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https://issues.apache.org/jira/browse/SPARK-6737?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Josh Rosen updated SPARK-6737:
------------------------------
    Affects Version/s: 1.3.1
             Assignee: Josh Rosen

This bug is present in Spark 1.3+.  The problem lies in the interaction between 
DAGScheduler and OutputCommitCoordinator.  DAGScheduler only informs the 
OutputCommitCoordinator of stage completion for one of the less-common paths in 
which stages are marked as completed, whereas we should be calling it for every 
stage completion event.

This should be pretty easy to fix with a patch to the DAGScheduler, so I'll 
work on putting one together shortly.

> OutputCommitCoordinator.authorizedCommittersByStage map out of memory
> ---------------------------------------------------------------------
>
>                 Key: SPARK-6737
>                 URL: https://issues.apache.org/jira/browse/SPARK-6737
>             Project: Spark
>          Issue Type: Bug
>          Components: Scheduler, Spark Core, Streaming
>    Affects Versions: 1.3.0, 1.3.1
>         Environment: spark 1.3.1
>            Reporter: Tao Li
>            Assignee: Josh Rosen
>            Priority: Critical
>              Labels: Bug, Core, DAGScheduler, OOM, Streaming
>
> I am using spark streaming(1.3.1)  as a long time running service and out of 
> memory after running for 7 days. 
> I found that the field authorizedCommittersByStage in OutputCommitCoordinator 
> class cause the OOM. 
> authorizedCommittersByStage is a map, key is StageId, value is 
> Map[PartitionId, TaskAttemptId]. The OutputCommitCoordinator class has a 
> method stageEnd which will remove stageId from authorizedCommittersByStage. 
> But the method stageEnd is never called by DAGSchedule. And it cause the 
> authorizedCommittersByStage's stage info never be cleaned, which cause OOM.
> It happens in my spark streaming program(1.3.1), I am not sure if it will 
> appear in other spark components and other spark version.



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