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https://issues.apache.org/jira/browse/MAPREDUCE-2905?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13093036#comment-13093036
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Todd Lipcon commented on MAPREDUCE-2905:
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There's code in the fair scheduler which tries to avoid doing this. I think
something is broken about it, currently, though, since I've heard many people
report the same behavior. Look at CapBasedLoadManager.java.
Either way, I don't think doing this per-job is the right solution - better to
avoid exposing the config, and just Do The Right Thing.
> Allow mapred.fairscheduler.assignmultple to be set per job
> ----------------------------------------------------------
>
> Key: MAPREDUCE-2905
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-2905
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Components: contrib/fair-share
> Affects Versions: 0.20.2
> Reporter: Jeff Bean
>
> We encountered a situation where in the same cluster, large jobs benefit from
> mapred.fairscheduler.assignmultiple, but small jobs with small numbers of
> mappers do not: the mappers all clump to fully occupy just a few nodes, which
> causes those nodes to saturate and bottleneck. The desired behavior is to
> spread the job across more nodes so that a relatively small job doesn't
> saturate any node in the cluster.
> Testing has shown that setting mapred.fairscheduler.assignmultiple to false
> gives the desired behavior for small jobs, but is unnecessary for large jobs.
> However, since this is a cluster-wide setting, we can't properly tune.
> It'd be nice if jobs can set a param similar to
> mapred.fairscheduler.assignmultiple on submission to better control the task
> distribution of a particular job.
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