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https://issues.apache.org/jira/browse/YARN-2041?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14012134#comment-14012134
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Nishkam Ravi commented on YARN-2041:
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Sure. There seem to be multiple issues. Two seem to clearly stand out:
1. Performance degrades with FIFO for large values of memory-mb in both
single-job and multi-job mode. Observed for multiple benchmarks including
TeraSort, TeraValidate, TeraGen, WordCount, ShuffleText. Issue: FIFO seems to
be allocating too many jobs at once on a single node.
2. Performance with Capacity scheduler suffers for large values of memory-mb
only for TeraValidate (in single-job mode). Issue: why does Capacity scheduler
regress for TeraValidate?
> 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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