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From "Todd Lipcon (Commented) (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MAPREDUCE-2905) CapBasedLoadManager incorrectly allows assignment when assignMultiple is true (was: assignmultiple per job)
Date Tue, 18 Oct 2011 03:20:14 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-2905?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13129451#comment-13129451
] 

Todd Lipcon commented on MAPREDUCE-2905:
----------------------------------------

The patch seems to reformat a bunch of stuff to 4-space indentation instead of 2-space, making
it tough to review. Since I've already made you do several iterations, let me take care of
the next one for you... will upload an updated patch soon.
                
> 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, screenshot-1.jpg
>
>
> 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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