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Posted to mapreduce-dev@hadoop.apache.org by "Todd Lipcon (Resolved) (JIRA)" <ji...@apache.org> on 2011/11/22 20:36:40 UTC
[jira] [Resolved] (MAPREDUCE-2905) CapBasedLoadManager incorrectly
allows assignment when assignMultiple is true (was: assignmultiple per job)
[ https://issues.apache.org/jira/browse/MAPREDUCE-2905?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Todd Lipcon resolved MAPREDUCE-2905.
------------------------------------
Resolution: Fixed
Fix Version/s: 0.20.206.0
Hadoop Flags: Reviewed
Committed to 0.20-security.
> 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
> Assignee: Jeff Bean
> Fix For: 0.20.206.0
>
> Attachments: MR-2905.10-13-2011, MR-2905.patch, MR-2905.patch.2, mr-2905.txt, mr-2905.txt, 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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