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https://issues.apache.org/jira/browse/YARN-2041?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14000601#comment-14000601
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Karthik Kambatla commented on YARN-2041:
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yarn.nodemanager.resource.memory-mb should ideally be fixed per node in a YARN
cluster. As [~tgaves] said, we should look at how the individual tasks are
scheduled (spread out) and other relevant information.
> Hard to co-locate MR2 and Spark jobs on the same cluster in YARN
> ----------------------------------------------------------------
>
> Key: YARN-2041
> URL: https://issues.apache.org/jira/browse/YARN-2041
> Project: Hadoop YARN
> Issue Type: Improvement
> Components: nodemanager
> Affects Versions: 2.3.0
> Reporter: Nishkam Ravi
>
> Performance of MR2 jobs falls drastically as YARN config parameter
> yarn.nodemanager.resource.memory-mb is increased beyond a certain value.
> Performance of Spark falls drastically as the value of
> yarn.nodemanager.resource.memory-mb is decreased beyond a certain value for a
> large data set.
> This makes it hard to co-locate MR2 and Spark jobs in YARN.
> The experiments are being conducted on a 6-node cluster. The following
> workloads are being run: TeraGen, TeraSort, TeraValidate, WordCount,
> ShuffleText and PageRank.
> Will add more details to this JIRA over time.
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