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https://issues.apache.org/jira/browse/SPARK-12650?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15086135#comment-15086135
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John Vines commented on SPARK-12650:
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{code}[root@datanode1-systemtest-john-1 /]# java -XX:+PrintFlagsFinal -version
| grep HeapSize
uintx ErgoHeapSizeLimit = 0 {product}
uintx HeapSizePerGCThread = 87241520 {product}
uintx InitialHeapSize := 525375744 {product}
uintx LargePageHeapSizeThreshold = 134217728 {product}
uintx MaxHeapSize := 8407482368 {product}
java version "1.7.0_80"
Java(TM) SE Runtime Environment (build 1.7.0_80-b15)
Java HotSpot(TM) 64-Bit Server VM (build 24.80-b11, mixed mode)
{code}
> 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
> Components: Spark Submit
> 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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