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https://issues.apache.org/jira/browse/SPARK-21656?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16117241#comment-16117241
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Thomas Graves commented on SPARK-21656:
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As a said above it DOES help the application to keep them alive. the scheduler
logic will fall back to them at some point when it goes to rack/any locality or
when it finishes the tasks that are getting locality on those few nodes. Thus
why I'm saying its a conflict within spark.
SPARK should be resilient to any weird things happening. In the cases I have
described we could actually release all of our executors and never ask for more
within a stage, that is a BUG. We can change the configs to make it so that
doesn't normally happen but a user could change them back and when they do that
it shouldn't result in a deadlock.
> spark dynamic allocation should not idle timeout executors when tasks still
> to run
> ----------------------------------------------------------------------------------
>
> Key: SPARK-21656
> URL: https://issues.apache.org/jira/browse/SPARK-21656
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.1.1
> Reporter: Jong Yoon Lee
> Fix For: 2.1.1
>
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> Right now spark lets go of executors when they are idle for the 60s (or
> configurable time). I have seen spark let them go when they are idle but they
> were really needed. I have seen this issue when the scheduler was waiting to
> get node locality but that takes longer then the default idle timeout. In
> these jobs the number of executors goes down really small (less than 10) but
> there are still like 80,000 tasks to run.
> We should consider not allowing executors to idle timeout if they are still
> needed according to the number of tasks to be run.
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