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https://issues.apache.org/jira/browse/HADOOP-5186?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12688252#action_12688252
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Vinod K V commented on HADOOP-5186:
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One more issue with the current model of limiting by number of jobs per pool is
the under-utilization of map slots while reduce tasks are running. If N is the
maximum number of jobs that can run in a particular pool, when all the maps of
first N jobs are done and only the reduces are running, the map slots sit idle
and the maps of next N batch of jobs cannot yet be scheduled. The fix for this
is to change the limits to be in terms of tasks/slots instead of the number of
jobs.
> Improve limit handling in fairshare scheduler
> ---------------------------------------------
>
> Key: HADOOP-5186
> URL: https://issues.apache.org/jira/browse/HADOOP-5186
> Project: Hadoop Core
> Issue Type: Improvement
> Components: contrib/fair-share
> Reporter: Hemanth Yamijala
> Priority: Minor
>
> The fairshare scheduler has a way by which it can limit the number of jobs in
> a pool by setting the maxRunningJobs parameter in its allocations definition.
> This limit is treated as a hard limit, and comes into effect even if the
> cluster is free to run more jobs, resulting in underutilization. Possibly the
> same thing happens with the parameter maxRunningJobs for user and
> userMaxJobsDefault. It may help to treat these as a soft limit and run
> additional jobs to keep the cluster fully utilized.
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