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https://issues.apache.org/jira/browse/SPARK-11181?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14968645#comment-14968645
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prakhar jauhari commented on SPARK-11181:
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Hey [~saisai_shao], this jira is for the issue on spark-1.3.1 branch and the
issue still exists on the branch.
We are currently using spark -1.3.1 in production so moving to 1.5 is not a
option right now. I am currently working to back-port the fix in SPARK-8119 to
spark-1.3.1. I'll create a PR for the same (just in case some one needs the fix
on spark -1.3.1).
Will close this jira after that.
> Spark Yarn : Spark reducing total executors count even when Dynamic
> Allocation is disabled.
> -------------------------------------------------------------------------------------------
>
> Key: SPARK-11181
> URL: https://issues.apache.org/jira/browse/SPARK-11181
> Project: Spark
> Issue Type: Bug
> Components: Scheduler, Spark Core, YARN
> Affects Versions: 1.3.1
> Environment: Spark-1.3.1 on hadoop-yarn-2.4.0 cluster.
> All servers in cluster running Linux version 2.6.32.
> Job in yarn-client mode.
> Reporter: prakhar jauhari
>
> Spark driver reduces total executors count even when Dynamic Allocation is
> not enabled.
> To reproduce this:
> 1. A 2 node yarn setup : each DN has ~ 20GB mem and 4 cores.
> 2. When the application launches and gets it required executors, One of the
> DN's losses connectivity and is timed out.
> 3. Spark issues a killExecutor for the executor on the DN which was timed
> out.
> 4. Even with dynamic allocation off, spark's scheduler reduces the
> "targetNumExecutors".
> 5. Thus the job runs with reduced executor count.
> Note : The severity of the issue increases : If some of the DN that were
> running my job's executors lose connectivity intermittently, spark scheduler
> reduces "targetNumExecutors", thus not asking for new executors on any other
> nodes, causing the job to hang.
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