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https://issues.apache.org/jira/browse/YARN-4714?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16726879#comment-16726879
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Andres Namm commented on YARN-4714:
-----------------------------------
I have built another answer which depends whether you are using spark client or
cluster mode.
* In cluster mode it failed when I specified *Driver Memory* --driver-memory
to be 512m. (The default setting requested 2GB of am resources (This consists
of driver memory + Overhead requested for Application Master) which was enough)
* In client mode the setting that mattered was spark.yarn.am.memory as by
default this requested only 1024m for the AM which is too little as Java 8
requires a lot of virtual memory. > 1024m seemed to be working.
Answer is described
[here|https://github.com/AndresNamm/SparkConfAndDebugging/blob/master/Debug/SparkMemoryIssue.md]
> [Java 8] Over usage of virtual memory
> -------------------------------------
>
> Key: YARN-4714
> URL: https://issues.apache.org/jira/browse/YARN-4714
> Project: Hadoop YARN
> Issue Type: Bug
> Reporter: Mohammad Kamrul Islam
> Assignee: Mohammad Kamrul Islam
> Priority: Blocker
> Attachments: HADOOP-11364.01.patch
>
>
> In our Hadoop 2 + Java8 effort , we found few jobs are being Killed by Hadoop
> due to excessive virtual memory allocation. Although the physical memory
> usage is low.
> The most common error message is "Container [pid=??,containerID=container_??]
> is running beyond virtual memory limits. Current usage: 365.1 MB of 1 GB
> physical memory used; 3.2 GB of 2.1 GB virtual memory used. Killing
> container."
> We see this problem for MR job as well as in spark driver/executor.
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