLIP hopefully
> >>>>>>>>>>
> >>>>>>>>>> next
> >>>>>>>>>>
> >>>>>>>>>> week.
> >>>>>>>>>>
> >>>>>>>>>> There is a fair chance that a first version of this will be in
> >>>>>>>>>>
> >>>>>>>>>> 1.10,
> >>>>>>>>>>
> >>>>>>>>>> but
> >>>>>>>>>>
> >>>>>>>>>> I
> >>>>>>>>>>
> >>>>>>>>>> think it will take another release to battle test it and migrate
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> connectors.
> >>>>>>>>>>
> >>>>>>>>>> Best,
> >>>>>>>>>> Stephan
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <
> >> [hidden email]
> >>>>>>>> <mailto:[hidden email]>
> >>>>>>>>>>
> >>>>>>>>>> <
> >>>>>>>>>>
> >>>>>>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>>>>>
> >>>>>>>>>> wrote:
> >>>>>>>>>>
> >>>>>>>>>> Hi,
> >>>>>>>>>>
> >>>>>>>>>> This proposal looks very promising for us. Do you have any plans
> >>>>>>>>>>
> >>>>>>>>>> in
> >>>>>>>>>>
> >>>>>>>>>> which
> >>>>>>>>>>
> >>>>>>>>>> Flink release it is going to be released? We are thinking on
> >>>>>>>>>>
> >>>>>>>>>> using a
> >>>>>>>>>>
> >>>>>>>>>> Data
> >>>>>>>>>>
> >>>>>>>>>> Set API for our future use cases but on the other hand Data Set
> >>>>>>>>>>
> >>>>>>>>>> API
> >>>>>>>>>>
> >>>>>>>>>> is
> >>>>>>>>>>
> >>>>>>>>>> going to be deprecated so using proposed bounded data streams
> >>>>>>>>>>
> >>>>>>>>>> solution
> >>>>>>>>>>
> >>>>>>>>>> could be more viable in the long term.
> >>>>>>>>>>
> >>>>>>>>>> Thanks,
> >>>>>>>>>> Łukasz
> >>>>>>>>>>
> >>>>>>>>>> On 2019/10/01 15:48:03, Thomas Weise <[hidden email]
> >>>>>> <mailto:
> >>>>>>>> [hidden email]>> <[hidden email] <mailto:
> >>>>>>>> [hidden email]>> <
> >>>>>>>>>>
> >>>>>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> >>>>>>>>>>
> >>>>>>>>>> Thanks for putting together this proposal!
> >>>>>>>>>>
> >>>>>>>>>> I see that the "Per Split Event Time" and "Event Time Alignment"
> >>>>>>>>>>
> >>>>>>>>>> sections
> >>>>>>>>>>
> >>>>>>>>>> are still TBD.
> >>>>>>>>>>
> >>>>>>>>>> It would probably be good to flesh those out a bit before
> >>>>>>>>>>
> >>>>>>>>>> proceeding
> >>>>>>>>>>
> >>>>>>>>>> too
> >>>>>>>>>>
> >>>>>>>>>> far
> >>>>>>>>>>
> >>>>>>>>>> as the event time alignment will probably influence the
> >>>>>>>>>>
> >>>>>>>>>> interaction
> >>>>>>>>>>
> >>>>>>>>>> with
> >>>>>>>>>>
> >>>>>>>>>> the split reader, specifically ReaderStatus
> >>>>>>>>>>
> >>>>>>>>>> emitNext(SourceOutput<E>
> >>>>>>>>>>
> >>>>>>>>>> output).
> >>>>>>>>>>
> >>>>>>>>>> We currently have only one implementation for event time
> >> alignment
> >>>>>>>>>>
> >>>>>>>>>> in
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> Kinesis consumer. The synchronization in that case takes place
> >> as
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> last
> >>>>>>>>>>
> >>>>>>>>>> step before records are emitted downstream (RecordEmitter). With
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> currently proposed interfaces, the equivalent can be implemented
> >>>>>>>>>>
> >>>>>>>>>> in
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> reader loop, although note that in the Kinesis consumer the per
> >>>>>>>>>>
> >>>>>>>>>> shard
> >>>>>>>>>>
> >>>>>>>>>> threads push records.
> >>>>>>>>>>
> >>>>>>>>>> Synchronization has not been implemented for the Kafka consumer
> >>>>>>>>>>
> >>>>>>>>>> yet.
> >>>>>>>>>>
> >>>>>>>>>> https://issues.apache.org/jira/browse/FLINK-12675 <
> >>>>>>>> https://issues.apache.org/jira/browse/FLINK-12675>
> >>>>>>>>>>
> >>>>>>>>>> When I looked at it, I realized that the implementation will
> >> look
> >>>>>>>>>>
> >>>>>>>>>> quite
> >>>>>>>>>>
> >>>>>>>>>> different
> >>>>>>>>>> from Kinesis because it needs to take place in the pull part,
> >>>>>>>>>>
> >>>>>>>>>> where
> >>>>>>>>>>
> >>>>>>>>>> records
> >>>>>>>>>>
> >>>>>>>>>> are taken from the Kafka client. Due to the multiplexing it
> >> cannot
> >>>>>>>>>>
> >>>>>>>>>> be
> >>>>>>>>>>
> >>>>>>>>>> done
> >>>>>>>>>>
> >>>>>>>>>> by blocking the split thread like it currently works for
> >> Kinesis.
> >>>>>>>>>>
> >>>>>>>>>> Reading
> >>>>>>>>>>
> >>>>>>>>>> from individual Kafka partitions needs to be controlled via
> >>>>>>>>>>
> >>>>>>>>>> pause/resume
> >>>>>>>>>>
> >>>>>>>>>> on the Kafka client.
> >>>>>>>>>>
> >>>>>>>>>> To take on that responsibility the split thread would need to be
> >>>>>>>>>>
> >>>>>>>>>> aware
> >>>>>>>>>>
> >>>>>>>>>> of
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>> watermarks or at least whether it should or should not continue
> >> to
> >>>>>>>>>>
> >>>>>>>>>> consume
> >>>>>>>>>>
> >>>>>>>>>> a given split and this may require a different SourceReader or
> >>>>>>>>>>
> >>>>>>>>>> SourceOutput
> >>>>>>>>>>
> >>>>>>>>>> interface.
> >>>>>>>>>>
> >>>>>>>>>> Thanks,
> >>>>>>>>>> Thomas
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email]
> >>>>>> <mailto:
> >>>>>>>> [hidden email]>> <[hidden email] <mailto:
> >> [hidden email]
> >>>>>
> >>>>>> <
> >>>>>>>>>>
> >>>>>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
> >>>>>>>>>>
> >>>>>>>>>> Hi Stephan,
> >>>>>>>>>>
> >>>>>>>>>> Thank you for feedback!
> >>>>>>>>>> Will take a look at your branch before public discussing.
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <[hidden email]
> >>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> >>> [hidden email]
> >>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> <
> >>>>>>>>>>
> >>>>>>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>>>>>
> >>>>>>>>>> wrote:
> >>>>>>>>>>
> >>>>>>>>>> Hi Biao!
> >>>>>>>>>>
> >>>>>>>>>> Thanks for reviving this. I would like to join this discussion,
> >>>>>>>>>>
> >>>>>>>>>> but
> >>>>>>>>>>
> >>>>>>>>>> am
> >>>>>>>>>>
> >>>>>>>>>> quite occupied with the 1.9 release, so can we maybe pause this
> >>>>>>>>>>
> >>>>>>>>>> discussion
> >>>>>>>>>>
> >>>>>>>>>> for a week or so?
> >>>>>>>>>>
> >>>>>>>>>> In the meantime I can share some suggestion based on prior
> >>>>>>>>>>
> >>>>>>>>>> experiments:
> >>>>>>>>>>
> >>>>>>>>>> How to do watermarks / timestamp extractors in a simpler and
> >> more
> >>>>>>>>>>
> >>>>>>>>>> flexible
> >>>>>>>>>>
> >>>>>>>>>> way. I think that part is quite promising should be part of the
> >>>>>>>>>>
> >>>>>>>>>> new
> >>>>>>>>>>
> >>>>>>>>>> source
> >>>>>>>>>>
> >>>>>>>>>> interface.
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> >>>>>>>> <
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
> >>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> >>>>>>>> <
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
> >>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> Some experiments on how to build the source reader and its
> >>>>>>>>>>
> >>>>>>>>>> library
> >>>>>>>>>>
> >>>>>>>>>> for
> >>>>>>>>>>
> >>>>>>>>>> common threading/split patterns:
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> >>>>>>>> <
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
> >>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> Best,
> >>>>>>>>>> Stephan
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]
> >>>>>>> <mailto:
> >>>>>>>> [hidden email]>> <[hidden email] <mailto:
> >> [hidden email]
> >>>>>
> >>>>>> <
> >>>>>>>>>>
> >>>>>>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>>>>>
> >>>>>>>>>> wrote:
> >>>>>>>>>>
> >>>>>>>>>> Hi devs,
> >>>>>>>>>>
> >>>>>>>>>> Since 1.9 is nearly released, I think we could get back to
> >>>>>>>>>>
> >>>>>>>>>> FLIP-27.
> >>>>>>>>>>
> >>>>>>>>>> I
> >>>>>>>>>>
> >>>>>>>>>> believe it should be included in 1.10.
> >>>>>>>>>>
> >>>>>>>>>> There are so many things mentioned in document of FLIP-27. [1] I
> >>>>>>>>>>
> >>>>>>>>>> think
> >>>>>>>>>>
> >>>>>>>>>> we'd better discuss them separately. However the wiki is not a
> >>>>>>>>>>
> >>>>>>>>>> good
> >>>>>>>>>>
> >>>>>>>>>> place
> >>>>>>>>>>
> >>>>>>>>>> to discuss. I wrote google doc about SplitReader API which
> >>>>>>>>>>
> >>>>>>>>>> misses
> >>>>>>>>>>
> >>>>>>>>>> some
> >>>>>>>>>>
> >>>>>>>>>> details in the document. [2]
> >>>>>>>>>>
> >>>>>>>>>> 1.
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> >>>>>>>> <
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
> >>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> 2.
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> >>>>>>>> <
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
> >>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> CC Stephan, Aljoscha, Piotrek, Becket
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email]
> >>>>>> <mailto:
> >>>>>>>> [hidden email]>> <[hidden email] <mailto:
> >> [hidden email]
> >>>>>
> >>>>>> <
> >>>>>>>>>>
> >>>>>>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>>>>>
> >>>>>>>>>> wrote:
> >>>>>>>>>>
> >>>>>>>>>> Hi Steven,
> >>>>>>>>>> Thank you for the feedback. Please take a look at the document
> >>>>>>>>>>
> >>>>>>>>>> FLIP-27
> >>>>>>>>>>
> >>>>>>>>>> <
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> >>>>>>>> <
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>
> >>>
> >>
> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
> >>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> which
> >>>>>>>>>>
> >>>>>>>>>> is updated recently. A lot of details of enumerator were added
> >>>>>>>>>>
> >>>>>>>>>> in
> >>>>>>>>>>
> >>>>>>>>>> this
> >>>>>>>>>>
> >>>>>>>>>> document. I think it would help.
> >>>>>>>>>>
> >>>>>>>>>> Steven Wu <[hidden email] <mailto:[hidden email]>>
> >> <
> >>>>>>>> [hidden email] <mailto:[hidden email]>> <
> >>>>>>> [hidden email]
> >>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
> >>>>>>>> [hidden email]>>
> >>>>>>>>>>
> >>>>>>>>>> 于2019年3月28日周四
> >>>>>>>>>>
> >>>>>>>>>> 下午12:52写道：
> >>>>>>>>>>
> >>>>>>>>>> This proposal mentioned that SplitEnumerator might run on the
> >>>>>>>>>> JobManager or
> >>>>>>>>>> in a single task on a TaskManager.
> >>>>>>>>>>
> >>>>>>>>>> if enumerator is a single task on a taskmanager, then the job
> >>>>>>>>>>
> >>>>>>>>>> DAG
> >>>>>>>>>>
> >>>>>>>>>> can
> >>>>>>>>>>
> >>>>>>>>>> never
> >>>>>>>>>> been embarrassingly parallel anymore. That will nullify the
> >>>>>>>>>>
> >>>>>>>>>> leverage
> >>>>>>>>>>
> >>>>>>>>>> of
> >>>>>>>>>>
> >>>>>>>>>> fine-grained recovery for embarrassingly parallel jobs.
> >>>>>>>>>>
> >>>>>>>>>> It's not clear to me what's the implication of running
> >>>>>>>>>>
> >>>>>>>>>> enumerator
> >>>>>>>>>>
> >>>>>>>>>> on
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> jobmanager. So I will leave that out for now.
> >>>>>>>>>>
> >>>>>>>>>> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email]
> >>>>>> <mailto:
> >>>>>>>> [hidden email]>> <[hidden email] <mailto:
> >> [hidden email]
> >>>>>
> >>>>>> <
> >>>>>>>>>>
> >>>>>>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>>>>>
> >>>>>>>>>> wrote:
> >>>>>>>>>>
> >>>>>>>>>> Hi Stephan & Piotrek,
> >>>>>>>>>>
> >>>>>>>>>> Thank you for feedback.
> >>>>>>>>>>
> >>>>>>>>>> It seems that there are a lot of things to do in community.
> >>>>>>>>>>
> >>>>>>>>>> I
> >>>>>>>>>>
> >>>>>>>>>> am
> >>>>>>>>>>
> >>>>>>>>>> just
> >>>>>>>>>>
> >>>>>>>>>> afraid that this discussion may be forgotten since there so
> >>>>>>>>>>
> >>>>>>>>>> many
> >>>>>>>>>>
> >>>>>>>>>> proposals
> >>>>>>>>>>
> >>>>>>>>>> recently.
> >>>>>>>>>> Anyway, wish to see the split topics soon :)
> >>>>>>>>>>
> >>>>>>>>>> Piotr Nowojski <[hidden email] <mailto:
> >>> [hidden email]
> >>>>>>>>
> >>>>>>> <
> >>>>>>>> [hidden email] <mailto:[hidden email]>> <
> >>>>>>>> [hidden email] <mailto:[hidden email]>> <
> >>>>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>>>>>
> >>>>>>>>>> 于2019年1月24日周四
> >>>>>>>>>>
> >>>>>>>>>> 下午8:21写道：
> >>>>>>>>>>
> >>>>>>>>>> Hi Biao!
> >>>>>>>>>>
> >>>>>>>>>> This discussion was stalled because of preparations for
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> open
> >>>>>>>>>>
> >>>>>>>>>> sourcing
> >>>>>>>>>>
> >>>>>>>>>> & merging Blink. I think before creating the tickets we
> >>>>>>>>>>
> >>>>>>>>>> should
> >>>>>>>>>>
> >>>>>>>>>> split this
> >>>>>>>>>>
> >>>>>>>>>> discussion into topics/areas outlined by Stephan and
> >>>>>>>>>>
> >>>>>>>>>> create
> >>>>>>>>>>
> >>>>>>>>>> Flips
> >>>>>>>>>>
> >>>>>>>>>> for
> >>>>>>>>>>
> >>>>>>>>>> that.
> >>>>>>>>>>
> >>>>>>>>>> I think there is no chance for this to be completed in
> >>>>>>>>>>
> >>>>>>>>>> couple
> >>>>>>>>>>
> >>>>>>>>>> of
> >>>>>>>>>>
> >>>>>>>>>> remaining
> >>>>>>>>>>
> >>>>>>>>>> weeks/1 month before 1.8 feature freeze, however it would
> >>>>>>>>>>
> >>>>>>>>>> be
> >>>>>>>>>>
> >>>>>>>>>> good
> >>>>>>>>>>
> >>>>>>>>>> to aim
> >>>>>>>>>>
> >>>>>>>>>> with those changes for 1.9.
> >>>>>>>>>>
> >>>>>>>>>> Piotrek
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email] <mailto:
> >>>>>>>> [hidden email]>> <[hidden email] <mailto:
> >> [hidden email]
> >>>>>
> >>>>>> <
> >>>>>>>>>>
> >>>>>>>>>> [hidden email] <mailto:[hidden email]>>
> >>>>>>>>>>
> >>>>>>>>>> wrote:
> >>>>>>>>>>
> >>>>>>>>>> Hi community,
> >>>>>>>>>> The summary of Stephan makes a lot sense to me. It is
> >>>>>>>>>>
> >>>>>>>>>> much
> >>>>>>>>>>
> >>>>>>>>>> clearer
> >>>>>>>>>>
> >>>>>>>>>> indeed
> >>>>>>>>>>
> >>>>>>>>>> after splitting the complex topic into small ones.
> >>>>>>>>>> I was wondering is there any detail plan for next step?
> >>>>>>>>>>
> >>>>>>>>>> If
> >>>>>>>>>>
> >>>>>>>>>> not,
> >>>>>>>>>>
> >>>>>>>>>> I
> >>>>>>>>>>
> >>>>>>>>>> would
> >>>>>>>>>>
> >>>>>>>>>> like to push this thing forward by creating some JIRA
> >>>>>>>>>>
> >>>>>>>>>> issues.
> >>>>>>>>>>
> >>>>>>>>>> Another question is that should version 1.8 include
> >>>>>>>>>>
> >>>>>>>>>> these
> >>>>>>>>>>
> >>>>>>>>>> features?
> >>>>>>>>>>
> >>>>>>>>>> Stephan Ewen <[hidden email] <mailto:[hidden email]>> <
> >>>>>>>> [hidden email] <mailto:[hidden email]>> <[hidden email]
> >>>> <mailto:
> >>>>>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
> >>>>>>>> 于2018年12月1日周六
> >>>>>>>>>>
> >>>>>>>>>> 上午4:20写道：
> >>>>>>>>>>
> >>>>>>>>>> Thanks everyone for the lively discussion. Let me try
> >>>>>>>>>>
> >>>>>>>>>> to
> >>>>>>>>>>
> >>>>>>>>>> summarize
> >>>>>>>>>>
> >>>>>>>>>> where I
> >>>>>>>>>>
> >>>>>>>>>> see convergence in the discussion and open issues.
> >>>>>>>>>> I'll try to group this by design aspect of the source.
> >>>>>>>>>>
> >>>>>>>>>> Please
> >>>>>>>>>>
> >>>>>>>>>> let me
> >>>>>>>>>>
> >>>>>>>>>> know
> >>>>>>>>>>
> >>>>>>>>>> if I got things wrong or missed something crucial here.
> >>>>>>>>>>
> >>>>>>>>>> For issues 1-3, if the below reflects the state of the
> >>>>>>>>>>
> >>>>>>>>>> discussion, I
> >>>>>>>>>>
> >>>>>>>>>> would
> >>>>>>>>>>
> >>>>>>>>>> try and update the FLIP in the next days.
> >>>>>>>>>> For the remaining ones we need more discussion.
> >>>>>>>>>>
> >>>>>>>>>> I would suggest to fork each of these aspects into a
> >>>>>>>>>>
> >>>>>>>>>> separate
> >>>>>>>>>>
> >>>>>>>>>> mail
> >>>>>>>>>>
> >>>>>>>>>> thread,
> >>>>>>>>>>
> >>>>>>>>>> or will loose sight of the individual aspects.
> >>>>>>>>>>
> >>>>>>>>>> *(1) Separation of Split Enumerator and Split Reader*
> >>>>>>>>>>
> >>>>>>>>>> - All seem to agree this is a good thing
> >>>>>>>>>> - Split Enumerator could in the end live on JobManager
> >>>>>>>>>>
> >>>>>>>>>> (and
> >>>>>>>>>>
> >>>>>>>>>> assign
> >>>>>>>>>>
> >>>>>>>>>> splits
> >>>>>>>>>>
> >>>>>>>>>> via RPC) or in a task (and assign splits via data
> >>>>>>>>>>
> >>>>>>>>>> streams)
> >>>>>>>>>>
> >>>>>>>>>> - this discussion is orthogonal and should come later,
> >>>>>>>>>>
> >>>>>>>>>> when
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> interface
> >>>>>>>>>>
> >>>>>>>>>> is agreed upon.
> >>>>>>>>>>
> >>>>>>>>>> *(2) Split Readers for one or more splits*
> >>>>>>>>>>
> >>>>>>>>>> - Discussion seems to agree that we need to support
> >>>>>>>>>>
> >>>>>>>>>> one
> >>>>>>>>>>
> >>>>>>>>>> reader
> >>>>>>>>>>
> >>>>>>>>>> that
> >>>>>>>>>>
> >>>>>>>>>> possibly handles multiple splits concurrently.
> >>>>>>>>>> - The requirement comes from sources where one
> >>>>>>>>>>
> >>>>>>>>>> poll()-style
> >>>>>>>>>>
> >>>>>>>>>> call
> >>>>>>>>>>
> >>>>>>>>>> fetches
> >>>>>>>>>>
> >>>>>>>>>> data from different splits / partitions
> >>>>>>>>>>     --> example sources that require that would be for
> >>>>>>>>>>
> >>>>>>>>>> example
> >>>>>>>>>>
> >>>>>>>>>> Kafka,
> >>>>>>>>>>
> >>>>>>>>>> Pravega, Pulsar
> >>>>>>>>>>
> >>>>>>>>>> - Could have one split reader per source, or multiple
> >>>>>>>>>>
> >>>>>>>>>> split
> >>>>>>>>>>
> >>>>>>>>>> readers
> >>>>>>>>>>
> >>>>>>>>>> that
> >>>>>>>>>>
> >>>>>>>>>> share the "poll()" function
> >>>>>>>>>> - To not make it too complicated, we can start with
> >>>>>>>>>>
> >>>>>>>>>> thinking
> >>>>>>>>>>
> >>>>>>>>>> about
> >>>>>>>>>>
> >>>>>>>>>> one
> >>>>>>>>>>
> >>>>>>>>>> split reader for all splits initially and see if that
> >>>>>>>>>>
> >>>>>>>>>> covers
> >>>>>>>>>>
> >>>>>>>>>> all
> >>>>>>>>>>
> >>>>>>>>>> requirements
> >>>>>>>>>>
> >>>>>>>>>> *(3) Threading model of the Split Reader*
> >>>>>>>>>>
> >>>>>>>>>> - Most active part of the discussion ;-)
> >>>>>>>>>>
> >>>>>>>>>> - A non-blocking way for Flink's task code to interact
> >>>>>>>>>>
> >>>>>>>>>> with
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> source
> >>>>>>>>>>
> >>>>>>>>>> is
> >>>>>>>>>>
> >>>>>>>>>> needed in order to a task runtime code based on a
> >>>>>>>>>> single-threaded/actor-style task design
> >>>>>>>>>>     --> I personally am a big proponent of that, it will
> >>>>>>>>>>
> >>>>>>>>>> help
> >>>>>>>>>>
> >>>>>>>>>> with
> >>>>>>>>>>
> >>>>>>>>>> well-behaved checkpoints, efficiency, and simpler yet
> >>>>>>>>>>
> >>>>>>>>>> more
> >>>>>>>>>>
> >>>>>>>>>> robust
> >>>>>>>>>>
> >>>>>>>>>> runtime
> >>>>>>>>>>
> >>>>>>>>>> code
> >>>>>>>>>>
> >>>>>>>>>> - Users care about simple abstraction, so as a
> >>>>>>>>>>
> >>>>>>>>>> subclass
> >>>>>>>>>>
> >>>>>>>>>> of
> >>>>>>>>>>
> >>>>>>>>>> SplitReader
> >>>>>>>>>>
> >>>>>>>>>> (non-blocking / async) we need to have a
> >>>>>>>>>>
> >>>>>>>>>> BlockingSplitReader
> >>>>>>>>>>
> >>>>>>>>>> which
> >>>>>>>>>>
> >>>>>>>>>> will
> >>>>>>>>>>
> >>>>>>>>>> form the basis of most source implementations.
> >>>>>>>>>>
> >>>>>>>>>> BlockingSplitReader
> >>>>>>>>>>
> >>>>>>>>>> lets
> >>>>>>>>>>
> >>>>>>>>>> users do blocking simple poll() calls.
> >>>>>>>>>> - The BlockingSplitReader would spawn a thread (or
> >>>>>>>>>>
> >>>>>>>>>> more)
> >>>>>>>>>>
> >>>>>>>>>> and
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> thread(s) can make blocking calls and hand over data
> >>>>>>>>>>
> >>>>>>>>>> buffers
> >>>>>>>>>>
> >>>>>>>>>> via
> >>>>>>>>>>
> >>>>>>>>>> a
> >>>>>>>>>>
> >>>>>>>>>> blocking
> >>>>>>>>>>
> >>>>>>>>>> queue
> >>>>>>>>>> - This should allow us to cover both, a fully async
> >>>>>>>>>>
> >>>>>>>>>> runtime,
> >>>>>>>>>>
> >>>>>>>>>> and a
> >>>>>>>>>>
> >>>>>>>>>> simple
> >>>>>>>>>>
> >>>>>>>>>> blocking interface for users.
> >>>>>>>>>> - This is actually very similar to how the Kafka
> >>>>>>>>>>
> >>>>>>>>>> connectors
> >>>>>>>>>>
> >>>>>>>>>> work.
> >>>>>>>>>>
> >>>>>>>>>> Kafka
> >>>>>>>>>>
> >>>>>>>>>> 9+ with one thread, Kafka 8 with multiple threads
> >>>>>>>>>>
> >>>>>>>>>> - On the base SplitReader (the async one), the
> >>>>>>>>>>
> >>>>>>>>>> non-blocking
> >>>>>>>>>>
> >>>>>>>>>> method
> >>>>>>>>>>
> >>>>>>>>>> that
> >>>>>>>>>>
> >>>>>>>>>> gets the next chunk of data would signal data
> >>>>>>>>>>
> >>>>>>>>>> availability
> >>>>>>>>>>
> >>>>>>>>>> via
> >>>>>>>>>>
> >>>>>>>>>> a
> >>>>>>>>>>
> >>>>>>>>>> CompletableFuture, because that gives the best
> >>>>>>>>>>
> >>>>>>>>>> flexibility
> >>>>>>>>>>
> >>>>>>>>>> (can
> >>>>>>>>>>
> >>>>>>>>>> await
> >>>>>>>>>>
> >>>>>>>>>> completion or register notification handlers).
> >>>>>>>>>> - The source task would register a "thenHandle()" (or
> >>>>>>>>>>
> >>>>>>>>>> similar)
> >>>>>>>>>>
> >>>>>>>>>> on the
> >>>>>>>>>>
> >>>>>>>>>> future to put a "take next data" task into the
> >>>>>>>>>>
> >>>>>>>>>> actor-style
> >>>>>>>>>>
> >>>>>>>>>> mailbox
> >>>>>>>>>>
> >>>>>>>>>> *(4) Split Enumeration and Assignment*
> >>>>>>>>>>
> >>>>>>>>>> - Splits may be generated lazily, both in cases where
> >>>>>>>>>>
> >>>>>>>>>> there
> >>>>>>>>>>
> >>>>>>>>>> is a
> >>>>>>>>>>
> >>>>>>>>>> limited
> >>>>>>>>>>
> >>>>>>>>>> number of splits (but very many), or splits are
> >>>>>>>>>>
> >>>>>>>>>> discovered
> >>>>>>>>>>
> >>>>>>>>>> over
> >>>>>>>>>>
> >>>>>>>>>> time
> >>>>>>>>>>
> >>>>>>>>>> - Assignment should also be lazy, to get better load
> >>>>>>>>>>
> >>>>>>>>>> balancing
> >>>>>>>>>>
> >>>>>>>>>> - Assignment needs support locality preferences
> >>>>>>>>>>
> >>>>>>>>>> - Possible design based on discussion so far:
> >>>>>>>>>>
> >>>>>>>>>>     --> SplitReader has a method "addSplits(SplitT...)"
> >>>>>>>>>>
> >>>>>>>>>> to
> >>>>>>>>>>
> >>>>>>>>>> add
> >>>>>>>>>>
> >>>>>>>>>> one or
> >>>>>>>>>>
> >>>>>>>>>> more
> >>>>>>>>>>
> >>>>>>>>>> splits. Some split readers might assume they have only
> >>>>>>>>>>
> >>>>>>>>>> one
> >>>>>>>>>>
> >>>>>>>>>> split
> >>>>>>>>>>
> >>>>>>>>>> ever,
> >>>>>>>>>>
> >>>>>>>>>> concurrently, others assume multiple splits. (Note:
> >>>>>>>>>>
> >>>>>>>>>> idea
> >>>>>>>>>>
> >>>>>>>>>> behind
> >>>>>>>>>>
> >>>>>>>>>> being
> >>>>>>>>>>
> >>>>>>>>>> able
> >>>>>>>>>>
> >>>>>>>>>> to add multiple splits at the same time is to ease
> >>>>>>>>>>
> >>>>>>>>>> startup
> >>>>>>>>>>
> >>>>>>>>>> where
> >>>>>>>>>>
> >>>>>>>>>> multiple
> >>>>>>>>>>
> >>>>>>>>>> splits may be assigned instantly.)
> >>>>>>>>>>     --> SplitReader has a context object on which it can
> >>>>>>>>>>
> >>>>>>>>>> call
> >>>>>>>>>>
> >>>>>>>>>> indicate
> >>>>>>>>>>
> >>>>>>>>>> when
> >>>>>>>>>>
> >>>>>>>>>> splits are completed. The enumerator gets that
> >>>>>>>>>>
> >>>>>>>>>> notification and
> >>>>>>>>>>
> >>>>>>>>>> can
> >>>>>>>>>>
> >>>>>>>>>> use
> >>>>>>>>>>
> >>>>>>>>>> to
> >>>>>>>>>>
> >>>>>>>>>> decide when to assign new splits. This should help both
> >>>>>>>>>>
> >>>>>>>>>> in
> >>>>>>>>>>
> >>>>>>>>>> cases
> >>>>>>>>>>
> >>>>>>>>>> of
> >>>>>>>>>>
> >>>>>>>>>> sources
> >>>>>>>>>>
> >>>>>>>>>> that take splits lazily (file readers) and in case the
> >>>>>>>>>>
> >>>>>>>>>> source
> >>>>>>>>>>
> >>>>>>>>>> needs to
> >>>>>>>>>>
> >>>>>>>>>> preserve a partial order between splits (Kinesis,
> >>>>>>>>>>
> >>>>>>>>>> Pravega,
> >>>>>>>>>>
> >>>>>>>>>> Pulsar may
> >>>>>>>>>>
> >>>>>>>>>> need
> >>>>>>>>>>
> >>>>>>>>>> that).
> >>>>>>>>>>     --> SplitEnumerator gets notification when
> >>>>>>>>>>
> >>>>>>>>>> SplitReaders
> >>>>>>>>>>
> >>>>>>>>>> start
> >>>>>>>>>>
> >>>>>>>>>> and
> >>>>>>>>>>
> >>>>>>>>>> when
> >>>>>>>>>>
> >>>>>>>>>> they finish splits. They can decide at that moment to
> >>>>>>>>>>
> >>>>>>>>>> push
> >>>>>>>>>>
> >>>>>>>>>> more
> >>>>>>>>>>
> >>>>>>>>>> splits
> >>>>>>>>>>
> >>>>>>>>>> to
> >>>>>>>>>>
> >>>>>>>>>> that reader
> >>>>>>>>>>     --> The SplitEnumerator should probably be aware of
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> source
> >>>>>>>>>>
> >>>>>>>>>> parallelism, to build its initial distribution.
> >>>>>>>>>>
> >>>>>>>>>> - Open question: Should the source expose something
> >>>>>>>>>>
> >>>>>>>>>> like
> >>>>>>>>>>
> >>>>>>>>>> "host
> >>>>>>>>>>
> >>>>>>>>>> preferences", so that yarn/mesos/k8s can take this into
> >>>>>>>>>>
> >>>>>>>>>> account
> >>>>>>>>>>
> >>>>>>>>>> when
> >>>>>>>>>>
> >>>>>>>>>> selecting a node to start a TM on?
> >>>>>>>>>>
> >>>>>>>>>> *(5) Watermarks and event time alignment*
> >>>>>>>>>>
> >>>>>>>>>> - Watermark generation, as well as idleness, needs to
> >>>>>>>>>>
> >>>>>>>>>> be
> >>>>>>>>>>
> >>>>>>>>>> per
> >>>>>>>>>>
> >>>>>>>>>> split
> >>>>>>>>>>
> >>>>>>>>>> (like
> >>>>>>>>>>
> >>>>>>>>>> currently in the Kafka Source, per partition)
> >>>>>>>>>> - It is desirable to support optional
> >>>>>>>>>>
> >>>>>>>>>> event-time-alignment,
> >>>>>>>>>>
> >>>>>>>>>> meaning
> >>>>>>>>>>
> >>>>>>>>>> that
> >>>>>>>>>>
> >>>>>>>>>> splits that are ahead are back-pressured or temporarily
> >>>>>>>>>>
> >>>>>>>>>> unsubscribed
> >>>>>>>>>>
> >>>>>>>>>> - I think i would be desirable to encapsulate
> >>>>>>>>>>
> >>>>>>>>>> watermark
> >>>>>>>>>>
> >>>>>>>>>> generation
> >>>>>>>>>>
> >>>>>>>>>> logic
> >>>>>>>>>>
> >>>>>>>>>> in watermark generators, for a separation of concerns.
> >>>>>>>>>>
> >>>>>>>>>> The
> >>>>>>>>>>
> >>>>>>>>>> watermark
> >>>>>>>>>>
> >>>>>>>>>> generators should run per split.
> >>>>>>>>>> - Using watermark generators would also help with
> >>>>>>>>>>
> >>>>>>>>>> another
> >>>>>>>>>>
> >>>>>>>>>> problem of
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> suggested interface, namely supporting non-periodic
> >>>>>>>>>>
> >>>>>>>>>> watermarks
> >>>>>>>>>>
> >>>>>>>>>> efficiently.
> >>>>>>>>>>
> >>>>>>>>>> - Need a way to "dispatch" next record to different
> >>>>>>>>>>
> >>>>>>>>>> watermark
> >>>>>>>>>>
> >>>>>>>>>> generators
> >>>>>>>>>>
> >>>>>>>>>> - Need a way to tell SplitReader to "suspend" a split
> >>>>>>>>>>
> >>>>>>>>>> until a
> >>>>>>>>>>
> >>>>>>>>>> certain
> >>>>>>>>>>
> >>>>>>>>>> watermark is reached (event time backpressure)
> >>>>>>>>>> - This would in fact be not needed (and thus simpler)
> >>>>>>>>>>
> >>>>>>>>>> if
> >>>>>>>>>>
> >>>>>>>>>> we
> >>>>>>>>>>
> >>>>>>>>>> had
> >>>>>>>>>>
> >>>>>>>>>> a
> >>>>>>>>>>
> >>>>>>>>>> SplitReader per split and may be a reason to re-open
> >>>>>>>>>>
> >>>>>>>>>> that
> >>>>>>>>>>
> >>>>>>>>>> discussion
> >>>>>>>>>>
> >>>>>>>>>> *(6) Watermarks across splits and in the Split
> >>>>>>>>>>
> >>>>>>>>>> Enumerator*
> >>>>>>>>>>
> >>>>>>>>>> - The split enumerator may need some watermark
> >>>>>>>>>>
> >>>>>>>>>> awareness,
> >>>>>>>>>>
> >>>>>>>>>> which
> >>>>>>>>>>
> >>>>>>>>>> should
> >>>>>>>>>>
> >>>>>>>>>> be
> >>>>>>>>>>
> >>>>>>>>>> purely based on split metadata (like create timestamp
> >>>>>>>>>>
> >>>>>>>>>> of
> >>>>>>>>>>
> >>>>>>>>>> file
> >>>>>>>>>>
> >>>>>>>>>> splits)
> >>>>>>>>>>
> >>>>>>>>>> - If there are still more splits with overlapping
> >>>>>>>>>>
> >>>>>>>>>> event
> >>>>>>>>>>
> >>>>>>>>>> time
> >>>>>>>>>>
> >>>>>>>>>> range
> >>>>>>>>>>
> >>>>>>>>>> for
> >>>>>>>>>>
> >>>>>>>>>> a
> >>>>>>>>>>
> >>>>>>>>>> split reader, then that split reader should not advance
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> watermark
> >>>>>>>>>>
> >>>>>>>>>> within the split beyond the overlap boundary. Otherwise
> >>>>>>>>>>
> >>>>>>>>>> future
> >>>>>>>>>>
> >>>>>>>>>> splits
> >>>>>>>>>>
> >>>>>>>>>> will
> >>>>>>>>>>
> >>>>>>>>>> produce late data.
> >>>>>>>>>>
> >>>>>>>>>> - One way to approach this could be that the split
> >>>>>>>>>>
> >>>>>>>>>> enumerator
> >>>>>>>>>>
> >>>>>>>>>> may
> >>>>>>>>>>
> >>>>>>>>>> send
> >>>>>>>>>>
> >>>>>>>>>> watermarks to the readers, and the readers cannot emit
> >>>>>>>>>>
> >>>>>>>>>> watermarks
> >>>>>>>>>>
> >>>>>>>>>> beyond
> >>>>>>>>>>
> >>>>>>>>>> that received watermark.
> >>>>>>>>>> - Many split enumerators would simply immediately send
> >>>>>>>>>>
> >>>>>>>>>> Long.MAX
> >>>>>>>>>>
> >>>>>>>>>> out
> >>>>>>>>>>
> >>>>>>>>>> and
> >>>>>>>>>>
> >>>>>>>>>> leave the progress purely to the split readers.
> >>>>>>>>>>
> >>>>>>>>>> - For event-time alignment / split back pressure, this
> >>>>>>>>>>
> >>>>>>>>>> begs
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> question
> >>>>>>>>>>
> >>>>>>>>>> how we can avoid deadlocks that may arise when splits
> >>>>>>>>>>
> >>>>>>>>>> are
> >>>>>>>>>>
> >>>>>>>>>> suspended
> >>>>>>>>>>
> >>>>>>>>>> for
> >>>>>>>>>>
> >>>>>>>>>> event time back pressure,
> >>>>>>>>>>
> >>>>>>>>>> *(7) Batch and streaming Unification*
> >>>>>>>>>>
> >>>>>>>>>> - Functionality wise, the above design should support
> >>>>>>>>>>
> >>>>>>>>>> both
> >>>>>>>>>>
> >>>>>>>>>> - Batch often (mostly) does not care about reading "in
> >>>>>>>>>>
> >>>>>>>>>> order"
> >>>>>>>>>>
> >>>>>>>>>> and
> >>>>>>>>>>
> >>>>>>>>>> generating watermarks
> >>>>>>>>>>     --> Might use different enumerator logic that is
> >>>>>>>>>>
> >>>>>>>>>> more
> >>>>>>>>>>
> >>>>>>>>>> locality
> >>>>>>>>>>
> >>>>>>>>>> aware
> >>>>>>>>>>
> >>>>>>>>>> and ignores event time order
> >>>>>>>>>>     --> Does not generate watermarks
> >>>>>>>>>> - Would be great if bounded sources could be
> >>>>>>>>>>
> >>>>>>>>>> identified
> >>>>>>>>>>
> >>>>>>>>>> at
> >>>>>>>>>>
> >>>>>>>>>> compile
> >>>>>>>>>>
> >>>>>>>>>> time,
> >>>>>>>>>>
> >>>>>>>>>> so that "env.addBoundedSource(...)" is type safe and
> >>>>>>>>>>
> >>>>>>>>>> can
> >>>>>>>>>>
> >>>>>>>>>> return a
> >>>>>>>>>>
> >>>>>>>>>> "BoundedDataStream".
> >>>>>>>>>> - Possible to defer this discussion until later
> >>>>>>>>>>
> >>>>>>>>>> *Miscellaneous Comments*
> >>>>>>>>>>
> >>>>>>>>>> - Should the source have a TypeInformation for the
> >>>>>>>>>>
> >>>>>>>>>> produced
> >>>>>>>>>>
> >>>>>>>>>> type,
> >>>>>>>>>>
> >>>>>>>>>> instead
> >>>>>>>>>>
> >>>>>>>>>> of a serializer? We need a type information in the
> >>>>>>>>>>
> >>>>>>>>>> stream
> >>>>>>>>>>
> >>>>>>>>>> anyways, and
> >>>>>>>>>>
> >>>>>>>>>> can
> >>>>>>>>>>
> >>>>>>>>>> derive the serializer from that. Plus, creating the
> >>>>>>>>>>
> >>>>>>>>>> serializer
> >>>>>>>>>>
> >>>>>>>>>> should
> >>>>>>>>>>
> >>>>>>>>>> respect the ExecutionConfig.
> >>>>>>>>>>
> >>>>>>>>>> - The TypeSerializer interface is very powerful but
> >>>>>>>>>>
> >>>>>>>>>> also
> >>>>>>>>>>
> >>>>>>>>>> not
> >>>>>>>>>>
> >>>>>>>>>> easy to
> >>>>>>>>>>
> >>>>>>>>>> implement. Its purpose is to handle data super
> >>>>>>>>>>
> >>>>>>>>>> efficiently,
> >>>>>>>>>>
> >>>>>>>>>> support
> >>>>>>>>>>
> >>>>>>>>>> flexible ways of evolution, etc.
> >>>>>>>>>> For metadata I would suggest to look at the
> >>>>>>>>>>
> >>>>>>>>>> SimpleVersionedSerializer
> >>>>>>>>>>
> >>>>>>>>>> instead, which is used for example for checkpoint
> >>>>>>>>>>
> >>>>>>>>>> master
> >>>>>>>>>>
> >>>>>>>>>> hooks,
> >>>>>>>>>>
> >>>>>>>>>> or for
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> streaming file sink. I think that is is a good match
> >>>>>>>>>>
> >>>>>>>>>> for
> >>>>>>>>>>
> >>>>>>>>>> cases
> >>>>>>>>>>
> >>>>>>>>>> where
> >>>>>>>>>>
> >>>>>>>>>> we
> >>>>>>>>>>
> >>>>>>>>>> do
> >>>>>>>>>>
> >>>>>>>>>> not need more than ser/deser (no copy, etc.) and don't
> >>>>>>>>>>
> >>>>>>>>>> need to
> >>>>>>>>>>
> >>>>>>>>>> push
> >>>>>>>>>>
> >>>>>>>>>> versioning out of the serialization paths for best
> >>>>>>>>>>
> >>>>>>>>>> performance
> >>>>>>>>>>
> >>>>>>>>>> (as in
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> TypeSerializer)
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
> >>>>>>>>>>
> >>>>>>>>>> [hidden email]>
> >>>>>>>>>>
> >>>>>>>>>> wrote:
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> Hi Biao,
> >>>>>>>>>>
> >>>>>>>>>> Thanks for the answer!
> >>>>>>>>>>
> >>>>>>>>>> So given the multi-threaded readers, now we have as
> >>>>>>>>>>
> >>>>>>>>>> open
> >>>>>>>>>>
> >>>>>>>>>> questions:
> >>>>>>>>>>
> >>>>>>>>>> 1) How do we let the checkpoints pass through our
> >>>>>>>>>>
> >>>>>>>>>> multi-threaded
> >>>>>>>>>>
> >>>>>>>>>> reader
> >>>>>>>>>>
> >>>>>>>>>> operator?
> >>>>>>>>>>
> >>>>>>>>>> 2) Do we have separate reader and source operators or
> >>>>>>>>>>
> >>>>>>>>>> not? In
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> strategy
> >>>>>>>>>>
> >>>>>>>>>> that has a separate source, the source operator has a
> >>>>>>>>>>
> >>>>>>>>>> parallelism of
> >>>>>>>>>>
> >>>>>>>>>> 1
> >>>>>>>>>>
> >>>>>>>>>> and
> >>>>>>>>>>
> >>>>>>>>>> is responsible for split recovery only.
> >>>>>>>>>>
> >>>>>>>>>> For the first one, given also the constraints
> >>>>>>>>>>
> >>>>>>>>>> (blocking,
> >>>>>>>>>>
> >>>>>>>>>> finite
> >>>>>>>>>>
> >>>>>>>>>> queues,
> >>>>>>>>>>
> >>>>>>>>>> etc), I do not have an answer yet.
> >>>>>>>>>>
> >>>>>>>>>> For the 2nd, I think that we should go with separate
> >>>>>>>>>>
> >>>>>>>>>> operators
> >>>>>>>>>>
> >>>>>>>>>> for
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> source and the readers, for the following reasons:
> >>>>>>>>>>
> >>>>>>>>>> 1) This is more aligned with a potential future
> >>>>>>>>>>
> >>>>>>>>>> improvement
> >>>>>>>>>>
> >>>>>>>>>> where the
> >>>>>>>>>>
> >>>>>>>>>> split
> >>>>>>>>>>
> >>>>>>>>>> discovery becomes a responsibility of the JobManager
> >>>>>>>>>>
> >>>>>>>>>> and
> >>>>>>>>>>
> >>>>>>>>>> readers are
> >>>>>>>>>>
> >>>>>>>>>> pooling more work from the JM.
> >>>>>>>>>>
> >>>>>>>>>> 2) The source is going to be the "single point of
> >>>>>>>>>>
> >>>>>>>>>> truth".
> >>>>>>>>>>
> >>>>>>>>>> It
> >>>>>>>>>>
> >>>>>>>>>> will
> >>>>>>>>>>
> >>>>>>>>>> know
> >>>>>>>>>>
> >>>>>>>>>> what
> >>>>>>>>>>
> >>>>>>>>>> has been processed and what not. If the source and the
> >>>>>>>>>>
> >>>>>>>>>> readers
> >>>>>>>>>>
> >>>>>>>>>> are a
> >>>>>>>>>>
> >>>>>>>>>> single
> >>>>>>>>>>
> >>>>>>>>>> operator with parallelism > 1, or in general, if the
> >>>>>>>>>>
> >>>>>>>>>> split
> >>>>>>>>>>
> >>>>>>>>>> discovery
> >>>>>>>>>>
> >>>>>>>>>> is
> >>>>>>>>>>
> >>>>>>>>>> done by each task individually, then:
> >>>>>>>>>>    i) we have to have a deterministic scheme for each
> >>>>>>>>>>
> >>>>>>>>>> reader to
> >>>>>>>>>>
> >>>>>>>>>> assign
> >>>>>>>>>>
> >>>>>>>>>> splits to itself (e.g. mod subtaskId). This is not
> >>>>>>>>>>
> >>>>>>>>>> necessarily
> >>>>>>>>>>
> >>>>>>>>>> trivial
> >>>>>>>>>>
> >>>>>>>>>> for
> >>>>>>>>>>
> >>>>>>>>>> all sources.
> >>>>>>>>>>    ii) each reader would have to keep a copy of all its
> >>>>>>>>>>
> >>>>>>>>>> processed
> >>>>>>>>>>
> >>>>>>>>>> slpits
> >>>>>>>>>>
> >>>>>>>>>>    iii) the state has to be a union state with a
> >>>>>>>>>>
> >>>>>>>>>> non-trivial
> >>>>>>>>>>
> >>>>>>>>>> merging
> >>>>>>>>>>
> >>>>>>>>>> logic
> >>>>>>>>>>
> >>>>>>>>>> in order to support rescaling.
> >>>>>>>>>>
> >>>>>>>>>> Two additional points that you raised above:
> >>>>>>>>>>
> >>>>>>>>>> i) The point that you raised that we need to keep all
> >>>>>>>>>>
> >>>>>>>>>> splits
> >>>>>>>>>>
> >>>>>>>>>> (processed
> >>>>>>>>>>
> >>>>>>>>>> and
> >>>>>>>>>>
> >>>>>>>>>> not-processed) I think is a bit of a strong
> >>>>>>>>>>
> >>>>>>>>>> requirement.
> >>>>>>>>>>
> >>>>>>>>>> This
> >>>>>>>>>>
> >>>>>>>>>> would
> >>>>>>>>>>
> >>>>>>>>>> imply
> >>>>>>>>>>
> >>>>>>>>>> that for infinite sources the state will grow
> >>>>>>>>>>
> >>>>>>>>>> indefinitely.
> >>>>>>>>>>
> >>>>>>>>>> This is
> >>>>>>>>>>
> >>>>>>>>>> problem
> >>>>>>>>>>
> >>>>>>>>>> is even more pronounced if we do not have a single
> >>>>>>>>>>
> >>>>>>>>>> source
> >>>>>>>>>>
> >>>>>>>>>> that
> >>>>>>>>>>
> >>>>>>>>>> assigns
> >>>>>>>>>>
> >>>>>>>>>> splits to readers, as each reader will have its own
> >>>>>>>>>>
> >>>>>>>>>> copy
> >>>>>>>>>>
> >>>>>>>>>> of
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> state.
> >>>>>>>>>>
> >>>>>>>>>> ii) it is true that for finite sources we need to
> >>>>>>>>>>
> >>>>>>>>>> somehow
> >>>>>>>>>>
> >>>>>>>>>> not
> >>>>>>>>>>
> >>>>>>>>>> close
> >>>>>>>>>>
> >>>>>>>>>> the
> >>>>>>>>>>
> >>>>>>>>>> readers when the source/split discoverer finishes. The
> >>>>>>>>>> ContinuousFileReaderOperator has a work-around for
> >>>>>>>>>>
> >>>>>>>>>> that.
> >>>>>>>>>>
> >>>>>>>>>> It is
> >>>>>>>>>>
> >>>>>>>>>> not
> >>>>>>>>>>
> >>>>>>>>>> elegant,
> >>>>>>>>>>
> >>>>>>>>>> and checkpoints are not emitted after closing the
> >>>>>>>>>>
> >>>>>>>>>> source,
> >>>>>>>>>>
> >>>>>>>>>> but
> >>>>>>>>>>
> >>>>>>>>>> this, I
> >>>>>>>>>>
> >>>>>>>>>> believe, is a bigger problem which requires more
> >>>>>>>>>>
> >>>>>>>>>> changes
> >>>>>>>>>>
> >>>>>>>>>> than
> >>>>>>>>>>
> >>>>>>>>>> just
> >>>>>>>>>>
> >>>>>>>>>> refactoring the source interface.
> >>>>>>>>>>
> >>>>>>>>>> Cheers,
> >>>>>>>>>> Kostas
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> --
> >>>>>>>>>> Best, Jingsong Lee
> >>>>>>>>
> >>>>>>>>
> >>>>>>>
> >>>>>>
> >>>>>>
> >>>>>> --
> >>>>>> Best, Jingsong Lee
> >>>>>>
> >>>>>
> >>>>
> >>>>
> >>>
> >>
> >
>
>

[Becket Qin]

I had an offline chat with Jark, and here are some more thoughts:

1. From SQL perspective, BOUNDED source leads to the batch execution mode,
UNBOUNDED source leads to the streaming execution mode.
2. The semantic of UNBOUNDED source is may or may not stop. The semantic of
BOUNDED source is will stop.
3. The semantic of DataStream is may or may not terminate. The semantic of
BoundedDataStream is will terminate.

Given that, option 3 seems a better option because:
1. SQL already has strict binding between Boundedness and execution mode.
Letting DataStream be consistent would be good.
2. The semantic of UNBOUNDED source is exactly the same as DataStream. So
we should avoid breaking such semantic, i.e. turning some DataStream from
"may or may not terminate" to "will terminate".

For case where users want BOUNDED-streaming combination, they can simply
use an UNBOUNDED source that stops at some point. We can even provide a
simple wrapper to wrap a BOUNDED source as an UNBOUNDED source if that
helps. But API wise, option 3 seems telling a pretty good whole story.

Thanks,

Jiangjie (Becket) Qin




On Thu, Dec 19, 2019 at 10:30 PM Becket Qin <[hidden email]> wrote:

> Hi Timo,
>
> Bounded is just a special case of unbounded and every bounded source can
>> also be treated as an unbounded source. This would unify the API if
>> people don't need a bounded operation.
>
>
> With option 3 users can still get a unified API with something like below:
>
> DataStream boundedStream = env.boundedSource(boundedSource);
> DataStream unboundedStream = env.source(unboundedSource);
>
> So in both cases, users can still use a unified DataStream without
> touching the bounded stream only methods.
> By "unify the API if people don't need the bounded operation". Do you
> expect a DataStream with a Bounded source to have the batch operators and
> scheduler settings as well?
>
>
> If we allow DataStream from BOUNDED source, we will essentially pick "*modified
> option 2*".
>
> // The source is either bounded or unbounded, but only unbounded
>> operations could be performed on the returned DataStream.
>> DataStream<Type> dataStream = env.source(someSource);
>
>
>> // The source must be a bounded source, otherwise exception is thrown.
>> BoundedDataStream<Type> boundedDataStream =
>> env.boundedSource(boundedSource);
>
>
>
> // Add the following method to DataStream
>
> Boundedness DataStream#getBoundedness();
>
>
> From pure logical perspective, Boundedness and runtime settings
> (Stream/Batch) are two orthogonal dimensions. And are specified in the
> following way.
>
> *Boundedness* - defined by the source: BOUNDED / UNBOUNDED.
> *Running mode* - defined by the API class: DataStream (Streaming mode) /
> BoundedDataStream (batch mode).
>
> Excluding the UNBOUNDED-batch combination, the "*modified option 2"*
> covers the rest three combination. Compared with "*modified option 2*",
> the main benefit of option 3 is its simplicity and clearness, by tying
> boundedness to running mode and giving up BOUNDED-streaming combination.
>
> Just to be clear, I am fine with either option. But I would like to
> understand a bit more about the bounded-streaming use case and when users
> would prefer this over bounded-batch case, and whether the added value
> justifies the additional complexity in the API. Two cases I can think of
> are:
> 1. The records in DataStream will be processed in order, while
> BoundedDataStream processes records without order guarantee.
> 2. DataStream emits intermediate results when processing a finite dataset,
> while BoundedDataStream only emit the final result. In any case, it could
> be supported by an UNBOUNDED source stopping at some point.
>
> Case 1 is actually misleading because DataStream in general doesn't really
> support in-order process.
> Case 2 seems a rare use case because the instantaneous intermediate result
> seems difficult to reason about. In any case, this can be supported by an
> UNBOUNDED source that stops at some point.
>
> Is there other use cases for bounded-streaming combination I missed? I am
> a little hesitating to put the testing requirement here because ideally I'd
> avoid having public APIs for testing purpose only. And this could be
> resolved by having a UNBOUNDED source stopping at some point as well.
>
> Sorry for the long discussion, but I would really like to make an API
> decision after knowing all the pros and cons.
>
> Thanks,
>
> Jiangjie (Becket) Qin
>
>
>
>
>
>
>
> On Thu, Dec 19, 2019 at 6:19 PM Timo Walther <[hidden email]> wrote:
>
>> Hi Becket,
>>
>> regarding *Option 3* I think we can relax the constraints for
>> env.source():
>>
>> // MySource can be bounded or unbounded
>> DataStream<Type> dataStream = env.source(mySource);
>>
>> // MySource must be bounded, otherwise throws exception.
>> BoundedDataStream<Type> boundedDataStream = env.boundedSource(mySource);
>>
>> Bounded is just a special case of unbounded and every bounded source can
>> also be treated as an unbounded source. This would unify the API if
>> people don't need a bounded operation. It also addresses Jark's concerns.
>>
>> Regards,
>> Timo
>>
>>
>> On 18.12.19 14:16, Becket Qin wrote:
>> > Hi Jark,
>> >
>> > Please see the reply below:
>> >
>> > Regarding to option#3, my concern is that if we don't support streaming
>> >> mode for bounded source,
>> >> how could we create a testing source for streaming mode? Currently,
>> all the
>> >> testing source for streaming
>> >> are bounded, so that the integration test will finish finally.
>> >
>> >
>> > An UNBOUNDED source does not mean it will never stops. It simply
>> indicates
>> > that the source *may* run forever, so the runtime needs to be prepared
>> for
>> > that, but the task may still stop at some point when it hits some
>> > source-specific condition. So an UNBOUNDED testing source can still
>> stop at
>> > some point if needed.
>> >
>> > Regarding to Source#getRecordOrder(), could we have a implicit contract
>> >> that unbounded source should
>> >> already read in order (i.e. reading partitions in parallel), for
>> bounded
>> >> source the order is not mandatory.
>> >
>> >
>> >
>> >> This is also the behaviors of the current sources.
>> >
>> > 1) a source can't guarantee it reads in strict order, because the
>> producer
>> >> may produce data not in order.
>> >> 2) *Bounded-StrictOrder* is not necessary, because batch can reorder
>> data.
>> >
>> >
>> > It is true that sometimes the source cannot guarantee the record order,
>> but
>> > sometimes it can. Right now, even for stream processing, there is no
>> > processing order guarantee. For example, a join operator may emit a
>> later
>> > record which successfully found a join match earlier.
>> > Event order is one of the most important requirements for event
>> processing,
>> > a clear order guarantee would be necessary. That said, I agree that
>> right
>> > now even if the sources provide the record order requirement, the
>> runtime
>> > is not able to guarantee that out of the box. So I am OK if we add the
>> > record order to the Source later. But we should avoid misleading users
>> to
>> > make them think the processing order is guaranteed when using the
>> unbounded
>> > runtime.
>> >
>> > Thanks,
>> >
>> > Jiangjie (Becket) Qin
>> >
>> > On Wed, Dec 18, 2019 at 10:29 AM Jark Wu <[hidden email]> wrote:
>> >
>> >> Hi Becket,
>> >>
>> >> That's great we have reached a consensus on Source#getBoundedness().
>> >>
>> >> Regarding to option#3, my concern is that if we don't support streaming
>> >> mode for bounded source,
>> >> how could we create a testing source for streaming mode? Currently,
>> all the
>> >> testing source for streaming
>> >> are bounded, so that the integration test will finish finally.
>> >>
>> >> Regarding to Source#getRecordOrder(), could we have a implicit contract
>> >> that unbounded source should
>> >> already read in order (i.e. reading partitions in parallel), for
>> bounded
>> >> source the order is not mandatory.
>> >> This is also the behaviors of the current sources.
>> >> 1) a source can't guarantee it reads in strict order, because the
>> producer
>> >> may produce data not in order.
>> >> 2) *Bounded-StrictOrder* is not necessary, because batch can reorder
>> data.
>> >>
>> >> Best,
>> >> Jark
>> >>
>> >>
>> >>
>> >> On Tue, 17 Dec 2019 at 22:03, Becket Qin <[hidden email]> wrote:
>> >>
>> >>> Hi folks,
>> >>>
>> >>> Thanks for the comments. I am convinced that the Source API should not
>> >> take
>> >>> boundedness as a parameter after it is constructed. What Timo and
>> Dawid
>> >>> suggested sounds a reasonable solution to me. So the Source API would
>> >>> become:
>> >>>
>> >>> Source {
>> >>>      Boundedness getBoundedness();
>> >>> }
>> >>>
>> >>> Assuming the above Source API, in addition to the two options
>> mentioned
>> >> in
>> >>> earlier emails, I am thinking of another option:
>> >>>
>> >>> *Option 3:*
>> >>> // MySource must be unbounded, otherwise throws exception.
>> >>> DataStream<Type> dataStream = env.source(mySource);
>> >>>
>> >>> // MySource must be bounded, otherwise throws exception.
>> >>> BoundedDataStream<Type> boundedDataStream =
>> env.boundedSource(mySource);
>> >>>
>> >>> The pros of this API are:
>> >>>     a) It fits the requirements from Table / SQL well.
>> >>>     b) DataStream users still have type safety (option 2 only has
>> partial
>> >>> type safety).
>> >>>     c) Cristal clear boundedness from the API which makes DataStream
>> join
>> >> /
>> >>> connect easy to reason about.
>> >>> The caveats I see,
>> >>>     a) It is inconsistent with Table since Table has one unified
>> >> interface.
>> >>>     b) No streaming mode for bounded source.
>> >>>
>> >>> @Stephan Ewen <[hidden email]> @Aljoscha Krettek
>> >>> <[hidden email]> what do you think of the approach?
>> >>>
>> >>>
>> >>> Orthogonal to the above API, I am wondering whether boundedness is the
>> >> only
>> >>> dimension needed to describe the characteristic of the Source
>> behavior.
>> >> We
>> >>> may also need to have another dimension of *record order*.
>> >>>
>> >>> For example, when a file source is reading from a directory with
>> bounded
>> >>> records, it may have two ways to read.
>> >>> 1. Read files in parallel.
>> >>> 2. Read files in the chronological order.
>> >>> In both cases, the file source is a Bounded Source. However, the
>> >> processing
>> >>> requirement for downstream may be different. In the first case, the
>> >>> record processing and result emitting order does not matter, e.g. word
>> >>> count. In the second case, the records may have to be processed in the
>> >>> order they were read, e.g. change log processing.
>> >>>
>> >>> If the Source only has a getBoundedness() method, the downstream
>> >> processors
>> >>> would not know whether the records emitted from the Source should be
>> >>> processed in order or not. So combining the boundedness and record
>> order,
>> >>> we will have four scenarios:
>> >>>
>> >>> *Bounded-StrictOrder*:     A segment of change log.
>> >>> *Bounded-Random*:          Batch Word Count.
>> >>> *Unbounded-StrictOrder*: An infinite change log.
>> >>> *Unbounded-Random*:     Streaming Word Count.
>> >>>
>> >>> Option 2 mentioned in the previous email was kind of trying to handle
>> the
>> >>> Bounded-StrictOrder case by creating a DataStream from a bounded
>> source,
>> >>> which actually does not work.
>> >>> It looks that we do not have strict order support in some operators at
>> >> this
>> >>> point, e.g. join. But we may still want to add the semantic to the
>> Source
>> >>> first so later on we don't need to change all the source
>> implementations,
>> >>> especially given that many of them will be implemented by 3rd party.
>> >>>
>> >>> Given that, we need another dimension of *Record Order* in the Source.
>> >> More
>> >>> specifically, the API would become:
>> >>>
>> >>> Source {
>> >>>      Boundedness getBoundedness();
>> >>>      RecordOrder getRecordOrder();
>> >>> }
>> >>>
>> >>> public enum RecordOrder {
>> >>>      /** The record in the DataStream must be processed in its strict
>> >> order
>> >>> for correctness. */
>> >>>      STRICT,
>> >>>      /** The record in the DataStream can be processed in arbitrary
>> order.
>> >>> */
>> >>>      RANDOM;
>> >>> }
>> >>>
>> >>> Any thoughts?
>> >>>
>> >>> Thanks,
>> >>>
>> >>> Jiangjie (Becket) Qin
>> >>>
>> >>> On Tue, Dec 17, 2019 at 3:44 PM Timo Walther <[hidden email]>
>> wrote:
>> >>>
>> >>>> Hi Becket,
>> >>>>
>> >>>> I completely agree with Dawid's suggestion. The information about the
>> >>>> boundedness should come out of the source. Because most of the
>> >> streaming
>> >>>> sources can be made bounded based on some connector specific
>> criterion.
>> >>>> In Kafka, it would be an end offset or end timestamp but in any case
>> >>>> having just a env.boundedSource() is not enough because parameters
>> for
>> >>>> making the source bounded are missing.
>> >>>>
>> >>>> I suggest to have a simple `isBounded(): Boolean` flag in every
>> source
>> >>>> that might be influenced by a connector builder as Dawid mentioned.
>> >>>>
>> >>>> For type safety during programming, we can still go with *Final state
>> >>>> 1*. By having a env.source() vs env.boundedSource(). The latter would
>> >>>> just enforce that the boolean flag is set to `true` and could make
>> >>>> bounded operations available (if we need that actually).
>> >>>>
>> >>>> However, I don't think that we should start making a unified Table
>> API
>> >>>> ununified again. Boundedness is an optimization property. Every
>> bounded
>> >>>> operation can also executed in an unbounded way using
>> >> updates/retraction
>> >>>> or watermarks.
>> >>>>
>> >>>> Regards,
>> >>>> Timo
>> >>>>
>> >>>>
>> >>>> On 15.12.19 14:22, Becket Qin wrote:
>> >>>>> Hi Dawid and Jark,
>> >>>>>
>> >>>>> I think the discussion ultimately boils down to the question that
>> >> which
>> >>>> one
>> >>>>> of the following two final states do we want? Once we make this
>> >>> decision,
>> >>>>> everything else can be naturally derived.
>> >>>>>
>> >>>>> *Final state 1*: Separate API for bounded / unbounded DataStream &
>> >>> Table.
>> >>>>> That means any code users write will be valid at the point when they
>> >>>> write
>> >>>>> the code. This is similar to having type safety check at programming
>> >>>> time.
>> >>>>> For example,
>> >>>>>
>> >>>>> BoundedDataStream extends DataStream {
>> >>>>> // Operations only available for bounded data.
>> >>>>> BoundedDataStream sort(...);
>> >>>>>
>> >>>>> // Interaction with another BoundedStream returns a Bounded stream.
>> >>>>> BoundedJoinedDataStream join(BoundedDataStream other)
>> >>>>>
>> >>>>> // Interaction with another unbounded stream returns an unbounded
>> >>> stream.
>> >>>>> JoinedDataStream join(DataStream other)
>> >>>>> }
>> >>>>>
>> >>>>> BoundedTable extends Table {
>> >>>>>     // Bounded only operation.
>> >>>>> BoundedTable sort(...);
>> >>>>>
>> >>>>> // Interaction with another BoundedTable returns a BoundedTable.
>> >>>>> BoundedTable join(BoundedTable other)
>> >>>>>
>> >>>>> // Interaction with another unbounded table returns an unbounded
>> >> table.
>> >>>>> Table join(Table other)
>> >>>>> }
>> >>>>>
>> >>>>> *Final state 2*: One unified API for bounded / unbounded DataStream
>> /
>> >>>>> Table.
>> >>>>> That unified API may throw exception at DAG compilation time if an
>> >>>> invalid
>> >>>>> operation is tried. This is what Table API currently follows.
>> >>>>>
>> >>>>> DataStream {
>> >>>>> // Throws exception if the DataStream is unbounded.
>> >>>>> DataStream sort();
>> >>>>> // Get boundedness.
>> >>>>> Boundedness getBoundedness();
>> >>>>> }
>> >>>>>
>> >>>>> Table {
>> >>>>> // Throws exception if the table has infinite rows.
>> >>>>> Table orderBy();
>> >>>>>
>> >>>>> // Get boundedness.
>> >>>>> Boundedness getBoundedness();
>> >>>>> }
>> >>>>>
>> >>>>> >From what I understand, there is no consensus so far on this
>> decision
>> >>>> yet.
>> >>>>> Whichever final state we choose, we need to make it consistent
>> across
>> >>> the
>> >>>>> entire project. We should avoid the case that Table follows one
>> final
>> >>>> state
>> >>>>> while DataStream follows another. Some arguments I am aware of from
>> >>> both
>> >>>>> sides so far are following:
>> >>>>>
>> >>>>> Arguments for final state 1:
>> >>>>> 1a) Clean API with method safety check at programming time.
>> >>>>> 1b) (Counter 2b) Although SQL does not have programming time error
>> >>>> check, SQL
>> >>>>> is not really a "programming language" per se. So SQL can be
>> >> different
>> >>>> from
>> >>>>> Table and DataStream.
>> >>>>> 1c)  Although final state 2 seems making it easier for SQL to use
>> >> given
>> >>>> it
>> >>>>> is more "config based" than "parameter based", final state 1 can
>> >>> probably
>> >>>>> also meet what SQL wants by wrapping the Source in TableSource /
>> >>>>> TableSourceFactory API if needed.
>> >>>>>
>> >>>>> Arguments for final state 2:
>> >>>>> 2a) The Source API itself seems already sort of following the
>> unified
>> >>> API
>> >>>>> pattern.
>> >>>>> 2b) There is no "programming time" method error check in SQL case,
>> so
>> >>> we
>> >>>>> cannot really achieve final state 1 across the board.
>> >>>>> 2c) It is an easier path given our current status, i.e. Table is
>> >>> already
>> >>>>> following final state 2.
>> >>>>> 2d) Users can always explicitly check the boundedness if they want
>> >> to.
>> >>>>>
>> >>>>> As I mentioned earlier, my initial thought was also to have a
>> >>>>> "configuration based" Source rather than a "parameter based" Source.
>> >> So
>> >>>> it
>> >>>>> is completely possible that I missed some important consideration or
>> >>>> design
>> >>>>> principles that we want to enforce for the project. It would be good
>> >>>>> if @Stephan
>> >>>>> Ewen <[hidden email]> and @Aljoscha Krettek <
>> >>>> [hidden email]> can
>> >>>>> also provide more thoughts on this.
>> >>>>>
>> >>>>>
>> >>>>> Re: Jingsong
>> >>>>>
>> >>>>> As you said, there are some batched system source, like parquet/orc
>> >>>> source.
>> >>>>>> Could we have the batch emit interface to improve performance? The
>> >>>> queue of
>> >>>>>> per record may cause performance degradation.
>> >>>>>
>> >>>>>
>> >>>>> The current interface does not necessarily cause performance problem
>> >>> in a
>> >>>>> multi-threading case. In fact, the base implementation allows
>> >>>> SplitReaders
>> >>>>> to add a batch <E> of records<T> to the records queue<E>, so each
>> >>> element
>> >>>>> in the records queue would be a batch <E>. In this case, when the
>> >> main
>> >>>>> thread polls records, it will take a batch <E> of records <T> from
>> >> the
>> >>>>> shared records queue and process the records <T> in a batch manner.
>> >>>>>
>> >>>>> Thanks,
>> >>>>>
>> >>>>> Jiangjie (Becket) Qin
>> >>>>>
>> >>>>> On Thu, Dec 12, 2019 at 1:29 PM Jingsong Li <[hidden email]
>> >
>> >>>> wrote:
>> >>>>>
>> >>>>>> Hi Becket,
>> >>>>>>
>> >>>>>> I also have some performance concerns too.
>> >>>>>>
>> >>>>>> If I understand correctly, SourceOutput will emit data per record
>> >> into
>> >>>> the
>> >>>>>> queue? I'm worried about the multithreading performance of this
>> >> queue.
>> >>>>>>
>> >>>>>>> One example is some batched messaging systems which only have an
>> >>> offset
>> >>>>>> for the entire batch instead of individual messages in the batch.
>> >>>>>>
>> >>>>>> As you said, there are some batched system source, like parquet/orc
>> >>>> source.
>> >>>>>> Could we have the batch emit interface to improve performance? The
>> >>>> queue of
>> >>>>>> per record may cause performance degradation.
>> >>>>>>
>> >>>>>> Best,
>> >>>>>> Jingsong Lee
>> >>>>>>
>> >>>>>> On Thu, Dec 12, 2019 at 9:15 AM Jark Wu <[hidden email]> wrote:
>> >>>>>>
>> >>>>>>> Hi Becket,
>> >>>>>>>
>> >>>>>>> I think Dawid explained things clearly and makes a lot of sense.
>> >>>>>>> I'm also in favor of #2, because #1 doesn't work for our future
>> >>> unified
>> >>>>>>> envrionment.
>> >>>>>>>
>> >>>>>>> You can see the vision in this documentation [1]. In the future,
>> we
>> >>>> would
>> >>>>>>> like to
>> >>>>>>> drop the global streaming/batch mode in SQL (i.e.
>> >>>>>>> EnvironmentSettings#inStreamingMode/inBatchMode).
>> >>>>>>> A source is bounded or unbounded once defined, so queries can be
>> >>>> inferred
>> >>>>>>> from source to run
>> >>>>>>> in streaming or batch or hybrid mode. However, in #1, we will lose
>> >>> this
>> >>>>>>> ability because the framework
>> >>>>>>> doesn't know whether the source is bounded or unbounded.
>> >>>>>>>
>> >>>>>>> Best,
>> >>>>>>> Jark
>> >>>>>>>
>> >>>>>>>
>> >>>>>>> [1]:
>> >>>>>>>
>> >>>>>>>
>> >>>>>>
>> >>>>
>> >>>
>> >>
>> https://docs.google.com/document/d/1yrKXEIRATfxHJJ0K3t6wUgXAtZq8D-XgvEnvl2uUcr0/edit#heading=h.v4ib17buma1p
>> >>>>>>>
>> >>>>>>> On Wed, 11 Dec 2019 at 20:52, Piotr Nowojski <[hidden email]
>> >
>> >>>>>> wrote:
>> >>>>>>>
>> >>>>>>>> Hi,
>> >>>>>>>>
>> >>>>>>>> Regarding the:
>> >>>>>>>>
>> >>>>>>>> Collection<E> getNextRecords()
>> >>>>>>>>
>> >>>>>>>> I’m pretty sure such design would unfortunately impact the
>> >>> performance
>> >>>>>>>> (accessing and potentially creating the collection on the hot
>> >> path).
>> >>>>>>>>
>> >>>>>>>> Also the
>> >>>>>>>>
>> >>>>>>>> InputStatus emitNext(DataOutput<T> output) throws Exception;
>> >>>>>>>> or
>> >>>>>>>> Status pollNext(SourceOutput<T> sourceOutput) throws Exception;
>> >>>>>>>>
>> >>>>>>>> Gives us some opportunities in the future, to allow Source hot
>> >>> looping
>> >>>>>>>> inside, until it receives some signal “please exit because of
>> some
>> >>>>>>> reasons”
>> >>>>>>>> (output collector could return such hint upon collecting the
>> >>> result).
>> >>>>>> But
>> >>>>>>>> that’s another topic outside of this FLIP’s scope.
>> >>>>>>>>
>> >>>>>>>> Piotrek
>> >>>>>>>>
>> >>>>>>>>> On 11 Dec 2019, at 10:41, Till Rohrmann <[hidden email]>
>> >>>>>> wrote:
>> >>>>>>>>>
>> >>>>>>>>> Hi Becket,
>> >>>>>>>>>
>> >>>>>>>>> quick clarification from my side because I think you
>> >> misunderstood
>> >>> my
>> >>>>>>>>> question. I did not suggest to let the SourceReader return only
>> a
>> >>>>>>> single
>> >>>>>>>>> record at a time when calling getNextRecords. As the return type
>> >>>>>>>> indicates,
>> >>>>>>>>> the method can return an arbitrary number of records.
>> >>>>>>>>>
>> >>>>>>>>> Cheers,
>> >>>>>>>>> Till
>> >>>>>>>>>
>> >>>>>>>>> On Wed, Dec 11, 2019 at 10:13 AM Dawid Wysakowicz <
>> >>>>>>>> [hidden email] <mailto:[hidden email]>>
>> >>>>>>>>> wrote:
>> >>>>>>>>>
>> >>>>>>>>>> Hi Becket,
>> >>>>>>>>>>
>> >>>>>>>>>> Issue #1 - Design of Source interface
>> >>>>>>>>>>
>> >>>>>>>>>> I mentioned the lack of a method like
>> >>>>>>>> Source#createEnumerator(Boundedness
>> >>>>>>>>>> boundedness, SplitEnumeratorContext context), because without
>> >> the
>> >>>>>>>> current
>> >>>>>>>>>> proposal is not complete/does not work.
>> >>>>>>>>>>
>> >>>>>>>>>> If we say that boundedness is an intrinsic property of a source
>> >>> imo
>> >>>>>> we
>> >>>>>>>>>> don't need the Source#createEnumerator(Boundedness boundedness,
>> >>>>>>>>>> SplitEnumeratorContext context) method.
>> >>>>>>>>>>
>> >>>>>>>>>> Assuming a source from my previous example:
>> >>>>>>>>>>
>> >>>>>>>>>> Source source = KafkaSource.builder()
>> >>>>>>>>>>    ...
>> >>>>>>>>>>    .untilTimestamp(...)
>> >>>>>>>>>>    .build()
>> >>>>>>>>>>
>> >>>>>>>>>> Would the enumerator differ if created like
>> >>>>>>>>>> source.createEnumerator(CONTINUOUS_UNBOUNDED, ...) vs source
>> >>>>>>>>>> .createEnumerator(BOUNDED, ...)? I know I am repeating myself,
>> >> but
>> >>>>>>> this
>> >>>>>>>> is
>> >>>>>>>>>> the part that my opinion differ the most from the current
>> >>> proposal.
>> >>>>>> I
>> >>>>>>>>>> really think it should always be the source that tells if it is
>> >>>>>>> bounded
>> >>>>>>>> or
>> >>>>>>>>>> not. In the current proposal methods
>> >> continousSource/boundedSource
>> >>>>>>>> somewhat
>> >>>>>>>>>> reconfigure the source, which I think is misleading.
>> >>>>>>>>>>
>> >>>>>>>>>> I think a call like:
>> >>>>>>>>>>
>> >>>>>>>>>> Source source = KafkaSource.builder()
>> >>>>>>>>>>    ...
>> >>>>>>>>>>    .readContinously() / readUntilLatestOffset() /
>> >>> readUntilTimestamp
>> >>>> /
>> >>>>>>>> readUntilOffsets / ...
>> >>>>>>>>>>    .build()
>> >>>>>>>>>>
>> >>>>>>>>>> is way cleaner (and expressive) than
>> >>>>>>>>>>
>> >>>>>>>>>> Source source = KafkaSource.builder()
>> >>>>>>>>>>    ...
>> >>>>>>>>>>    .build()
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> env.continousSource(source) // which actually underneath would
>> >>> call
>> >>>>>>>> createEnumerator(CONTINUOUS, ctx) which would be equivalent to
>> >>>>>>>> source.readContinously().createEnumerator(ctx)
>> >>>>>>>>>> // or
>> >>>>>>>>>> env.boundedSource(source) // which actually underneath would
>> >> call
>> >>>>>>>> createEnumerator(BOUNDED, ctx) which would be equivalent to
>> >>>>>>>> source.readUntilLatestOffset().createEnumerator(ctx)
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> Sorry for the comparison, but to me it seems there is too much
>> >>> magic
>> >>>>>>>>>> happening underneath those two calls.
>> >>>>>>>>>>
>> >>>>>>>>>> I really believe the Source interface should have
>> getBoundedness
>> >>>>>>> method
>> >>>>>>>>>> instead of (supportBoundedness) + createEnumerator(Boundedness,
>> >>> ...)
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> Issue #2 - Design of
>> >>>>>>>>>>
>> ExecutionEnvironment#source()/continuousSource()/boundedSource()
>> >>>>>>>>>>
>> >>>>>>>>>> As you might have guessed I am slightly in favor of option #2
>> >>>>>>> modified.
>> >>>>>>>>>> Yes I am aware every step of the dag would have to be able to
>> >> say
>> >>> if
>> >>>>>>> it
>> >>>>>>>> is
>> >>>>>>>>>> bounded or not. I have a feeling it would be easier to express
>> >>> cross
>> >>>>>>>>>> bounded/unbounded operations, but I must admit I have not
>> >> thought
>> >>> it
>> >>>>>>>>>> through thoroughly, In the spirit of batch is just a special
>> >> case
>> >>> of
>> >>>>>>>>>> streaming I thought BoundedStream would extend from DataStream.
>> >>>>>>> Correct
>> >>>>>>>> me
>> >>>>>>>>>> if I am wrong. In such a setup the cross bounded/unbounded
>> >>> operation
>> >>>>>>>> could
>> >>>>>>>>>> be expressed quite easily I think:
>> >>>>>>>>>>
>> >>>>>>>>>> DataStream {
>> >>>>>>>>>>    DataStream join(DataStream, ...); // we could not really
>> tell
>> >> if
>> >>>>>> the
>> >>>>>>>> result is bounded or not, but because bounded stream is a special
>> >>> case
>> >>>>>> of
>> >>>>>>>> unbounded the API object is correct, irrespective if the left or
>> >>> right
>> >>>>>>> side
>> >>>>>>>> of the join is bounded
>> >>>>>>>>>> }
>> >>>>>>>>>>
>> >>>>>>>>>> BoundedStream extends DataStream {
>> >>>>>>>>>>    BoundedStream join(BoundedStream, ...); // only if both
>> sides
>> >>> are
>> >>>>>>>> bounded the result can be bounded as well. However we do have
>> >> access
>> >>>> to
>> >>>>>>> the
>> >>>>>>>> DataStream#join here, so you can still join with a DataStream
>> >>>>>>>>>> }
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> On the other hand I also see benefits of two completely
>> >> disjointed
>> >>>>>>> APIs,
>> >>>>>>>>>> as we could prohibit some streaming calls in the bounded API. I
>> >>>>>> can't
>> >>>>>>>> think
>> >>>>>>>>>> of any unbounded operators that could not be implemented for
>> >>> bounded
>> >>>>>>>> stream.
>> >>>>>>>>>>
>> >>>>>>>>>> Besides I think we both agree we don't like the method:
>> >>>>>>>>>>
>> >>>>>>>>>> DataStream boundedStream(Source)
>> >>>>>>>>>>
>> >>>>>>>>>> suggested in the current state of the FLIP. Do we ? :)
>> >>>>>>>>>>
>> >>>>>>>>>> Best,
>> >>>>>>>>>>
>> >>>>>>>>>> Dawid
>> >>>>>>>>>>
>> >>>>>>>>>> On 10/12/2019 18:57, Becket Qin wrote:
>> >>>>>>>>>>
>> >>>>>>>>>> Hi folks,
>> >>>>>>>>>>
>> >>>>>>>>>> Thanks for the discussion, great feedback. Also thanks Dawid
>> for
>> >>> the
>> >>>>>>>>>> explanation, it is much clearer now.
>> >>>>>>>>>>
>> >>>>>>>>>> One thing that is indeed missing from the FLIP is how the
>> >>>>>> boundedness
>> >>>>>>> is
>> >>>>>>>>>> passed to the Source implementation. So the API should be
>> >>>>>>>>>> Source#createEnumerator(Boundedness boundedness,
>> >>>>>>> SplitEnumeratorContext
>> >>>>>>>>>> context)
>> >>>>>>>>>> And we can probably remove the
>> >>> Source#supportBoundedness(Boundedness
>> >>>>>>>>>> boundedness) method.
>> >>>>>>>>>>
>> >>>>>>>>>> Assuming we have that, we are essentially choosing from one of
>> >> the
>> >>>>>>>>>> following two options:
>> >>>>>>>>>>
>> >>>>>>>>>> Option 1:
>> >>>>>>>>>> // The source is continuous source, and only unbounded
>> >> operations
>> >>>>>> can
>> >>>>>>> be
>> >>>>>>>>>> performed.
>> >>>>>>>>>> DataStream<Type> datastream = env.continuousSource(someSource);
>> >>>>>>>>>>
>> >>>>>>>>>> // The source is bounded source, both bounded and unbounded
>> >>>>>> operations
>> >>>>>>>> can
>> >>>>>>>>>> be performed.
>> >>>>>>>>>> BoundedDataStream<Type> boundedDataStream =
>> >>>>>>>> env.boundedSource(someSource);
>> >>>>>>>>>>
>> >>>>>>>>>>    - Pros:
>> >>>>>>>>>>         a) explicit boundary between bounded / unbounded
>> streams,
>> >>> it
>> >>>>>> is
>> >>>>>>>>>> quite simple and clear to the users.
>> >>>>>>>>>>    - Cons:
>> >>>>>>>>>>         a) For applications that do not involve bounded
>> >> operations,
>> >>>>>> they
>> >>>>>>>>>> still have to call different API to distinguish bounded /
>> >>> unbounded
>> >>>>>>>> streams.
>> >>>>>>>>>>         b) No support for bounded stream to run in a streaming
>> >>>> runtime
>> >>>>>>>>>> setting, i.e. scheduling and operators behaviors.
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> Option 2:
>> >>>>>>>>>> // The source is either bounded or unbounded, but only
>> unbounded
>> >>>>>>>> operations
>> >>>>>>>>>> could be performed on the returned DataStream.
>> >>>>>>>>>> DataStream<Type> dataStream = env.source(someSource);
>> >>>>>>>>>>
>> >>>>>>>>>> // The source must be a bounded source, otherwise exception is
>> >>>>>> thrown.
>> >>>>>>>>>> BoundedDataStream<Type> boundedDataStream =
>> >>>>>>>>>> env.boundedSource(boundedSource);
>> >>>>>>>>>>
>> >>>>>>>>>> The pros and cons are exactly the opposite of option 1.
>> >>>>>>>>>>    - Pros:
>> >>>>>>>>>>         a) For applications that do not involve bounded
>> >> operations,
>> >>>>>> they
>> >>>>>>>>>> still have to call different API to distinguish bounded /
>> >>> unbounded
>> >>>>>>>> streams.
>> >>>>>>>>>>         b) Support for bounded stream to run in a streaming
>> >> runtime
>> >>>>>>>> setting,
>> >>>>>>>>>> i.e. scheduling and operators behaviors.
>> >>>>>>>>>>    - Cons:
>> >>>>>>>>>>         a) Bounded / unbounded streams are kind of mixed, i.e.
>> >>> given
>> >>>> a
>> >>>>>>>>>> DataStream, it is not clear whether it is bounded or not,
>> unless
>> >>> you
>> >>>>>>>> have
>> >>>>>>>>>> the access to its source.
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> If we only think from the Source API perspective, option 2
>> >> seems a
>> >>>>>>>> better
>> >>>>>>>>>> choice because functionality wise it is a superset of option 1,
>> >> at
>> >>>>>> the
>> >>>>>>>> cost
>> >>>>>>>>>> of some seemingly acceptable ambiguity in the DataStream API.
>> >>>>>>>>>> But if we look at the DataStream API as a whole, option 1 seems
>> >> a
>> >>>>>>>> clearer
>> >>>>>>>>>> choice. For example, some times a library may have to know
>> >>> whether a
>> >>>>>>>>>> certain task will finish or not. And it would be difficult to
>> >> tell
>> >>>>>> if
>> >>>>>>>> the
>> >>>>>>>>>> input is a DataStream, unless additional information is
>> provided
>> >>> all
>> >>>>>>> the
>> >>>>>>>>>> way from the Source. One possible solution is to have a
>> >> *modified
>> >>>>>>>> option 2*
>> >>>>>>>>>> which adds a method to the DataStream API to indicate
>> >> boundedness,
>> >>>>>>> such
>> >>>>>>>> as
>> >>>>>>>>>> getBoundedness(). It would solve the problem with a potential
>> >>>>>>> confusion
>> >>>>>>>> of
>> >>>>>>>>>> what is difference between a DataStream with
>> >> getBoundedness()=true
>> >>>>>>> and a
>> >>>>>>>>>> BoundedDataStream. But that seems not super difficult to
>> >> explain.
>> >>>>>>>>>>
>> >>>>>>>>>> So from API's perspective, I don't have a strong opinion
>> between
>> >>>>>>>> *option 1*
>> >>>>>>>>>> and *modified option 2. *I like the cleanness of option 1, but
>> >>>>>>> modified
>> >>>>>>>>>> option 2 would be more attractive if we have concrete use case
>> >> for
>> >>>>>> the
>> >>>>>>>>>> "Bounded stream with unbounded streaming runtime settings".
>> >>>>>>>>>>
>> >>>>>>>>>> Re: Till
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> Maybe this has already been asked before but I was wondering
>> why
>> >>> the
>> >>>>>>>>>> SourceReader interface has the method pollNext which hands the
>> >>>>>>>>>> responsibility of outputting elements to the SourceReader
>> >>>>>>>> implementation?
>> >>>>>>>>>> Has this been done for backwards compatibility reasons with the
>> >>> old
>> >>>>>>>> source
>> >>>>>>>>>> interface? If not, then one could define a Collection<E>
>> >>>>>>>> getNextRecords()
>> >>>>>>>>>> method which returns the currently retrieved records and then
>> >> the
>> >>>>>>> caller
>> >>>>>>>>>> emits them outside of the SourceReader. That way the interface
>> >>> would
>> >>>>>>> not
>> >>>>>>>>>> allow to implement an outputting loop where we never hand back
>> >>>>>> control
>> >>>>>>>> to
>> >>>>>>>>>> the caller. At the moment, this contract can be easily broken
>> >> and
>> >>> is
>> >>>>>>>> only
>> >>>>>>>>>> mentioned loosely in the JavaDocs.
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> The primary reason we handover the SourceOutput to the
>> >>> SourceReader
>> >>>>>> is
>> >>>>>>>>>> because sometimes it is difficult for a SourceReader to emit
>> one
>> >>>>>>> record
>> >>>>>>>> at
>> >>>>>>>>>> a time. One example is some batched messaging systems which
>> only
>> >>>>>> have
>> >>>>>>> an
>> >>>>>>>>>> offset for the entire batch instead of individual messages in
>> >> the
>> >>>>>>>> batch. In
>> >>>>>>>>>> that case, returning one record at a time would leave the
>> >>>>>> SourceReader
>> >>>>>>>> in
>> >>>>>>>>>> an uncheckpointable state because they can only checkpoint at
>> >> the
>> >>>>>>> batch
>> >>>>>>>>>> boundaries.
>> >>>>>>>>>>
>> >>>>>>>>>> Thanks,
>> >>>>>>>>>>
>> >>>>>>>>>> Jiangjie (Becket) Qin
>> >>>>>>>>>>
>> >>>>>>>>>> On Tue, Dec 10, 2019 at 5:33 PM Till Rohrmann <
>> >>> [hidden email]
>> >>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
>> >>>>>>>> [hidden email]>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> Hi everyone,
>> >>>>>>>>>>
>> >>>>>>>>>> thanks for drafting this FLIP. It reads very well.
>> >>>>>>>>>>
>> >>>>>>>>>> Concerning Dawid's proposal, I tend to agree. The boundedness
>> >>> could
>> >>>>>>> come
>> >>>>>>>>>> from the source and tell the system how to treat the operator
>> >>>>>>>> (scheduling
>> >>>>>>>>>> wise). From a user's perspective it should be fine to get back
>> a
>> >>>>>>>> DataStream
>> >>>>>>>>>> when calling env.source(boundedSource) if he does not need
>> >> special
>> >>>>>>>>>> operations defined on a BoundedDataStream. If he needs this,
>> >> then
>> >>>>>> one
>> >>>>>>>> could
>> >>>>>>>>>> use the method BoundedDataStream
>> >> env.boundedSource(boundedSource).
>> >>>>>>>>>>
>> >>>>>>>>>> If possible, we could enforce the proper usage of
>> >>>>>> env.boundedSource()
>> >>>>>>> by
>> >>>>>>>>>> introducing a BoundedSource type so that one cannot pass an
>> >>>>>>>>>> unbounded source to it. That way users would not be able to
>> >> shoot
>> >>>>>>>>>> themselves in the foot.
>> >>>>>>>>>>
>> >>>>>>>>>> Maybe this has already been asked before but I was wondering
>> why
>> >>> the
>> >>>>>>>>>> SourceReader interface has the method pollNext which hands the
>> >>>>>>>>>> responsibility of outputting elements to the SourceReader
>> >>>>>>>> implementation?
>> >>>>>>>>>> Has this been done for backwards compatibility reasons with the
>> >>> old
>> >>>>>>>> source
>> >>>>>>>>>> interface? If not, then one could define a Collection<E>
>> >>>>>>>> getNextRecords()
>> >>>>>>>>>> method which returns the currently retrieved records and then
>> >> the
>> >>>>>>> caller
>> >>>>>>>>>> emits them outside of the SourceReader. That way the interface
>> >>> would
>> >>>>>>> not
>> >>>>>>>>>> allow to implement an outputting loop where we never hand back
>> >>>>>> control
>> >>>>>>>> to
>> >>>>>>>>>> the caller. At the moment, this contract can be easily broken
>> >> and
>> >>> is
>> >>>>>>>> only
>> >>>>>>>>>> mentioned loosely in the JavaDocs.
>> >>>>>>>>>>
>> >>>>>>>>>> Cheers,
>> >>>>>>>>>> Till
>> >>>>>>>>>>
>> >>>>>>>>>> On Tue, Dec 10, 2019 at 7:49 AM Jingsong Li <
>> >>> [hidden email]
>> >>>>>>>> <mailto:[hidden email]>> <[hidden email]
>> <mailto:
>> >>>>>>>> [hidden email]>>
>> >>>>>>>>>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> Hi all,
>> >>>>>>>>>>
>> >>>>>>>>>> I think current design is good.
>> >>>>>>>>>>
>> >>>>>>>>>> My understanding is:
>> >>>>>>>>>>
>> >>>>>>>>>> For execution mode: bounded mode and continuous mode, It's
>> >> totally
>> >>>>>>>>>> different. I don't think we have the ability to integrate the
>> >> two
>> >>>>>>> models
>> >>>>>>>>>>
>> >>>>>>>>>> at
>> >>>>>>>>>>
>> >>>>>>>>>> present. It's about scheduling, memory, algorithms, States,
>> etc.
>> >>> we
>> >>>>>>>>>> shouldn't confuse them.
>> >>>>>>>>>>
>> >>>>>>>>>> For source capabilities: only bounded, only continuous, both
>> >>> bounded
>> >>>>>>> and
>> >>>>>>>>>> continuous.
>> >>>>>>>>>> I think Kafka is a source that can be ran both bounded
>> >>>>>>>>>> and continuous execution mode.
>> >>>>>>>>>> And Kafka with end offset should be ran both bounded
>> >>>>>>>>>> and continuous execution mode.  Using apache Beam with Flink
>> >>>>>> runner, I
>> >>>>>>>>>>
>> >>>>>>>>>> used
>> >>>>>>>>>>
>> >>>>>>>>>> to run a "bounded" Kafka in streaming mode. For our previous
>> >>>>>>> DataStream,
>> >>>>>>>>>>
>> >>>>>>>>>> it
>> >>>>>>>>>>
>> >>>>>>>>>> is not necessarily required that the source cannot be bounded.
>> >>>>>>>>>>
>> >>>>>>>>>> So it is my thought for Dawid's question:
>> >>>>>>>>>> 1.pass a bounded source to continuousSource() +1
>> >>>>>>>>>> 2.pass a continuous source to boundedSource() -1, should throw
>> >>>>>>>> exception.
>> >>>>>>>>>>
>> >>>>>>>>>> In StreamExecutionEnvironment, continuousSource and
>> >> boundedSource
>> >>>>>>> define
>> >>>>>>>>>> the execution mode. It defines a clear boundary of execution
>> >> mode.
>> >>>>>>>>>>
>> >>>>>>>>>> Best,
>> >>>>>>>>>> Jingsong Lee
>> >>>>>>>>>>
>> >>>>>>>>>> On Tue, Dec 10, 2019 at 10:37 AM Jark Wu <[hidden email]
>> >>> <mailto:
>> >>>>>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
>> >>>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> I agree with Dawid's point that the boundedness information
>> >> should
>> >>>>>>> come
>> >>>>>>>>>> from the source itself (e.g. the end timestamp), not through
>> >>>>>>>>>> env.boundedSouce()/continuousSource().
>> >>>>>>>>>> I think if we want to support something like `env.source()`
>> that
>> >>>>>>> derive
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> execution mode from source, `supportsBoundedness(Boundedness)`
>> >>>>>>>>>> method is not enough, because we don't know whether it is
>> >> bounded
>> >>> or
>> >>>>>>>>>>
>> >>>>>>>>>> not.
>> >>>>>>>>>>
>> >>>>>>>>>> Best,
>> >>>>>>>>>> Jark
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> On Mon, 9 Dec 2019 at 22:21, Dawid Wysakowicz <
>> >>>>>> [hidden email]
>> >>>>>>>> <mailto:[hidden email]>> <[hidden email]
>> <mailto:
>> >>>>>>>> [hidden email]>>
>> >>>>>>>>>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> One more thing. In the current proposal, with the
>> >>>>>>>>>> supportsBoundedness(Boundedness) method and the boundedness
>> >> coming
>> >>>>>>>>>>
>> >>>>>>>>>> from
>> >>>>>>>>>>
>> >>>>>>>>>> either continuousSource or boundedSource I could not find how
>> >> this
>> >>>>>>>>>> information is fed back to the SplitEnumerator.
>> >>>>>>>>>>
>> >>>>>>>>>> Best,
>> >>>>>>>>>>
>> >>>>>>>>>> Dawid
>> >>>>>>>>>>
>> >>>>>>>>>> On 09/12/2019 13:52, Becket Qin wrote:
>> >>>>>>>>>>
>> >>>>>>>>>> Hi Dawid,
>> >>>>>>>>>>
>> >>>>>>>>>> Thanks for the comments. This actually brings another relevant
>> >>>>>>>>>>
>> >>>>>>>>>> question
>> >>>>>>>>>>
>> >>>>>>>>>> about what does a "bounded source" imply. I actually had the
>> >> same
>> >>>>>>>>>> impression when I look at the Source API. Here is what I
>> >>> understand
>> >>>>>>>>>>
>> >>>>>>>>>> after
>> >>>>>>>>>>
>> >>>>>>>>>> some discussion with Stephan. The bounded source has the
>> >> following
>> >>>>>>>>>>
>> >>>>>>>>>> impacts.
>> >>>>>>>>>>
>> >>>>>>>>>> 1. API validity.
>> >>>>>>>>>> - A bounded source generates a bounded stream so some
>> operations
>> >>>>>>>>>>
>> >>>>>>>>>> that
>> >>>>>>>>>>
>> >>>>>>>>>> only
>> >>>>>>>>>>
>> >>>>>>>>>> works for bounded records would be performed, e.g. sort.
>> >>>>>>>>>> - To expose these bounded stream only APIs, there are two
>> >> options:
>> >>>>>>>>>>       a. Add them to the DataStream API and throw exception if
>> a
>> >>>>>>>>>>
>> >>>>>>>>>> method
>> >>>>>>>>>>
>> >>>>>>>>>> is
>> >>>>>>>>>>
>> >>>>>>>>>> called on an unbounded stream.
>> >>>>>>>>>>       b. Create a BoundedDataStream class which is returned
>> from
>> >>>>>>>>>> env.boundedSource(), while DataStream is returned from
>> >>>>>>>>>>
>> >>>>>>>>>> env.continousSource().
>> >>>>>>>>>>
>> >>>>>>>>>> Note that this cannot be done by having single
>> >>>>>>>>>>
>> >>>>>>>>>> env.source(theSource)
>> >>>>>>>>>>
>> >>>>>>>>>> even
>> >>>>>>>>>>
>> >>>>>>>>>> the Source has a getBoundedness() method.
>> >>>>>>>>>>
>> >>>>>>>>>> 2. Scheduling
>> >>>>>>>>>> - A bounded source could be computed stage by stage without
>> >>>>>>>>>>
>> >>>>>>>>>> bringing
>> >>>>>>>>>>
>> >>>>>>>>>> up
>> >>>>>>>>>>
>> >>>>>>>>>> all
>> >>>>>>>>>>
>> >>>>>>>>>> the tasks at the same time.
>> >>>>>>>>>>
>> >>>>>>>>>> 3. Operator behaviors
>> >>>>>>>>>> - A bounded source indicates the records are finite so some
>> >>>>>>>>>>
>> >>>>>>>>>> operators
>> >>>>>>>>>>
>> >>>>>>>>>> can
>> >>>>>>>>>>
>> >>>>>>>>>> wait until it receives all the records before it starts the
>> >>>>>>>>>>
>> >>>>>>>>>> processing.
>> >>>>>>>>>>
>> >>>>>>>>>> In the above impact, only 1 is relevant to the API design. And
>> >> the
>> >>>>>>>>>>
>> >>>>>>>>>> current
>> >>>>>>>>>>
>> >>>>>>>>>> proposal in FLIP-27 is following 1.b.
>> >>>>>>>>>>
>> >>>>>>>>>> // boundedness depends of source property, imo this should
>> >> always
>> >>>>>>>>>>
>> >>>>>>>>>> be
>> >>>>>>>>>>
>> >>>>>>>>>> preferred
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> DataStream<MyType> stream = env.source(theSource);
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> In your proposal, does DataStream have bounded stream only
>> >>> methods?
>> >>>>>>>>>>
>> >>>>>>>>>> It
>> >>>>>>>>>>
>> >>>>>>>>>> looks it should have, otherwise passing a bounded Source to
>> >>>>>>>>>>
>> >>>>>>>>>> env.source()
>> >>>>>>>>>>
>> >>>>>>>>>> would be confusing. In that case, we will essentially do 1.a if
>> >> an
>> >>>>>>>>>> unbounded Source is created from env.source(unboundedSource).
>> >>>>>>>>>>
>> >>>>>>>>>> If we have the methods only supported for bounded streams in
>> >>>>>>>>>>
>> >>>>>>>>>> DataStream,
>> >>>>>>>>>>
>> >>>>>>>>>> it
>> >>>>>>>>>>
>> >>>>>>>>>> seems a little weird to have a separate BoundedDataStream
>> >>>>>>>>>>
>> >>>>>>>>>> interface.
>> >>>>>>>>>>
>> >>>>>>>>>> Am I understand it correctly?
>> >>>>>>>>>>
>> >>>>>>>>>> Thanks,
>> >>>>>>>>>>
>> >>>>>>>>>> Jiangjie (Becket) Qin
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> On Mon, Dec 9, 2019 at 6:40 PM Dawid Wysakowicz <
>> >>>>>>>>>>
>> >>>>>>>>>> [hidden email] <mailto:[hidden email]>>
>> >>>>>>>>>>
>> >>>>>>>>>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> Hi all,
>> >>>>>>>>>>
>> >>>>>>>>>> Really well written proposal and very important one. I must
>> >> admit
>> >>>>>>>>>>
>> >>>>>>>>>> I
>> >>>>>>>>>>
>> >>>>>>>>>> have
>> >>>>>>>>>>
>> >>>>>>>>>> not understood all the intricacies of it yet.
>> >>>>>>>>>>
>> >>>>>>>>>> One question I have though is about where does the information
>> >>>>>>>>>>
>> >>>>>>>>>> about
>> >>>>>>>>>>
>> >>>>>>>>>> boundedness come from. I think in most cases it is a property
>> of
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> source. As you described it might be e.g. end offset, a flag
>> >>>>>>>>>>
>> >>>>>>>>>> should
>> >>>>>>>>>>
>> >>>>>>>>>> it
>> >>>>>>>>>>
>> >>>>>>>>>> monitor new splits etc. I think it would be a really nice use
>> >> case
>> >>>>>>>>>>
>> >>>>>>>>>> to
>> >>>>>>>>>>
>> >>>>>>>>>> be
>> >>>>>>>>>>
>> >>>>>>>>>> able to say:
>> >>>>>>>>>>
>> >>>>>>>>>> new KafkaSource().readUntil(long timestamp),
>> >>>>>>>>>>
>> >>>>>>>>>> which could work as an "end offset". Moreover I think all
>> >> Bounded
>> >>>>>>>>>>
>> >>>>>>>>>> sources
>> >>>>>>>>>>
>> >>>>>>>>>> support continuous mode, but no intrinsically continuous source
>> >>>>>>>>>>
>> >>>>>>>>>> support
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> Bounded mode. If I understood the proposal correctly it suggest
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> boundedness sort of "comes" from the outside of the source,
>> from
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> invokation of either boundedStream or continousSource.
>> >>>>>>>>>>
>> >>>>>>>>>> I am wondering if it would make sense to actually change the
>> >>>>>>>>>>
>> >>>>>>>>>> method
>> >>>>>>>>>>
>> >>>>>>>>>> boolean Source#supportsBoundedness(Boundedness)
>> >>>>>>>>>>
>> >>>>>>>>>> to
>> >>>>>>>>>>
>> >>>>>>>>>> Boundedness Source#getBoundedness().
>> >>>>>>>>>>
>> >>>>>>>>>> As for the methods #boundedSource, #continousSource, assuming
>> >> the
>> >>>>>>>>>> boundedness is property of the source they do not affect how
>> the
>> >>>>>>>>>>
>> >>>>>>>>>> enumerator
>> >>>>>>>>>>
>> >>>>>>>>>> works, but mostly how the dag is scheduled, right? I am not
>> >>>>>>>>>>
>> >>>>>>>>>> against
>> >>>>>>>>>>
>> >>>>>>>>>> those
>> >>>>>>>>>>
>> >>>>>>>>>> methods, but I think it is a very specific use case to actually
>> >>>>>>>>>>
>> >>>>>>>>>> override
>> >>>>>>>>>>
>> >>>>>>>>>> the property of the source. In general I would expect users to
>> >>>>>>>>>>
>> >>>>>>>>>> only
>> >>>>>>>>>>
>> >>>>>>>>>> call
>> >>>>>>>>>>
>> >>>>>>>>>> env.source(theSource), where the source tells if it is bounded
>> >> or
>> >>>>>>>>>>
>> >>>>>>>>>> not. I
>> >>>>>>>>>>
>> >>>>>>>>>> would suggest considering following set of methods:
>> >>>>>>>>>>
>> >>>>>>>>>> // boundedness depends of source property, imo this should
>> >> always
>> >>>>>>>>>>
>> >>>>>>>>>> be
>> >>>>>>>>>>
>> >>>>>>>>>> preferred
>> >>>>>>>>>>
>> >>>>>>>>>> DataStream<MyType> stream = env.source(theSource);
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> // always continous execution, whether bounded or unbounded
>> >> source
>> >>>>>>>>>>
>> >>>>>>>>>> DataStream<MyType> boundedStream =
>> >> env.continousSource(theSource);
>> >>>>>>>>>>
>> >>>>>>>>>> // imo this would make sense if the BoundedDataStream provides
>> >>>>>>>>>>
>> >>>>>>>>>> additional features unavailable for continous mode
>> >>>>>>>>>>
>> >>>>>>>>>> BoundedDataStream<MyType> batch = env.boundedSource(theSource);
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> Best,
>> >>>>>>>>>>
>> >>>>>>>>>> Dawid
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> On 04/12/2019 11:25, Stephan Ewen wrote:
>> >>>>>>>>>>
>> >>>>>>>>>> Thanks, Becket, for updating this.
>> >>>>>>>>>>
>> >>>>>>>>>> I agree with moving the aspects you mentioned into separate
>> >> FLIPs
>> >>>>>>>>>>
>> >>>>>>>>>> -
>> >>>>>>>>>>
>> >>>>>>>>>> this
>> >>>>>>>>>>
>> >>>>>>>>>> one way becoming unwieldy in size.
>> >>>>>>>>>>
>> >>>>>>>>>> +1 to the FLIP in its current state. Its a very detailed
>> >> write-up,
>> >>>>>>>>>>
>> >>>>>>>>>> nicely
>> >>>>>>>>>>
>> >>>>>>>>>> done!
>> >>>>>>>>>>
>> >>>>>>>>>> On Wed, Dec 4, 2019 at 7:38 AM Becket Qin <
>> [hidden email]
>> >>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
>> >>>>>>>> [hidden email]>>
>> >>>>>>>>>>
>> >>>>>>>>>> <
>> >>>>>>>>>>
>> >>>>>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>> Hi all,
>> >>>>>>>>>>
>> >>>>>>>>>> Sorry for the long belated update. I have updated FLIP-27 wiki
>> >>>>>>>>>>
>> >>>>>>>>>> page
>> >>>>>>>>>>
>> >>>>>>>>>> with
>> >>>>>>>>>>
>> >>>>>>>>>> the latest proposals. Some noticeable changes include:
>> >>>>>>>>>> 1. A new generic communication mechanism between
>> SplitEnumerator
>> >>>>>>>>>>
>> >>>>>>>>>> and
>> >>>>>>>>>>
>> >>>>>>>>>> SourceReader.
>> >>>>>>>>>> 2. Some detail API method signature changes.
>> >>>>>>>>>>
>> >>>>>>>>>> We left a few things out of this FLIP and will address them in
>> >>>>>>>>>>
>> >>>>>>>>>> separate
>> >>>>>>>>>>
>> >>>>>>>>>> FLIPs. Including:
>> >>>>>>>>>> 1. Per split event time.
>> >>>>>>>>>> 2. Event time alignment.
>> >>>>>>>>>> 3. Fine grained failover for SplitEnumerator failure.
>> >>>>>>>>>>
>> >>>>>>>>>> Please let us know if you have any question.
>> >>>>>>>>>>
>> >>>>>>>>>> Thanks,
>> >>>>>>>>>>
>> >>>>>>>>>> Jiangjie (Becket) Qin
>> >>>>>>>>>>
>> >>>>>>>>>> On Sat, Nov 16, 2019 at 6:10 AM Stephan Ewen <[hidden email]
>> >>>>>>> <mailto:
>> >>>>>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
>> <
>> >>>>>>>>>>
>> >>>>>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>> Hi  Łukasz!
>> >>>>>>>>>>
>> >>>>>>>>>> Becket and me are working hard on figuring out the last details
>> >>>>>>>>>>
>> >>>>>>>>>> and
>> >>>>>>>>>>
>> >>>>>>>>>> implementing the first PoC. We would update the FLIP hopefully
>> >>>>>>>>>>
>> >>>>>>>>>> next
>> >>>>>>>>>>
>> >>>>>>>>>> week.
>> >>>>>>>>>>
>> >>>>>>>>>> There is a fair chance that a first version of this will be in
>> >>>>>>>>>>
>> >>>>>>>>>> 1.10,
>> >>>>>>>>>>
>> >>>>>>>>>> but
>> >>>>>>>>>>
>> >>>>>>>>>> I
>> >>>>>>>>>>
>> >>>>>>>>>> think it will take another release to battle test it and
>> migrate
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> connectors.
>> >>>>>>>>>>
>> >>>>>>>>>> Best,
>> >>>>>>>>>> Stephan
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> On Fri, Nov 15, 2019 at 11:14 AM Łukasz Jędrzejewski <
>> >> [hidden email]
>> >>>>>>>> <mailto:[hidden email]>
>> >>>>>>>>>>
>> >>>>>>>>>> <
>> >>>>>>>>>>
>> >>>>>>>>>> [hidden email] <mailto:[hidden email]>>
>> >>>>>>>>>>
>> >>>>>>>>>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>> Hi,
>> >>>>>>>>>>
>> >>>>>>>>>> This proposal looks very promising for us. Do you have any
>> plans
>> >>>>>>>>>>
>> >>>>>>>>>> in
>> >>>>>>>>>>
>> >>>>>>>>>> which
>> >>>>>>>>>>
>> >>>>>>>>>> Flink release it is going to be released? We are thinking on
>> >>>>>>>>>>
>> >>>>>>>>>> using a
>> >>>>>>>>>>
>> >>>>>>>>>> Data
>> >>>>>>>>>>
>> >>>>>>>>>> Set API for our future use cases but on the other hand Data Set
>> >>>>>>>>>>
>> >>>>>>>>>> API
>> >>>>>>>>>>
>> >>>>>>>>>> is
>> >>>>>>>>>>
>> >>>>>>>>>> going to be deprecated so using proposed bounded data streams
>> >>>>>>>>>>
>> >>>>>>>>>> solution
>> >>>>>>>>>>
>> >>>>>>>>>> could be more viable in the long term.
>> >>>>>>>>>>
>> >>>>>>>>>> Thanks,
>> >>>>>>>>>> Łukasz
>> >>>>>>>>>>
>> >>>>>>>>>> On 2019/10/01 15:48:03, Thomas Weise <[hidden email]
>> >>>>>> <mailto:
>> >>>>>>>> [hidden email]>> <[hidden email] <mailto:
>> >>>>>>>> [hidden email]>> <
>> >>>>>>>>>>
>> >>>>>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>> Thanks for putting together this proposal!
>> >>>>>>>>>>
>> >>>>>>>>>> I see that the "Per Split Event Time" and "Event Time
>> Alignment"
>> >>>>>>>>>>
>> >>>>>>>>>> sections
>> >>>>>>>>>>
>> >>>>>>>>>> are still TBD.
>> >>>>>>>>>>
>> >>>>>>>>>> It would probably be good to flesh those out a bit before
>> >>>>>>>>>>
>> >>>>>>>>>> proceeding
>> >>>>>>>>>>
>> >>>>>>>>>> too
>> >>>>>>>>>>
>> >>>>>>>>>> far
>> >>>>>>>>>>
>> >>>>>>>>>> as the event time alignment will probably influence the
>> >>>>>>>>>>
>> >>>>>>>>>> interaction
>> >>>>>>>>>>
>> >>>>>>>>>> with
>> >>>>>>>>>>
>> >>>>>>>>>> the split reader, specifically ReaderStatus
>> >>>>>>>>>>
>> >>>>>>>>>> emitNext(SourceOutput<E>
>> >>>>>>>>>>
>> >>>>>>>>>> output).
>> >>>>>>>>>>
>> >>>>>>>>>> We currently have only one implementation for event time
>> >> alignment
>> >>>>>>>>>>
>> >>>>>>>>>> in
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> Kinesis consumer. The synchronization in that case takes place
>> >> as
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> last
>> >>>>>>>>>>
>> >>>>>>>>>> step before records are emitted downstream (RecordEmitter).
>> With
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> currently proposed interfaces, the equivalent can be
>> implemented
>> >>>>>>>>>>
>> >>>>>>>>>> in
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> reader loop, although note that in the Kinesis consumer the per
>> >>>>>>>>>>
>> >>>>>>>>>> shard
>> >>>>>>>>>>
>> >>>>>>>>>> threads push records.
>> >>>>>>>>>>
>> >>>>>>>>>> Synchronization has not been implemented for the Kafka consumer
>> >>>>>>>>>>
>> >>>>>>>>>> yet.
>> >>>>>>>>>>
>> >>>>>>>>>> https://issues.apache.org/jira/browse/FLINK-12675 <
>> >>>>>>>> https://issues.apache.org/jira/browse/FLINK-12675>
>> >>>>>>>>>>
>> >>>>>>>>>> When I looked at it, I realized that the implementation will
>> >> look
>> >>>>>>>>>>
>> >>>>>>>>>> quite
>> >>>>>>>>>>
>> >>>>>>>>>> different
>> >>>>>>>>>> from Kinesis because it needs to take place in the pull part,
>> >>>>>>>>>>
>> >>>>>>>>>> where
>> >>>>>>>>>>
>> >>>>>>>>>> records
>> >>>>>>>>>>
>> >>>>>>>>>> are taken from the Kafka client. Due to the multiplexing it
>> >> cannot
>> >>>>>>>>>>
>> >>>>>>>>>> be
>> >>>>>>>>>>
>> >>>>>>>>>> done
>> >>>>>>>>>>
>> >>>>>>>>>> by blocking the split thread like it currently works for
>> >> Kinesis.
>> >>>>>>>>>>
>> >>>>>>>>>> Reading
>> >>>>>>>>>>
>> >>>>>>>>>> from individual Kafka partitions needs to be controlled via
>> >>>>>>>>>>
>> >>>>>>>>>> pause/resume
>> >>>>>>>>>>
>> >>>>>>>>>> on the Kafka client.
>> >>>>>>>>>>
>> >>>>>>>>>> To take on that responsibility the split thread would need to
>> be
>> >>>>>>>>>>
>> >>>>>>>>>> aware
>> >>>>>>>>>>
>> >>>>>>>>>> of
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>> watermarks or at least whether it should or should not continue
>> >> to
>> >>>>>>>>>>
>> >>>>>>>>>> consume
>> >>>>>>>>>>
>> >>>>>>>>>> a given split and this may require a different SourceReader or
>> >>>>>>>>>>
>> >>>>>>>>>> SourceOutput
>> >>>>>>>>>>
>> >>>>>>>>>> interface.
>> >>>>>>>>>>
>> >>>>>>>>>> Thanks,
>> >>>>>>>>>> Thomas
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> On Fri, Jul 26, 2019 at 1:39 AM Biao Liu <[hidden email]
>> >>>>>> <mailto:
>> >>>>>>>> [hidden email]>> <[hidden email] <mailto:
>> >> [hidden email]
>> >>>>>
>> >>>>>> <
>> >>>>>>>>>>
>> >>>>>>>>>> [hidden email] <mailto:[hidden email]>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>> Hi Stephan,
>> >>>>>>>>>>
>> >>>>>>>>>> Thank you for feedback!
>> >>>>>>>>>> Will take a look at your branch before public discussing.
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> On Fri, Jul 26, 2019 at 12:01 AM Stephan Ewen <
>> [hidden email]
>> >>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
>> >>> [hidden email]
>> >>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> <
>> >>>>>>>>>>
>> >>>>>>>>>> [hidden email] <mailto:[hidden email]>>
>> >>>>>>>>>>
>> >>>>>>>>>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>> Hi Biao!
>> >>>>>>>>>>
>> >>>>>>>>>> Thanks for reviving this. I would like to join this discussion,
>> >>>>>>>>>>
>> >>>>>>>>>> but
>> >>>>>>>>>>
>> >>>>>>>>>> am
>> >>>>>>>>>>
>> >>>>>>>>>> quite occupied with the 1.9 release, so can we maybe pause this
>> >>>>>>>>>>
>> >>>>>>>>>> discussion
>> >>>>>>>>>>
>> >>>>>>>>>> for a week or so?
>> >>>>>>>>>>
>> >>>>>>>>>> In the meantime I can share some suggestion based on prior
>> >>>>>>>>>>
>> >>>>>>>>>> experiments:
>> >>>>>>>>>>
>> >>>>>>>>>> How to do watermarks / timestamp extractors in a simpler and
>> >> more
>> >>>>>>>>>>
>> >>>>>>>>>> flexible
>> >>>>>>>>>>
>> >>>>>>>>>> way. I think that part is quite promising should be part of the
>> >>>>>>>>>>
>> >>>>>>>>>> new
>> >>>>>>>>>>
>> >>>>>>>>>> source
>> >>>>>>>>>>
>> >>>>>>>>>> interface.
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>
>> >>>>>>>
>> >>>>>>
>> >>>>
>> >>>
>> >>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
>> >>>>>>>> <
>> >>>>>>>>
>> >>>>>>>
>> >>>>>>
>> >>>>
>> >>>
>> >>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime
>> >>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>
>> >>>>>>>
>> >>>>>>
>> >>>>
>> >>>
>> >>
>> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
>> >>>>>>>> <
>> >>>>>>>>
>> >>>>>>>
>> >>>>>>
>> >>>>
>> >>>
>> >>
>> https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java
>> >>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> Some experiments on how to build the source reader and its
>> >>>>>>>>>>
>> >>>>>>>>>> library
>> >>>>>>>>>>
>> >>>>>>>>>> for
>> >>>>>>>>>>
>> >>>>>>>>>> common threading/split patterns:
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>
>> >>>>>>>
>> >>>>>>
>> >>>>
>> >>>
>> >>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
>> >>>>>>>> <
>> >>>>>>>>
>> >>>>>>>
>> >>>>>>
>> >>>>
>> >>>
>> >>
>> https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src
>> >>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> Best,
>> >>>>>>>>>> Stephan
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <[hidden email]
>> >>>>>>> <mailto:
>> >>>>>>>> [hidden email]>> <[hidden email] <mailto:
>> >> [hidden email]
>> >>>>>
>> >>>>>> <
>> >>>>>>>>>>
>> >>>>>>>>>> [hidden email] <mailto:[hidden email]>>
>> >>>>>>>>>>
>> >>>>>>>>>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>> Hi devs,
>> >>>>>>>>>>
>> >>>>>>>>>> Since 1.9 is nearly released, I think we could get back to
>> >>>>>>>>>>
>> >>>>>>>>>> FLIP-27.
>> >>>>>>>>>>
>> >>>>>>>>>> I
>> >>>>>>>>>>
>> >>>>>>>>>> believe it should be included in 1.10.
>> >>>>>>>>>>
>> >>>>>>>>>> There are so many things mentioned in document of FLIP-27. [1]
>> I
>> >>>>>>>>>>
>> >>>>>>>>>> think
>> >>>>>>>>>>
>> >>>>>>>>>> we'd better discuss them separately. However the wiki is not a
>> >>>>>>>>>>
>> >>>>>>>>>> good
>> >>>>>>>>>>
>> >>>>>>>>>> place
>> >>>>>>>>>>
>> >>>>>>>>>> to discuss. I wrote google doc about SplitReader API which
>> >>>>>>>>>>
>> >>>>>>>>>> misses
>> >>>>>>>>>>
>> >>>>>>>>>> some
>> >>>>>>>>>>
>> >>>>>>>>>> details in the document. [2]
>> >>>>>>>>>>
>> >>>>>>>>>> 1.
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>
>> >>>>>>>
>> >>>>>>
>> >>>>
>> >>>
>> >>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
>> >>>>>>>> <
>> >>>>>>>>
>> >>>>>>>
>> >>>>>>
>> >>>>
>> >>>
>> >>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface
>> >>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> 2.
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>
>> >>>>>>>
>> >>>>>>
>> >>>>
>> >>>
>> >>
>> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
>> >>>>>>>> <
>> >>>>>>>>
>> >>>>>>>
>> >>>>>>
>> >>>>
>> >>>
>> >>
>> https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing
>> >>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> CC Stephan, Aljoscha, Piotrek, Becket
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <[hidden email]
>> >>>>>> <mailto:
>> >>>>>>>> [hidden email]>> <[hidden email] <mailto:
>> >> [hidden email]
>> >>>>>
>> >>>>>> <
>> >>>>>>>>>>
>> >>>>>>>>>> [hidden email] <mailto:[hidden email]>>
>> >>>>>>>>>>
>> >>>>>>>>>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>> Hi Steven,
>> >>>>>>>>>> Thank you for the feedback. Please take a look at the document
>> >>>>>>>>>>
>> >>>>>>>>>> FLIP-27
>> >>>>>>>>>>
>> >>>>>>>>>> <
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>
>> >>>>>>>
>> >>>>>>
>> >>>>
>> >>>
>> >>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
>> >>>>>>>> <
>> >>>>>>>>
>> >>>>>>>
>> >>>>>>
>> >>>>
>> >>>
>> >>
>> https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface
>> >>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> which
>> >>>>>>>>>>
>> >>>>>>>>>> is updated recently. A lot of details of enumerator were added
>> >>>>>>>>>>
>> >>>>>>>>>> in
>> >>>>>>>>>>
>> >>>>>>>>>> this
>> >>>>>>>>>>
>> >>>>>>>>>> document. I think it would help.
>> >>>>>>>>>>
>> >>>>>>>>>> Steven Wu <[hidden email] <mailto:[hidden email]>>
>> >> <
>> >>>>>>>> [hidden email] <mailto:[hidden email]>> <
>> >>>>>>> [hidden email]
>> >>>>>>>> <mailto:[hidden email]>> <[hidden email] <mailto:
>> >>>>>>>> [hidden email]>>
>> >>>>>>>>>>
>> >>>>>>>>>> 于2019年3月28日周四
>> >>>>>>>>>>
>> >>>>>>>>>> 下午12:52写道：
>> >>>>>>>>>>
>> >>>>>>>>>> This proposal mentioned that SplitEnumerator might run on the
>> >>>>>>>>>> JobManager or
>> >>>>>>>>>> in a single task on a TaskManager.
>> >>>>>>>>>>
>> >>>>>>>>>> if enumerator is a single task on a taskmanager, then the job
>> >>>>>>>>>>
>> >>>>>>>>>> DAG
>> >>>>>>>>>>
>> >>>>>>>>>> can
>> >>>>>>>>>>
>> >>>>>>>>>> never
>> >>>>>>>>>> been embarrassingly parallel anymore. That will nullify the
>> >>>>>>>>>>
>> >>>>>>>>>> leverage
>> >>>>>>>>>>
>> >>>>>>>>>> of
>> >>>>>>>>>>
>> >>>>>>>>>> fine-grained recovery for embarrassingly parallel jobs.
>> >>>>>>>>>>
>> >>>>>>>>>> It's not clear to me what's the implication of running
>> >>>>>>>>>>
>> >>>>>>>>>> enumerator
>> >>>>>>>>>>
>> >>>>>>>>>> on
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> jobmanager. So I will leave that out for now.
>> >>>>>>>>>>
>> >>>>>>>>>> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <[hidden email]
>> >>>>>> <mailto:
>> >>>>>>>> [hidden email]>> <[hidden email] <mailto:
>> >> [hidden email]
>> >>>>>
>> >>>>>> <
>> >>>>>>>>>>
>> >>>>>>>>>> [hidden email] <mailto:[hidden email]>>
>> >>>>>>>>>>
>> >>>>>>>>>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>> Hi Stephan & Piotrek,
>> >>>>>>>>>>
>> >>>>>>>>>> Thank you for feedback.
>> >>>>>>>>>>
>> >>>>>>>>>> It seems that there are a lot of things to do in community.
>> >>>>>>>>>>
>> >>>>>>>>>> I
>> >>>>>>>>>>
>> >>>>>>>>>> am
>> >>>>>>>>>>
>> >>>>>>>>>> just
>> >>>>>>>>>>
>> >>>>>>>>>> afraid that this discussion may be forgotten since there so
>> >>>>>>>>>>
>> >>>>>>>>>> many
>> >>>>>>>>>>
>> >>>>>>>>>> proposals
>> >>>>>>>>>>
>> >>>>>>>>>> recently.
>> >>>>>>>>>> Anyway, wish to see the split topics soon :)
>> >>>>>>>>>>
>> >>>>>>>>>> Piotr Nowojski <[hidden email] <mailto:
>> >>> [hidden email]
>> >>>>>>>>
>> >>>>>>> <
>> >>>>>>>> [hidden email] <mailto:[hidden email]>> <
>> >>>>>>>> [hidden email] <mailto:[hidden email]>> <
>> >>>>>>>> [hidden email] <mailto:[hidden email]>>
>> >>>>>>>>>>
>> >>>>>>>>>> 于2019年1月24日周四
>> >>>>>>>>>>
>> >>>>>>>>>> 下午8:21写道：
>> >>>>>>>>>>
>> >>>>>>>>>> Hi Biao!
>> >>>>>>>>>>
>> >>>>>>>>>> This discussion was stalled because of preparations for
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> open
>> >>>>>>>>>>
>> >>>>>>>>>> sourcing
>> >>>>>>>>>>
>> >>>>>>>>>> & merging Blink. I think before creating the tickets we
>> >>>>>>>>>>
>> >>>>>>>>>> should
>> >>>>>>>>>>
>> >>>>>>>>>> split this
>> >>>>>>>>>>
>> >>>>>>>>>> discussion into topics/areas outlined by Stephan and
>> >>>>>>>>>>
>> >>>>>>>>>> create
>> >>>>>>>>>>
>> >>>>>>>>>> Flips
>> >>>>>>>>>>
>> >>>>>>>>>> for
>> >>>>>>>>>>
>> >>>>>>>>>> that.
>> >>>>>>>>>>
>> >>>>>>>>>> I think there is no chance for this to be completed in
>> >>>>>>>>>>
>> >>>>>>>>>> couple
>> >>>>>>>>>>
>> >>>>>>>>>> of
>> >>>>>>>>>>
>> >>>>>>>>>> remaining
>> >>>>>>>>>>
>> >>>>>>>>>> weeks/1 month before 1.8 feature freeze, however it would
>> >>>>>>>>>>
>> >>>>>>>>>> be
>> >>>>>>>>>>
>> >>>>>>>>>> good
>> >>>>>>>>>>
>> >>>>>>>>>> to aim
>> >>>>>>>>>>
>> >>>>>>>>>> with those changes for 1.9.
>> >>>>>>>>>>
>> >>>>>>>>>> Piotrek
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> On 20 Jan 2019, at 16:08, Biao Liu <[hidden email]
>> <mailto:
>> >>>>>>>> [hidden email]>> <[hidden email] <mailto:
>> >> [hidden email]
>> >>>>>
>> >>>>>> <
>> >>>>>>>>>>
>> >>>>>>>>>> [hidden email] <mailto:[hidden email]>>
>> >>>>>>>>>>
>> >>>>>>>>>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>> Hi community,
>> >>>>>>>>>> The summary of Stephan makes a lot sense to me. It is
>> >>>>>>>>>>
>> >>>>>>>>>> much
>> >>>>>>>>>>
>> >>>>>>>>>> clearer
>> >>>>>>>>>>
>> >>>>>>>>>> indeed
>> >>>>>>>>>>
>> >>>>>>>>>> after splitting the complex topic into small ones.
>> >>>>>>>>>> I was wondering is there any detail plan for next step?
>> >>>>>>>>>>
>> >>>>>>>>>> If
>> >>>>>>>>>>
>> >>>>>>>>>> not,
>> >>>>>>>>>>
>> >>>>>>>>>> I
>> >>>>>>>>>>
>> >>>>>>>>>> would
>> >>>>>>>>>>
>> >>>>>>>>>> like to push this thing forward by creating some JIRA
>> >>>>>>>>>>
>> >>>>>>>>>> issues.
>> >>>>>>>>>>
>> >>>>>>>>>> Another question is that should version 1.8 include
>> >>>>>>>>>>
>> >>>>>>>>>> these
>> >>>>>>>>>>
>> >>>>>>>>>> features?
>> >>>>>>>>>>
>> >>>>>>>>>> Stephan Ewen <[hidden email] <mailto:[hidden email]>> <
>> >>>>>>>> [hidden email] <mailto:[hidden email]>> <[hidden email]
>> >>>> <mailto:
>> >>>>>>>> [hidden email]>> <[hidden email] <mailto:[hidden email]>>
>> >>>>>>>> 于2018年12月1日周六
>> >>>>>>>>>>
>> >>>>>>>>>> 上午4:20写道：
>> >>>>>>>>>>
>> >>>>>>>>>> Thanks everyone for the lively discussion. Let me try
>> >>>>>>>>>>
>> >>>>>>>>>> to
>> >>>>>>>>>>
>> >>>>>>>>>> summarize
>> >>>>>>>>>>
>> >>>>>>>>>> where I
>> >>>>>>>>>>
>> >>>>>>>>>> see convergence in the discussion and open issues.
>> >>>>>>>>>> I'll try to group this by design aspect of the source.
>> >>>>>>>>>>
>> >>>>>>>>>> Please
>> >>>>>>>>>>
>> >>>>>>>>>> let me
>> >>>>>>>>>>
>> >>>>>>>>>> know
>> >>>>>>>>>>
>> >>>>>>>>>> if I got things wrong or missed something crucial here.
>> >>>>>>>>>>
>> >>>>>>>>>> For issues 1-3, if the below reflects the state of the
>> >>>>>>>>>>
>> >>>>>>>>>> discussion, I
>> >>>>>>>>>>
>> >>>>>>>>>> would
>> >>>>>>>>>>
>> >>>>>>>>>> try and update the FLIP in the next days.
>> >>>>>>>>>> For the remaining ones we need more discussion.
>> >>>>>>>>>>
>> >>>>>>>>>> I would suggest to fork each of these aspects into a
>> >>>>>>>>>>
>> >>>>>>>>>> separate
>> >>>>>>>>>>
>> >>>>>>>>>> mail
>> >>>>>>>>>>
>> >>>>>>>>>> thread,
>> >>>>>>>>>>
>> >>>>>>>>>> or will loose sight of the individual aspects.
>> >>>>>>>>>>
>> >>>>>>>>>> *(1) Separation of Split Enumerator and Split Reader*
>> >>>>>>>>>>
>> >>>>>>>>>> - All seem to agree this is a good thing
>> >>>>>>>>>> - Split Enumerator could in the end live on JobManager
>> >>>>>>>>>>
>> >>>>>>>>>> (and
>> >>>>>>>>>>
>> >>>>>>>>>> assign
>> >>>>>>>>>>
>> >>>>>>>>>> splits
>> >>>>>>>>>>
>> >>>>>>>>>> via RPC) or in a task (and assign splits via data
>> >>>>>>>>>>
>> >>>>>>>>>> streams)
>> >>>>>>>>>>
>> >>>>>>>>>> - this discussion is orthogonal and should come later,
>> >>>>>>>>>>
>> >>>>>>>>>> when
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> interface
>> >>>>>>>>>>
>> >>>>>>>>>> is agreed upon.
>> >>>>>>>>>>
>> >>>>>>>>>> *(2) Split Readers for one or more splits*
>> >>>>>>>>>>
>> >>>>>>>>>> - Discussion seems to agree that we need to support
>> >>>>>>>>>>
>> >>>>>>>>>> one
>> >>>>>>>>>>
>> >>>>>>>>>> reader
>> >>>>>>>>>>
>> >>>>>>>>>> that
>> >>>>>>>>>>
>> >>>>>>>>>> possibly handles multiple splits concurrently.
>> >>>>>>>>>> - The requirement comes from sources where one
>> >>>>>>>>>>
>> >>>>>>>>>> poll()-style
>> >>>>>>>>>>
>> >>>>>>>>>> call
>> >>>>>>>>>>
>> >>>>>>>>>> fetches
>> >>>>>>>>>>
>> >>>>>>>>>> data from different splits / partitions
>> >>>>>>>>>>     --> example sources that require that would be for
>> >>>>>>>>>>
>> >>>>>>>>>> example
>> >>>>>>>>>>
>> >>>>>>>>>> Kafka,
>> >>>>>>>>>>
>> >>>>>>>>>> Pravega, Pulsar
>> >>>>>>>>>>
>> >>>>>>>>>> - Could have one split reader per source, or multiple
>> >>>>>>>>>>
>> >>>>>>>>>> split
>> >>>>>>>>>>
>> >>>>>>>>>> readers
>> >>>>>>>>>>
>> >>>>>>>>>> that
>> >>>>>>>>>>
>> >>>>>>>>>> share the "poll()" function
>> >>>>>>>>>> - To not make it too complicated, we can start with
>> >>>>>>>>>>
>> >>>>>>>>>> thinking
>> >>>>>>>>>>
>> >>>>>>>>>> about
>> >>>>>>>>>>
>> >>>>>>>>>> one
>> >>>>>>>>>>
>> >>>>>>>>>> split reader for all splits initially and see if that
>> >>>>>>>>>>
>> >>>>>>>>>> covers
>> >>>>>>>>>>
>> >>>>>>>>>> all
>> >>>>>>>>>>
>> >>>>>>>>>> requirements
>> >>>>>>>>>>
>> >>>>>>>>>> *(3) Threading model of the Split Reader*
>> >>>>>>>>>>
>> >>>>>>>>>> - Most active part of the discussion ;-)
>> >>>>>>>>>>
>> >>>>>>>>>> - A non-blocking way for Flink's task code to interact
>> >>>>>>>>>>
>> >>>>>>>>>> with
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> source
>> >>>>>>>>>>
>> >>>>>>>>>> is
>> >>>>>>>>>>
>> >>>>>>>>>> needed in order to a task runtime code based on a
>> >>>>>>>>>> single-threaded/actor-style task design
>> >>>>>>>>>>     --> I personally am a big proponent of that, it will
>> >>>>>>>>>>
>> >>>>>>>>>> help
>> >>>>>>>>>>
>> >>>>>>>>>> with
>> >>>>>>>>>>
>> >>>>>>>>>> well-behaved checkpoints, efficiency, and simpler yet
>> >>>>>>>>>>
>> >>>>>>>>>> more
>> >>>>>>>>>>
>> >>>>>>>>>> robust
>> >>>>>>>>>>
>> >>>>>>>>>> runtime
>> >>>>>>>>>>
>> >>>>>>>>>> code
>> >>>>>>>>>>
>> >>>>>>>>>> - Users care about simple abstraction, so as a
>> >>>>>>>>>>
>> >>>>>>>>>> subclass
>> >>>>>>>>>>
>> >>>>>>>>>> of
>> >>>>>>>>>>
>> >>>>>>>>>> SplitReader
>> >>>>>>>>>>
>> >>>>>>>>>> (non-blocking / async) we need to have a
>> >>>>>>>>>>
>> >>>>>>>>>> BlockingSplitReader
>> >>>>>>>>>>
>> >>>>>>>>>> which
>> >>>>>>>>>>
>> >>>>>>>>>> will
>> >>>>>>>>>>
>> >>>>>>>>>> form the basis of most source implementations.
>> >>>>>>>>>>
>> >>>>>>>>>> BlockingSplitReader
>> >>>>>>>>>>
>> >>>>>>>>>> lets
>> >>>>>>>>>>
>> >>>>>>>>>> users do blocking simple poll() calls.
>> >>>>>>>>>> - The BlockingSplitReader would spawn a thread (or
>> >>>>>>>>>>
>> >>>>>>>>>> more)
>> >>>>>>>>>>
>> >>>>>>>>>> and
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> thread(s) can make blocking calls and hand over data
>> >>>>>>>>>>
>> >>>>>>>>>> buffers
>> >>>>>>>>>>
>> >>>>>>>>>> via
>> >>>>>>>>>>
>> >>>>>>>>>> a
>> >>>>>>>>>>
>> >>>>>>>>>> blocking
>> >>>>>>>>>>
>> >>>>>>>>>> queue
>> >>>>>>>>>> - This should allow us to cover both, a fully async
>> >>>>>>>>>>
>> >>>>>>>>>> runtime,
>> >>>>>>>>>>
>> >>>>>>>>>> and a
>> >>>>>>>>>>
>> >>>>>>>>>> simple
>> >>>>>>>>>>
>> >>>>>>>>>> blocking interface for users.
>> >>>>>>>>>> - This is actually very similar to how the Kafka
>> >>>>>>>>>>
>> >>>>>>>>>> connectors
>> >>>>>>>>>>
>> >>>>>>>>>> work.
>> >>>>>>>>>>
>> >>>>>>>>>> Kafka
>> >>>>>>>>>>
>> >>>>>>>>>> 9+ with one thread, Kafka 8 with multiple threads
>> >>>>>>>>>>
>> >>>>>>>>>> - On the base SplitReader (the async one), the
>> >>>>>>>>>>
>> >>>>>>>>>> non-blocking
>> >>>>>>>>>>
>> >>>>>>>>>> method
>> >>>>>>>>>>
>> >>>>>>>>>> that
>> >>>>>>>>>>
>> >>>>>>>>>> gets the next chunk of data would signal data
>> >>>>>>>>>>
>> >>>>>>>>>> availability
>> >>>>>>>>>>
>> >>>>>>>>>> via
>> >>>>>>>>>>
>> >>>>>>>>>> a
>> >>>>>>>>>>
>> >>>>>>>>>> CompletableFuture, because that gives the best
>> >>>>>>>>>>
>> >>>>>>>>>> flexibility
>> >>>>>>>>>>
>> >>>>>>>>>> (can
>> >>>>>>>>>>
>> >>>>>>>>>> await
>> >>>>>>>>>>
>> >>>>>>>>>> completion or register notification handlers).
>> >>>>>>>>>> - The source task would register a "thenHandle()" (or
>> >>>>>>>>>>
>> >>>>>>>>>> similar)
>> >>>>>>>>>>
>> >>>>>>>>>> on the
>> >>>>>>>>>>
>> >>>>>>>>>> future to put a "take next data" task into the
>> >>>>>>>>>>
>> >>>>>>>>>> actor-style
>> >>>>>>>>>>
>> >>>>>>>>>> mailbox
>> >>>>>>>>>>
>> >>>>>>>>>> *(4) Split Enumeration and Assignment*
>> >>>>>>>>>>
>> >>>>>>>>>> - Splits may be generated lazily, both in cases where
>> >>>>>>>>>>
>> >>>>>>>>>> there
>> >>>>>>>>>>
>> >>>>>>>>>> is a
>> >>>>>>>>>>
>> >>>>>>>>>> limited
>> >>>>>>>>>>
>> >>>>>>>>>> number of splits (but very many), or splits are
>> >>>>>>>>>>
>> >>>>>>>>>> discovered
>> >>>>>>>>>>
>> >>>>>>>>>> over
>> >>>>>>>>>>
>> >>>>>>>>>> time
>> >>>>>>>>>>
>> >>>>>>>>>> - Assignment should also be lazy, to get better load
>> >>>>>>>>>>
>> >>>>>>>>>> balancing
>> >>>>>>>>>>
>> >>>>>>>>>> - Assignment needs support locality preferences
>> >>>>>>>>>>
>> >>>>>>>>>> - Possible design based on discussion so far:
>> >>>>>>>>>>
>> >>>>>>>>>>     --> SplitReader has a method "addSplits(SplitT...)"
>> >>>>>>>>>>
>> >>>>>>>>>> to
>> >>>>>>>>>>
>> >>>>>>>>>> add
>> >>>>>>>>>>
>> >>>>>>>>>> one or
>> >>>>>>>>>>
>> >>>>>>>>>> more
>> >>>>>>>>>>
>> >>>>>>>>>> splits. Some split readers might assume they have only
>> >>>>>>>>>>
>> >>>>>>>>>> one
>> >>>>>>>>>>
>> >>>>>>>>>> split
>> >>>>>>>>>>
>> >>>>>>>>>> ever,
>> >>>>>>>>>>
>> >>>>>>>>>> concurrently, others assume multiple splits. (Note:
>> >>>>>>>>>>
>> >>>>>>>>>> idea
>> >>>>>>>>>>
>> >>>>>>>>>> behind
>> >>>>>>>>>>
>> >>>>>>>>>> being
>> >>>>>>>>>>
>> >>>>>>>>>> able
>> >>>>>>>>>>
>> >>>>>>>>>> to add multiple splits at the same time is to ease
>> >>>>>>>>>>
>> >>>>>>>>>> startup
>> >>>>>>>>>>
>> >>>>>>>>>> where
>> >>>>>>>>>>
>> >>>>>>>>>> multiple
>> >>>>>>>>>>
>> >>>>>>>>>> splits may be assigned instantly.)
>> >>>>>>>>>>     --> SplitReader has a context object on which it can
>> >>>>>>>>>>
>> >>>>>>>>>> call
>> >>>>>>>>>>
>> >>>>>>>>>> indicate
>> >>>>>>>>>>
>> >>>>>>>>>> when
>> >>>>>>>>>>
>> >>>>>>>>>> splits are completed. The enumerator gets that
>> >>>>>>>>>>
>> >>>>>>>>>> notification and
>> >>>>>>>>>>
>> >>>>>>>>>> can
>> >>>>>>>>>>
>> >>>>>>>>>> use
>> >>>>>>>>>>
>> >>>>>>>>>> to
>> >>>>>>>>>>
>> >>>>>>>>>> decide when to assign new splits. This should help both
>> >>>>>>>>>>
>> >>>>>>>>>> in
>> >>>>>>>>>>
>> >>>>>>>>>> cases
>> >>>>>>>>>>
>> >>>>>>>>>> of
>> >>>>>>>>>>
>> >>>>>>>>>> sources
>> >>>>>>>>>>
>> >>>>>>>>>> that take splits lazily (file readers) and in case the
>> >>>>>>>>>>
>> >>>>>>>>>> source
>> >>>>>>>>>>
>> >>>>>>>>>> needs to
>> >>>>>>>>>>
>> >>>>>>>>>> preserve a partial order between splits (Kinesis,
>> >>>>>>>>>>
>> >>>>>>>>>> Pravega,
>> >>>>>>>>>>
>> >>>>>>>>>> Pulsar may
>> >>>>>>>>>>
>> >>>>>>>>>> need
>> >>>>>>>>>>
>> >>>>>>>>>> that).
>> >>>>>>>>>>     --> SplitEnumerator gets notification when
>> >>>>>>>>>>
>> >>>>>>>>>> SplitReaders
>> >>>>>>>>>>
>> >>>>>>>>>> start
>> >>>>>>>>>>
>> >>>>>>>>>> and
>> >>>>>>>>>>
>> >>>>>>>>>> when
>> >>>>>>>>>>
>> >>>>>>>>>> they finish splits. They can decide at that moment to
>> >>>>>>>>>>
>> >>>>>>>>>> push
>> >>>>>>>>>>
>> >>>>>>>>>> more
>> >>>>>>>>>>
>> >>>>>>>>>> splits
>> >>>>>>>>>>
>> >>>>>>>>>> to
>> >>>>>>>>>>
>> >>>>>>>>>> that reader
>> >>>>>>>>>>     --> The SplitEnumerator should probably be aware of
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> source
>> >>>>>>>>>>
>> >>>>>>>>>> parallelism, to build its initial distribution.
>> >>>>>>>>>>
>> >>>>>>>>>> - Open question: Should the source expose something
>> >>>>>>>>>>
>> >>>>>>>>>> like
>> >>>>>>>>>>
>> >>>>>>>>>> "host
>> >>>>>>>>>>
>> >>>>>>>>>> preferences", so that yarn/mesos/k8s can take this into
>> >>>>>>>>>>
>> >>>>>>>>>> account
>> >>>>>>>>>>
>> >>>>>>>>>> when
>> >>>>>>>>>>
>> >>>>>>>>>> selecting a node to start a TM on?
>> >>>>>>>>>>
>> >>>>>>>>>> *(5) Watermarks and event time alignment*
>> >>>>>>>>>>
>> >>>>>>>>>> - Watermark generation, as well as idleness, needs to
>> >>>>>>>>>>
>> >>>>>>>>>> be
>> >>>>>>>>>>
>> >>>>>>>>>> per
>> >>>>>>>>>>
>> >>>>>>>>>> split
>> >>>>>>>>>>
>> >>>>>>>>>> (like
>> >>>>>>>>>>
>> >>>>>>>>>> currently in the Kafka Source, per partition)
>> >>>>>>>>>> - It is desirable to support optional
>> >>>>>>>>>>
>> >>>>>>>>>> event-time-alignment,
>> >>>>>>>>>>
>> >>>>>>>>>> meaning
>> >>>>>>>>>>
>> >>>>>>>>>> that
>> >>>>>>>>>>
>> >>>>>>>>>> splits that are ahead are back-pressured or temporarily
>> >>>>>>>>>>
>> >>>>>>>>>> unsubscribed
>> >>>>>>>>>>
>> >>>>>>>>>> - I think i would be desirable to encapsulate
>> >>>>>>>>>>
>> >>>>>>>>>> watermark
>> >>>>>>>>>>
>> >>>>>>>>>> generation
>> >>>>>>>>>>
>> >>>>>>>>>> logic
>> >>>>>>>>>>
>> >>>>>>>>>> in watermark generators, for a separation of concerns.
>> >>>>>>>>>>
>> >>>>>>>>>> The
>> >>>>>>>>>>
>> >>>>>>>>>> watermark
>> >>>>>>>>>>
>> >>>>>>>>>> generators should run per split.
>> >>>>>>>>>> - Using watermark generators would also help with
>> >>>>>>>>>>
>> >>>>>>>>>> another
>> >>>>>>>>>>
>> >>>>>>>>>> problem of
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> suggested interface, namely supporting non-periodic
>> >>>>>>>>>>
>> >>>>>>>>>> watermarks
>> >>>>>>>>>>
>> >>>>>>>>>> efficiently.
>> >>>>>>>>>>
>> >>>>>>>>>> - Need a way to "dispatch" next record to different
>> >>>>>>>>>>
>> >>>>>>>>>> watermark
>> >>>>>>>>>>
>> >>>>>>>>>> generators
>> >>>>>>>>>>
>> >>>>>>>>>> - Need a way to tell SplitReader to "suspend" a split
>> >>>>>>>>>>
>> >>>>>>>>>> until a
>> >>>>>>>>>>
>> >>>>>>>>>> certain
>> >>>>>>>>>>
>> >>>>>>>>>> watermark is reached (event time backpressure)
>> >>>>>>>>>> - This would in fact be not needed (and thus simpler)
>> >>>>>>>>>>
>> >>>>>>>>>> if
>> >>>>>>>>>>
>> >>>>>>>>>> we
>> >>>>>>>>>>
>> >>>>>>>>>> had
>> >>>>>>>>>>
>> >>>>>>>>>> a
>> >>>>>>>>>>
>> >>>>>>>>>> SplitReader per split and may be a reason to re-open
>> >>>>>>>>>>
>> >>>>>>>>>> that
>> >>>>>>>>>>
>> >>>>>>>>>> discussion
>> >>>>>>>>>>
>> >>>>>>>>>> *(6) Watermarks across splits and in the Split
>> >>>>>>>>>>
>> >>>>>>>>>> Enumerator*
>> >>>>>>>>>>
>> >>>>>>>>>> - The split enumerator may need some watermark
>> >>>>>>>>>>
>> >>>>>>>>>> awareness,
>> >>>>>>>>>>
>> >>>>>>>>>> which
>> >>>>>>>>>>
>> >>>>>>>>>> should
>> >>>>>>>>>>
>> >>>>>>>>>> be
>> >>>>>>>>>>
>> >>>>>>>>>> purely based on split metadata (like create timestamp
>> >>>>>>>>>>
>> >>>>>>>>>> of
>> >>>>>>>>>>
>> >>>>>>>>>> file
>> >>>>>>>>>>
>> >>>>>>>>>> splits)
>> >>>>>>>>>>
>> >>>>>>>>>> - If there are still more splits with overlapping
>> >>>>>>>>>>
>> >>>>>>>>>> event
>> >>>>>>>>>>
>> >>>>>>>>>> time
>> >>>>>>>>>>
>> >>>>>>>>>> range
>> >>>>>>>>>>
>> >>>>>>>>>> for
>> >>>>>>>>>>
>> >>>>>>>>>> a
>> >>>>>>>>>>
>> >>>>>>>>>> split reader, then that split reader should not advance
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> watermark
>> >>>>>>>>>>
>> >>>>>>>>>> within the split beyond the overlap boundary. Otherwise
>> >>>>>>>>>>
>> >>>>>>>>>> future
>> >>>>>>>>>>
>> >>>>>>>>>> splits
>> >>>>>>>>>>
>> >>>>>>>>>> will
>> >>>>>>>>>>
>> >>>>>>>>>> produce late data.
>> >>>>>>>>>>
>> >>>>>>>>>> - One way to approach this could be that the split
>> >>>>>>>>>>
>> >>>>>>>>>> enumerator
>> >>>>>>>>>>
>> >>>>>>>>>> may
>> >>>>>>>>>>
>> >>>>>>>>>> send
>> >>>>>>>>>>
>> >>>>>>>>>> watermarks to the readers, and the readers cannot emit
>> >>>>>>>>>>
>> >>>>>>>>>> watermarks
>> >>>>>>>>>>
>> >>>>>>>>>> beyond
>> >>>>>>>>>>
>> >>>>>>>>>> that received watermark.
>> >>>>>>>>>> - Many split enumerators would simply immediately send
>> >>>>>>>>>>
>> >>>>>>>>>> Long.MAX
>> >>>>>>>>>>
>> >>>>>>>>>> out
>> >>>>>>>>>>
>> >>>>>>>>>> and
>> >>>>>>>>>>
>> >>>>>>>>>> leave the progress purely to the split readers.
>> >>>>>>>>>>
>> >>>>>>>>>> - For event-time alignment / split back pressure, this
>> >>>>>>>>>>
>> >>>>>>>>>> begs
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> question
>> >>>>>>>>>>
>> >>>>>>>>>> how we can avoid deadlocks that may arise when splits
>> >>>>>>>>>>
>> >>>>>>>>>> are
>> >>>>>>>>>>
>> >>>>>>>>>> suspended
>> >>>>>>>>>>
>> >>>>>>>>>> for
>> >>>>>>>>>>
>> >>>>>>>>>> event time back pressure,
>> >>>>>>>>>>
>> >>>>>>>>>> *(7) Batch and streaming Unification*
>> >>>>>>>>>>
>> >>>>>>>>>> - Functionality wise, the above design should support
>> >>>>>>>>>>
>> >>>>>>>>>> both
>> >>>>>>>>>>
>> >>>>>>>>>> - Batch often (mostly) does not care about reading "in
>> >>>>>>>>>>
>> >>>>>>>>>> order"
>> >>>>>>>>>>
>> >>>>>>>>>> and
>> >>>>>>>>>>
>> >>>>>>>>>> generating watermarks
>> >>>>>>>>>>     --> Might use different enumerator logic that is
>> >>>>>>>>>>
>> >>>>>>>>>> more
>> >>>>>>>>>>
>> >>>>>>>>>> locality
>> >>>>>>>>>>
>> >>>>>>>>>> aware
>> >>>>>>>>>>
>> >>>>>>>>>> and ignores event time order
>> >>>>>>>>>>     --> Does not generate watermarks
>> >>>>>>>>>> - Would be great if bounded sources could be
>> >>>>>>>>>>
>> >>>>>>>>>> identified
>> >>>>>>>>>>
>> >>>>>>>>>> at
>> >>>>>>>>>>
>> >>>>>>>>>> compile
>> >>>>>>>>>>
>> >>>>>>>>>> time,
>> >>>>>>>>>>
>> >>>>>>>>>> so that "env.addBoundedSource(...)" is type safe and
>> >>>>>>>>>>
>> >>>>>>>>>> can
>> >>>>>>>>>>
>> >>>>>>>>>> return a
>> >>>>>>>>>>
>> >>>>>>>>>> "BoundedDataStream".
>> >>>>>>>>>> - Possible to defer this discussion until later
>> >>>>>>>>>>
>> >>>>>>>>>> *Miscellaneous Comments*
>> >>>>>>>>>>
>> >>>>>>>>>> - Should the source have a TypeInformation for the
>> >>>>>>>>>>
>> >>>>>>>>>> produced
>> >>>>>>>>>>
>> >>>>>>>>>> type,
>> >>>>>>>>>>
>> >>>>>>>>>> instead
>> >>>>>>>>>>
>> >>>>>>>>>> of a serializer? We need a type information in the
>> >>>>>>>>>>
>> >>>>>>>>>> stream
>> >>>>>>>>>>
>> >>>>>>>>>> anyways, and
>> >>>>>>>>>>
>> >>>>>>>>>> can
>> >>>>>>>>>>
>> >>>>>>>>>> derive the serializer from that. Plus, creating the
>> >>>>>>>>>>
>> >>>>>>>>>> serializer
>> >>>>>>>>>>
>> >>>>>>>>>> should
>> >>>>>>>>>>
>> >>>>>>>>>> respect the ExecutionConfig.
>> >>>>>>>>>>
>> >>>>>>>>>> - The TypeSerializer interface is very powerful but
>> >>>>>>>>>>
>> >>>>>>>>>> also
>> >>>>>>>>>>
>> >>>>>>>>>> not
>> >>>>>>>>>>
>> >>>>>>>>>> easy to
>> >>>>>>>>>>
>> >>>>>>>>>> implement. Its purpose is to handle data super
>> >>>>>>>>>>
>> >>>>>>>>>> efficiently,
>> >>>>>>>>>>
>> >>>>>>>>>> support
>> >>>>>>>>>>
>> >>>>>>>>>> flexible ways of evolution, etc.
>> >>>>>>>>>> For metadata I would suggest to look at the
>> >>>>>>>>>>
>> >>>>>>>>>> SimpleVersionedSerializer
>> >>>>>>>>>>
>> >>>>>>>>>> instead, which is used for example for checkpoint
>> >>>>>>>>>>
>> >>>>>>>>>> master
>> >>>>>>>>>>
>> >>>>>>>>>> hooks,
>> >>>>>>>>>>
>> >>>>>>>>>> or for
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> streaming file sink. I think that is is a good match
>> >>>>>>>>>>
>> >>>>>>>>>> for
>> >>>>>>>>>>
>> >>>>>>>>>> cases
>> >>>>>>>>>>
>> >>>>>>>>>> where
>> >>>>>>>>>>
>> >>>>>>>>>> we
>> >>>>>>>>>>
>> >>>>>>>>>> do
>> >>>>>>>>>>
>> >>>>>>>>>> not need more than ser/deser (no copy, etc.) and don't
>> >>>>>>>>>>
>> >>>>>>>>>> need to
>> >>>>>>>>>>
>> >>>>>>>>>> push
>> >>>>>>>>>>
>> >>>>>>>>>> versioning out of the serialization paths for best
>> >>>>>>>>>>
>> >>>>>>>>>> performance
>> >>>>>>>>>>
>> >>>>>>>>>> (as in
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> TypeSerializer)
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas <
>> >>>>>>>>>>
>> >>>>>>>>>> [hidden email]>
>> >>>>>>>>>>
>> >>>>>>>>>> wrote:
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> Hi Biao,
>> >>>>>>>>>>
>> >>>>>>>>>> Thanks for the answer!
>> >>>>>>>>>>
>> >>>>>>>>>> So given the multi-threaded readers, now we have as
>> >>>>>>>>>>
>> >>>>>>>>>> open
>> >>>>>>>>>>
>> >>>>>>>>>> questions:
>> >>>>>>>>>>
>> >>>>>>>>>> 1) How do we let the checkpoints pass through our
>> >>>>>>>>>>
>> >>>>>>>>>> multi-threaded
>> >>>>>>>>>>
>> >>>>>>>>>> reader
>> >>>>>>>>>>
>> >>>>>>>>>> operator?
>> >>>>>>>>>>
>> >>>>>>>>>> 2) Do we have separate reader and source operators or
>> >>>>>>>>>>
>> >>>>>>>>>> not? In
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> strategy
>> >>>>>>>>>>
>> >>>>>>>>>> that has a separate source, the source operator has a
>> >>>>>>>>>>
>> >>>>>>>>>> parallelism of
>> >>>>>>>>>>
>> >>>>>>>>>> 1
>> >>>>>>>>>>
>> >>>>>>>>>> and
>> >>>>>>>>>>
>> >>>>>>>>>> is responsible for split recovery only.
>> >>>>>>>>>>
>> >>>>>>>>>> For the first one, given also the constraints
>> >>>>>>>>>>
>> >>>>>>>>>> (blocking,
>> >>>>>>>>>>
>> >>>>>>>>>> finite
>> >>>>>>>>>>
>> >>>>>>>>>> queues,
>> >>>>>>>>>>
>> >>>>>>>>>> etc), I do not have an answer yet.
>> >>>>>>>>>>
>> >>>>>>>>>> For the 2nd, I think that we should go with separate
>> >>>>>>>>>>
>> >>>>>>>>>> operators
>> >>>>>>>>>>
>> >>>>>>>>>> for
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> source and the readers, for the following reasons:
>> >>>>>>>>>>
>> >>>>>>>>>> 1) This is more aligned with a potential future
>> >>>>>>>>>>
>> >>>>>>>>>> improvement
>> >>>>>>>>>>
>> >>>>>>>>>> where the
>> >>>>>>>>>>
>> >>>>>>>>>> split
>> >>>>>>>>>>
>> >>>>>>>>>> discovery becomes a responsibility of the JobManager
>> >>>>>>>>>>
>> >>>>>>>>>> and
>> >>>>>>>>>>
>> >>>>>>>>>> readers are
>> >>>>>>>>>>
>> >>>>>>>>>> pooling more work from the JM.
>> >>>>>>>>>>
>> >>>>>>>>>> 2) The source is going to be the "single point of
>> >>>>>>>>>>
>> >>>>>>>>>> truth".
>> >>>>>>>>>>
>> >>>>>>>>>> It
>> >>>>>>>>>>
>> >>>>>>>>>> will
>> >>>>>>>>>>
>> >>>>>>>>>> know
>> >>>>>>>>>>
>> >>>>>>>>>> what
>> >>>>>>>>>>
>> >>>>>>>>>> has been processed and what not. If the source and the
>> >>>>>>>>>>
>> >>>>>>>>>> readers
>> >>>>>>>>>>
>> >>>>>>>>>> are a
>> >>>>>>>>>>
>> >>>>>>>>>> single
>> >>>>>>>>>>
>> >>>>>>>>>> operator with parallelism > 1, or in general, if the
>> >>>>>>>>>>
>> >>>>>>>>>> split
>> >>>>>>>>>>
>> >>>>>>>>>> discovery
>> >>>>>>>>>>
>> >>>>>>>>>> is
>> >>>>>>>>>>
>> >>>>>>>>>> done by each task individually, then:
>> >>>>>>>>>>    i) we have to have a deterministic scheme for each
>> >>>>>>>>>>
>> >>>>>>>>>> reader to
>> >>>>>>>>>>
>> >>>>>>>>>> assign
>> >>>>>>>>>>
>> >>>>>>>>>> splits to itself (e.g. mod subtaskId). This is not
>> >>>>>>>>>>
>> >>>>>>>>>> necessarily
>> >>>>>>>>>>
>> >>>>>>>>>> trivial
>> >>>>>>>>>>
>> >>>>>>>>>> for
>> >>>>>>>>>>
>> >>>>>>>>>> all sources.
>> >>>>>>>>>>    ii) each reader would have to keep a copy of all its
>> >>>>>>>>>>
>> >>>>>>>>>> processed
>> >>>>>>>>>>
>> >>>>>>>>>> slpits
>> >>>>>>>>>>
>> >>>>>>>>>>    iii) the state has to be a union state with a
>> >>>>>>>>>>
>> >>>>>>>>>> non-trivial
>> >>>>>>>>>>
>> >>>>>>>>>> merging
>> >>>>>>>>>>
>> >>>>>>>>>> logic
>> >>>>>>>>>>
>> >>>>>>>>>> in order to support rescaling.
>> >>>>>>>>>>
>> >>>>>>>>>> Two additional points that you raised above:
>> >>>>>>>>>>
>> >>>>>>>>>> i) The point that you raised that we need to keep all
>> >>>>>>>>>>
>> >>>>>>>>>> splits
>> >>>>>>>>>>
>> >>>>>>>>>> (processed
>> >>>>>>>>>>
>> >>>>>>>>>> and
>> >>>>>>>>>>
>> >>>>>>>>>> not-processed) I think is a bit of a strong
>> >>>>>>>>>>
>> >>>>>>>>>> requirement.
>> >>>>>>>>>>
>> >>>>>>>>>> This
>> >>>>>>>>>>
>> >>>>>>>>>> would
>> >>>>>>>>>>
>> >>>>>>>>>> imply
>> >>>>>>>>>>
>> >>>>>>>>>> that for infinite sources the state will grow
>> >>>>>>>>>>
>> >>>>>>>>>> indefinitely.
>> >>>>>>>>>>
>> >>>>>>>>>> This is
>> >>>>>>>>>>
>> >>>>>>>>>> problem
>> >>>>>>>>>>
>> >>>>>>>>>> is even more pronounced if we do not have a single
>> >>>>>>>>>>
>> >>>>>>>>>> source
>> >>>>>>>>>>
>> >>>>>>>>>> that
>> >>>>>>>>>>
>> >>>>>>>>>> assigns
>> >>>>>>>>>>
>> >>>>>>>>>> splits to readers, as each reader will have its own
>> >>>>>>>>>>
>> >>>>>>>>>> copy
>> >>>>>>>>>>
>> >>>>>>>>>> of
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> state.
>> >>>>>>>>>>
>> >>>>>>>>>> ii) it is true that for finite sources we need to
>> >>>>>>>>>>
>> >>>>>>>>>> somehow
>> >>>>>>>>>>
>> >>>>>>>>>> not
>> >>>>>>>>>>
>> >>>>>>>>>> close
>> >>>>>>>>>>
>> >>>>>>>>>> the
>> >>>>>>>>>>
>> >>>>>>>>>> readers when the source/split discoverer finishes. The
>> >>>>>>>>>> ContinuousFileReaderOperator has a work-around for
>> >>>>>>>>>>
>> >>>>>>>>>> that.
>> >>>>>>>>>>
>> >>>>>>>>>> It is
>> >>>>>>>>>>
>> >>>>>>>>>> not
>> >>>>>>>>>>
>> >>>>>>>>>> elegant,
>> >>>>>>>>>>
>> >>>>>>>>>> and checkpoints are not emitted after closing the
>> >>>>>>>>>>
>> >>>>>>>>>> source,
>> >>>>>>>>>>
>> >>>>>>>>>> but
>> >>>>>>>>>>
>> >>>>>>>>>> this, I
>> >>>>>>>>>>
>> >>>>>>>>>> believe, is a bigger problem which requires more
>> >>>>>>>>>>
>> >>>>>>>>>> changes
>> >>>>>>>>>>
>> >>>>>>>>>> than
>> >>>>>>>>>>
>> >>>>>>>>>> just
>> >>>>>>>>>>
>> >>>>>>>>>> refactoring the source interface.
>> >>>>>>>>>>
>> >>>>>>>>>> Cheers,
>> >>>>>>>>>> Kostas
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>>
>> >>>>>>>>>> --
>> >>>>>>>>>> Best, Jingsong Lee
>> >>>>>>>>
>> >>>>>>>>
>> >>>>>>>
>> >>>>>>
>> >>>>>>
>> >>>>>> --
>> >>>>>> Best, Jingsong Lee
>> >>>>>>
>> >>>>>
>> >>>>
>> >>>>
>> >>>
>> >>
>> >
>>
>>