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https://issues.apache.org/jira/browse/SPARK-10790?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14906912#comment-14906912
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Jonathan Kelly commented on SPARK-10790:
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I can reproduce it with minExecutors=N and initialExecutors=unset and having
the job's first stage require <= N tasks. I just realized that for some reason
I can't reproduce it with minExecutors=N and initialExecutors=N, even though
that should be the same as minExecutors=N and initialExecutors=unset, right?
Anyway, please try the following:
spark-submit -c spark.dynamicAllocation.minExecutors=1 --class
org.apache.spark.examples.SparkPi spark-examples-1.5.0-hadoop2.6.0.jar 1
This one hangs for me.
This one does not:
spark-submit -c spark.dynamicAllocation.minExecutors=1 -c
spark.dynamicAllocation.initialExecutors=1 --class
org.apache.spark.examples.SparkPi spark-examples-1.5.0-hadoop2.6.0.jar 1
So maybe the problem has more to do with a hang being possible if
initialExecutors is left unset?
> Dynamic Allocation does not request any executors if first stage needs less
> than or equal to spark.dynamicAllocation.initialExecutors
> -------------------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-10790
> URL: https://issues.apache.org/jira/browse/SPARK-10790
> Project: Spark
> Issue Type: Bug
> Components: Scheduler
> Affects Versions: 1.5.0
> Reporter: Jonathan Kelly
>
> If you set spark.dynamicAllocation.initialExecutors > 0 (or
> spark.dynamicAllocation.minExecutors, since
> spark.dynamicAllocation.initialExecutors defaults to
> spark.dynamicAllocation.minExecutors), and the number of tasks in the first
> stage of your job is less than or equal to this min/init number of executors,
> dynamic allocation won't actually request any executors and will just hang
> indefinitely with the warning "Initial job has not accepted any resources;
> check your cluster UI to ensure that workers are registered and have
> sufficient resources".
> The cause appears to be that ExecutorAllocationManager does not request any
> executors while the application is still initializing, but it still sets the
> initial value of numExecutorsTarget to
> spark.dynamicAllocation.initialExecutors. Once the job is running and has
> submitted its first task, if the first task does not need more than
> spark.dynamicAllocation.initialExecutors,
> ExecutorAllocationManager.updateAndSyncNumExecutorsTarget() does not think
> that it needs to request any executors, so it doesn't.
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