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https://issues.apache.org/jira/browse/MAPREDUCE-2905?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jeff Bean updated MAPREDUCE-2905:
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Description:
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.
was:
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 jobs can set a param similar to
mapred.fairscheduler.assignmultiple on submission to better control the task
distribution of a particular job.
> 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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