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From "Hudson (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAPREDUCE-936) Allow a load difference in fairshare scheduler
Date Mon, 07 Sep 2009 18:06:57 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-936?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12752230#action_12752230

Hudson commented on MAPREDUCE-936:

Integrated in Hadoop-Mapreduce-trunk #75 (See [http://hudson.zones.apache.org/hudson/job/Hadoop-Mapreduce-trunk/75/])

> Allow a load difference in fairshare scheduler
> ----------------------------------------------
>                 Key: MAPREDUCE-936
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-936
>             Project: Hadoop Map/Reduce
>          Issue Type: Improvement
>          Components: contrib/fair-share
>    Affects Versions: 0.20.1, 0.21.0, 0.22.0
>            Reporter: Zheng Shao
>            Assignee: Zheng Shao
>             Fix For: 0.21.0
>         Attachments: MAPREDUCE-936.1.patch, MAPREDUCE-936.2.patch
> The problem we are facing: It takes a long time for all tasks of a job to get scheduled
on the cluster, even if the cluster is almost empty.
> There are two reasons that together lead to this situation:
> 1. The load factor makes sure each TT runs the same number of tasks. (This is the part
that this patch tries to change).
> 2. The scheduler tries to schedule map tasks locally (first node-local, then rack-local).
There is a wait time (mapred.fairscheduler.localitywait.node and mapred.fairscheduler.localitywait.rack,
both are around 10 sec in our conf), and accumulated wait time (JobInfo.localityWait). The
accumulated wait time is reset to 0 whenever a non-local map task is scheduled. That means
it takes N * wait_time to schedule N non-local map tasks.
> Because of 1, a lot of TT will not be able to take more tasks, even if they have free
slots. As a result, a lot of the map tasks cannot be scheduled locally.
> Because of 2, it's really hard to schedule a non-local task.
> As a result, sometimes we are seeing that it takes more than 2 minutes to schedule all
the mappers of a job.

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