Do you still run into the "java.lang.OutOfMemoryError: Java heap space"?
If not, then you don't really need to worry about the committed memory.
It is the maximum that really matters. The committed memory should increase
automatically when it's needed.
Thank you~
Xintong Song
On Fri, Jun 12, 2020 at 2:24 PM Ramya Ramamurthy <hair...@gmail.com> wrote:
> Hi Xintong,
>
> Thanks for the quick response.
>
> I have kept my task manager memory to be 1.5GB. But still seeing the Heap
> committed metric to be around 54MB or so. Why does this happen ? Should I
> configure any memory fraction configurations here ?
>
> Thanks.
>
> On Fri, Jun 12, 2020 at 10:58 AM Xintong Song <tonysong...@gmail.com>
> wrote:
>
> > Hi Ramya,
> >
> > Increasing the memory of your pod will not give you more JVM heap space.
> > You will need to configure Flink so it launches the JVM process with more
> > memory.
> >
> > In Flink 1.7, this could be achieved by configuring
> 'jobmanager.heap.size'
> > & 'taskmanager.heap.size' in your 'flink-conf.yaml'. Both of them are by
> > default 1024m.
> >
> > Please also note that, you should not configure these two options two as
> > large as your Kubernetes pod. Because Flink may also have some off-heap
> > memory overhead, so the total memory consumed by the Flink processes
> might
> > be larger than configured. This may cause your pods getting killed by
> > Kubernetes due to memory exceeding.
> >
> > According to our experience, leaving around 20~25% of your pod memory for
> > such overhead might be a good practice. In your case, that means
> > configuring 'taskmanager.heap.size' to 4GB. If RocksDB is used in your
> > workload, you may need to further increase the off-heap memory size.
> >
> > Thank you~
> >
> > Xintong Song
> >
> >
> >
> > On Fri, Jun 12, 2020 at 1:11 PM Ramya Ramamurthy <hair...@gmail.com>
> > wrote:
> >
> > > Thanks Till.
> > > Actually, i have around 5GB pods for each TM, and each pod with only
> one
> > > slot.
> > > But the metrics i have pulled is as below, which is slightly confusing.
> > > It says only ~50MB of Heap is committed for the tasks. Would you be
> able
> > > to point me to the right configuration to be set.
> > >
> > > Thanks
> > > ~Ramya.
> > >
> > > [image: image.png]
> > >
> > > On Tue, Jun 9, 2020 at 3:12 PM Till Rohrmann <trohrm...@apache.org>
> > wrote:
> > >
> > >> Hi Ramya,
> > >>
> > >> it looks as if you should give your Flink pods and also the Flink
> > process
> > >> a
> > >> bit more memory as the process fails with an out of memory error. You
> > >> could
> > >> also try Flink's latest version which comes with native Kubernetes
> > >> support.
> > >>
> > >> Cheers,
> > >> Till
> > >>
> > >> On Tue, Jun 9, 2020 at 8:45 AM Ramya Ramamurthy <hair...@gmail.com>
> > >> wrote:
> > >>
> > >> > Hi,
> > >> >
> > >> > My flink jobs are constantly going down beyond an hour with the
> below
> > >> > exception.
> > >> > This is Flink 1.7 on kubes, with checkpoints to Google storage.
> > >> >
> > >> > AsynchronousException{java.lang.Exception: Could not materialize
> > >> > checkpoint 21 for operator Source: Kafka011TableSource(sid, _zpsbd3,
> > >> > _zpsbd4, _zpsbd6, _zpsbd7, _zpsbd9, lvl_1, isBot, botcode, ssresp,
> > >> > reason, ts) -> from: (sid, _zpsbd3, _zpsbd6, ts) ->
> > >> > Timestamps/Watermarks -> where: (<>(sid, _UTF-16LE'7759')), select:
> > >> > (sid, _zpsbd3, _zpsbd6, ts) -> time attribute: (ts) (5/6).}
> > >> > at
> > >> >
> > >>
> >
> org.apache.flink.streaming.runtime.tasks.StreamTask$AsyncCheckpointExceptionHandler.tryHandleCheckpointException(StreamTask.java:1153)
> > >> > at
> > >> >
> > >>
> >
> org.apache.flink.streaming.runtime.tasks.StreamTask$AsyncCheckpointRunnable.handleExecutionException(StreamTask.java:947)
> > >> > at
> > >> >
> > >>
> >
> org.apache.flink.streaming.runtime.tasks.StreamTask$AsyncCheckpointRunnable.run(StreamTask.java:884)
> > >> > at
> > >> >
> > java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
> > >> > at java.util.concurrent.FutureTask.run(FutureTask.java:266)
> > >> > at
> > >> >
> > >>
> >
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> > >> > at
> > >> >
> > >>
> >
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> > >> > at java.lang.Thread.run(Thread.java:748)
> > >> > Caused by: java.lang.Exception: Could not materialize checkpoint 21
> > >> > for operator Source: Kafka011TableSource(sid, _zpsbd3, _zpsbd4,
> > >> > _zpsbd6, _zpsbd7, _zpsbd9, lvl_1, isBot, botcode, ssresp, reason,
> ts)
> > >> > -> from: (sid, _zpsbd3, _zpsbd6, ts) -> Timestamps/Watermarks ->
> > >> > where: (<>(sid, _UTF-16LE'7759')), select: (sid, _zpsbd3, _zpsbd6,
> ts)
> > >> > -> time attribute: (ts) (5/6).
> > >> > at
> > >> >
> > >>
> >
> org.apache.flink.streaming.runtime.tasks.StreamTask$AsyncCheckpointRunnable.handleExecutionException(StreamTask.java:942)
> > >> > ... 6 more
> > >> > Caused by: java.util.concurrent.ExecutionException:
> > >> > java.lang.OutOfMemoryError: Java heap space
> > >> > at
> java.util.concurrent.FutureTask.report(FutureTask.java:122)
> > >> > at java.util.concurrent.FutureTask.get(FutureTask.java:192)
> > >> > at
> > >> >
> > org.apache.flink.util.FutureUtil.runIfNotDoneAndGet(FutureUtil.java:53)
> > >> > at
> > >> >
> > >>
> >
> org.apache.flink.streaming.api.operators.OperatorSnapshotFinalizer.<init>(OperatorSnapshotFinalizer.java:53)
> > >> > at
> > >> >
> > >>
> >
> org.apache.flink.streaming.runtime.tasks.StreamTask$AsyncCheckpointRunnable.run(StreamTask.java:853)
> > >> > ... 5 more
> > >> > Caused by: java.lang.OutOfMemoryError: Java heap space
> > >> > at
> > >> >
> > >>
> >
> com.google.cloud.hadoop.repackaged.gcs.com.google.api.client.googleapis.media.MediaHttpUploader.buildContentChunk(MediaHttpUploader.java:609)
> > >> > at
> > >> >
> > >>
> >
> com.google.cloud.hadoop.repackaged.gcs.com.google.api.client.googleapis.media.MediaHttpUploader.resumableUpload(MediaHttpUploader.java:408)
> > >> > at
> > >> >
> > >>
> >
> com.google.cloud.hadoop.repackaged.gcs.com.google.api.client.googleapis.media.MediaHttpUploader.upload(MediaHttpUploader.java:336)
> > >> > at
> > >> >
> > >>
> >
> com.google.cloud.hadoop.repackaged.gcs.com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(AbstractGoogleClientRequest.java:558)
> > >> > at
> > >> >
> > >>
> >
> com.google.cloud.hadoop.repackaged.gcs.com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(AbstractGoogleClientRequest.java:482)
> > >> > at
> > >> >
> > >>
> >
> com.google.cloud.hadoop.repackaged.gcs.com.google.api.client.googleapis.services.AbstractGoogleClientRequest.execute(AbstractGoogleClientRequest.java:599)
> > >> > at
> > >> >
> > >>
> >
> com.google.cloud.hadoop.repackaged.gcs.com.google.cloud.hadoop.util.AbstractGoogleAsyncWriteChannel$UploadOperation.call(AbstractGoogleAsyncWriteChannel.java:272)
> > >> > ... 4 more
> > >> >
> > >> >
> > >> >
> > >> > Any help here in understanding this would be highly appreciated.
> > >> >
> > >> >
> > >> > Thanks.
> > >> >
> > >>
> > >
> >
>
