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https://issues.apache.org/jira/browse/SPARK-21383?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Marcelo Vanzin resolved SPARK-21383.
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Resolution: Fixed
Assignee: DjvuLee
Fix Version/s: 2.3.0
2.2.1
> YARN can allocate too many executors
> ------------------------------------
>
> Key: SPARK-21383
> URL: https://issues.apache.org/jira/browse/SPARK-21383
> Project: Spark
> Issue Type: Bug
> Components: YARN
> Affects Versions: 2.0.0
> Reporter: Thomas Graves
> Assignee: DjvuLee
> Fix For: 2.2.1, 2.3.0
>
>
> The YarnAllocator doesn't properly track containers being launched but not
> yet running. If it takes time to launch the containers on the NM they don't
> show up as numExecutorsRunning, but they are already out of the Pending list,
> so if the allocateResources call happens again it can think it has missing
> executors even when it doesn't (they just haven't been launched yet).
> This was introduced by SPARK-12447
> Where it check for missing:
> https://github.com/apache/spark/blob/master/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala#L297
> Only updates the numRunningExecutors after NM has started it:
> https://github.com/apache/spark/blob/master/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala#L524
> Thus if the NM is slow or the network is slow, it can miscount and start
> additional executors.
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