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From "Todd Lipcon (JIRA)" <j...@apache.org>
Subject [jira] Updated: (MAPREDUCE-1521) Protection against incorrectly configured reduces
Date Tue, 15 Feb 2011 01:43:57 GMT

     [ https://issues.apache.org/jira/browse/MAPREDUCE-1521?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Todd Lipcon updated MAPREDUCE-1521:
-----------------------------------

    Attachment: resourcestimator-overflow.txt
                resourceestimator-threshold.txt

0.20.100 branch contains these two other fixes as part of this patch.

> Protection against incorrectly configured reduces
> -------------------------------------------------
>
>                 Key: MAPREDUCE-1521
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1521
>             Project: Hadoop Map/Reduce
>          Issue Type: Improvement
>          Components: jobtracker
>            Reporter: Arun C Murthy
>            Assignee: Mahadev konar
>            Priority: Critical
>             Fix For: 0.22.0
>
>         Attachments: MAPREDUCE-1521-0.20-yahoo.patch, MAPREDUCE-1521-0.20-yahoo.patch,
MAPREDUCE-1521-0.20-yahoo.patch, MAPREDUCE-1521-0.20-yahoo.patch, MAPREDUCE-1521-0.20-yahoo.patch,
MAPREDUCE-1521-trunk.patch, resourceestimator-threshold.txt, resourcestimator-overflow.txt
>
>
> We've seen a fair number of instances where naive users process huge data-sets (>10TB)
with badly mis-configured #reduces e.g. 1 reduce.
> This is a significant problem on large clusters since it takes each attempt of the reduce
a long time to shuffle and then run into problems such as local disk-space etc. Then it takes
4 such attempts.
> Proposal: Come up with heuristics/configs to fail such jobs early. 
> Thoughts?

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