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https://issues.apache.org/jira/browse/MAPREDUCE-1521?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12836902#action_12836902
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Todd Lipcon commented on MAPREDUCE-1521:
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This makes me just a little bit nervous - the case I'm worried about is when a
job is working fine in production and then starts failing at 3am some morning
because the data volume increased just a little bit over the threshold.
Could we default this behavior off and only turn it on for clusters where the
operators prefer it?
> 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: Arun C Murthy
> Priority: Critical
> Fix For: 0.22.0
>
>
> 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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