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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.
It'd be nice developers can set a param similar to
mapred.fairscheduler.assignmultiple on a per-job basis to better control the
task allocation 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
round-robin spread the job across more nodes.
It'd be nice developers can set a param similar to
mapred.fairscheduler.assignmultiple on a per-job basis to better control the
task allocation 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
> 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.
> It'd be nice developers can set a param similar to
> mapred.fairscheduler.assignmultiple on a per-job basis to better control the
> task allocation of a particular job.
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