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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:
---------------------------------

    Attachment: MR-2905.10-13-2011

Unit test included. Unit test found typo, which was fixed ("assign map assign 
reduce, whatever")
                
> CapBasedLoadManager incorrectly allows assignment when assignMultiple is true 
> (was: assignmultiple per job)
> -----------------------------------------------------------------------------------------------------------
>
>                 Key: MAPREDUCE-2905
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-2905
>             Project: Hadoop Map/Reduce
>          Issue Type: Bug
>          Components: contrib/fair-share
>    Affects Versions: 0.20.2
>            Reporter: Jeff Bean
>         Attachments: MR-2905.10-13-2011, MR-2905.patch, MR-2905.patch.2
>
>
> 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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