Yun Tang created FLINK-19125:
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Summary: Avoid memory fragmentation when running flink docker image
Key: FLINK-19125
URL:
https://issues.apache.org/jira/browse/FLINK-19125 Project: Flink
Issue Type: Improvement
Components: Deployment / Kubernetes, Runtime / State Backends
Affects Versions: 1.11.1
Reporter: Yun Tang
This ticket tracks the problem of memory fragmentation when launching default Flink docker image.
In FLINK-18712, user reported if he submits job with rocksDB state backend on a k8s session cluster again and again once it finished, the memory usage of task manager grows continuously until OOM killed.
I reproduce this problem with official Flink docker image no matter how we use rocksDB (whether to enable managed memory).
I dig into the problem and found this is due to the memory fragmentation caused by {{glibc}}, which would not return memory to kernel gracefully (please refer to [glibc bugzilla|
https://sourceware.org/bugzilla/show_bug.cgi?id=15321] and [glibc manual|
https://www.gnu.org/software/libc/manual/html_mono/libc.html#Freeing-after-Malloc])
I found if limiting MALLOC_ARENA_MAX to 2 could mitigate this problem (please refer to [choose-for-malloc_arena_max|
https://devcenter.heroku.com/articles/tuning-glibc-memory-behavior#what-value-to-choose-for-malloc_arena_max] for more details).
And if we choose to use jemalloc to allocate memory via rebuilding another docker image, the problem would be gone.
{code:java}
apt-get -y install libjemalloc-dev
ENV LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libjemalloc.so
{code}
Jemalloc intends to [emphasize fragmentation avoidance|
https://github.com/jemalloc/jemalloc /wiki/Background#intended-use] and we might consider to re-factor our Dockerfile to base on jemalloc to avoid memory fragmentation.
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