[ANNOUNCE] Apache Flink 1.4.1 released

[Tzu-Li (Gordon) Tai]

The Apache Flink community is very happy to announce the release of Apache Flink 1.4.1, which is the first bugfix release for the Apache Flink 1.4 series.

Apache Flink® is an open-source stream processing framework for distributed, high-performing, always-available, and accurate data streaming applications.

The release is available for download at:
https://flink.apache.org/downloads.html

Please check out the release blog post for an overview of the improvements for this bugfix release:
https://flink.apache.org/news/2018/02/15/release-1.4.1.html

The full release notes are available in Jira:
https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12315522&version=12342212

We would like to thank all contributors of the Apache Flink community who made this release possible!

Cheers,
Gordon

[bowen.li]

Congratulations everyone!

On Thu, Feb 15, 2018 at 10:04 AM, Tzu-Li (Gordon) Tai <[hidden email]>
wrote:

> The Apache Flink community is very happy to announce the release of Apache
> Flink 1.4.1, which is the first bugfix release for the Apache Flink 1.4
> series.
>
>
> Apache Flink® is an open-source stream processing framework for
> distributed, high-performing, always-available, and accurate data streaming
> applications.
>
>
> The release is available for download at:
>
> https://flink.apache.org/downloads.html
>
>
> Please check out the release blog post for an overview of the improvements
> for this bugfix release:
>
> https://flink.apache.org/news/2018/02/15/release-1.4.1.html
>
>
> The full release notes are available in Jira:
>
> https://issues.apache.org/jira/secure/ReleaseNote.jspa?
> projectId=12315522&version=12342212
>
>
> We would like to thank all contributors of the Apache Flink community who
> made this release possible!
>
>
> Cheers,
>
> Gordon
>
>

[Carsten]

Hello all,

for some of our sensor data we would like to aggregate data for 10sec,
30sec, 1 min etc., thus conceptually have multiple windows on a single
stream. Currently, I am simply duplicating the data stream (separate
execution environments etc) and process each of the required windows. Is
there a better way? I heard about cascading windows but I am not sure if
this approach exits, needs to implemented from scratch,  or how to use it.


Any link/hint/suggestion, would be greatly appreciated.


Have a great day,

Carsten

[Alexx]

Dear Carsten,

Maybe you need a window with multiple triggers.

Best,
Alex.

On 17 February 2018 at 01:39, Carsten <[hidden email]>
wrote:

> Hello all,
>
> for some of our sensor data we would like to aggregate data for 10sec,
> 30sec, 1 min etc., thus conceptually have multiple windows on a single
> stream. Currently, I am simply duplicating the data stream (separate
> execution environments etc) and process each of the required windows. Is
> there a better way? I heard about cascading windows but I am not sure if
> this approach exits, needs to implemented from scratch,  or how to use it.
>
>
> Any link/hint/suggestion, would be greatly appreciated.
>
>
> Have a great day,
>
> Carsten
>

[Aljoscha Krettek-2]

Hi Carsten,

If you're using event-time windowing you can do something like this:

souce = env.addSource(...)

window1 = source
  .keyBy()
  .window(10 sec)
  .aggregate()/reduce()

window1.addSink(...)

window2 = window1
  .keyBy()
  .windwo(30 sec)
  .aggregate()/reduce()

window2.addSink(...)

And so on...

Does this solve your problem?

Best,
Aljoscha

> On 17. Feb 2018, at 09:40, Alexandru Gutan <[hidden email]> wrote:
>
> Dear Carsten,
>
> Maybe you need a window with multiple triggers.
>
> Best,
> Alex.
>
> On 17 February 2018 at 01:39, Carsten <[hidden email]>
> wrote:
>
>> Hello all,
>>
>> for some of our sensor data we would like to aggregate data for 10sec,
>> 30sec, 1 min etc., thus conceptually have multiple windows on a single
>> stream. Currently, I am simply duplicating the data stream (separate
>> execution environments etc) and process each of the required windows. Is
>> there a better way? I heard about cascading windows but I am not sure if
>> this approach exits, needs to implemented from scratch,  or how to use it.
>>
>>
>> Any link/hint/suggestion, would be greatly appreciated.
>>
>>
>> Have a great day,
>>
>> Carsten
>>

[Stephan Ewen]

Great, thanks a lot for being the release manager, Gordon!

On Fri, Feb 16, 2018 at 12:54 AM, Hao Sun <[hidden email]> wrote:

> This is great!
>
> On Thu, Feb 15, 2018 at 2:50 PM Bowen Li <[hidden email]> wrote:
>
>> Congratulations everyone!
>>
>> On Thu, Feb 15, 2018 at 10:04 AM, Tzu-Li (Gordon) Tai <
>> [hidden email]> wrote:
>>
>>> The Apache Flink community is very happy to announce the release of
>>> Apache Flink 1.4.1, which is the first bugfix release for the Apache Flink
>>> 1.4 series.
>>>
>>>
>>> Apache Flink® is an open-source stream processing framework for
>>> distributed, high-performing, always-available, and accurate data streaming
>>> applications.
>>>
>>>
>>> The release is available for download at:
>>>
>>> https://flink.apache.org/downloads.html
>>>
>>>
>>> Please check out the release blog post for an overview of the
>>> improvements for this bugfix release:
>>>
>>> https://flink.apache.org/news/2018/02/15/release-1.4.1.html
>>>
>>>
>>> The full release notes are available in Jira:
>>>
>>> https://issues.apache.org/jira/secure/ReleaseNote.jspa?
>>> projectId=12315522&version=12342212
>>>
>>>
>>> We would like to thank all contributors of the Apache Flink community
>>> who made this release possible!
>>>
>>>
>>> Cheers,
>>>
>>> Gordon
>>>
>>>
>>