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https://issues.apache.org/jira/browse/SPARK-12650?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15084497#comment-15084497
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Saisai Shao commented on SPARK-12650:
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[~vines], what is your meaning of "SparkSubmit does not Xmx itself at all",
what do you mean by "itself", client, or driver? Can't be worked with
{{spark.driver.memory}}?
For the yarn-client mode, driver is not managed by YARN, it is a local JVM
process managed by yourself, so {{spark.driver.memory}} control the memory size
of this process, the memory of AM is controlled by {{spark.yarn.am.memory}}.
I'm not exactly know what actual your problem it is, can you elaborate it, like
Spark version, your configurations...
> No means to specify Xmx settings for SparkSubmit in yarn-cluster mode
> ---------------------------------------------------------------------
>
> Key: SPARK-12650
> URL: https://issues.apache.org/jira/browse/SPARK-12650
> Project: Spark
> Issue Type: Bug
> Affects Versions: 1.5.2
> Environment: Hadoop 2.6.0
> Reporter: John Vines
>
> Background-
> I have an app master designed to do some work and then launch a spark job.
> Issue-
> If I use yarn-cluster, then the SparkSubmit does not Xmx itself at all,
> leading to the jvm taking a default heap which is relatively large. This
> causes a large amount of vmem to be taken, so that it is killed by yarn. This
> can be worked around by disabling Yarn's vmem check, but that is a hack.
> If I run it in yarn-client mode, it's fine as long as my container has enough
> space for the driver, which is manageable. But I feel that the utter lack of
> Xmx settings for what I believe is a very small jvm is a problem.
> I believe this was introduced with the fix for SPARK-3884
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