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https://issues.apache.org/jira/browse/MAPREDUCE-2324?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13065318#comment-13065318
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Robert Joseph Evans commented on MAPREDUCE-2324:
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OK I have thought about it and talk with some people about
statistics/scheduling and the like, and the conclusion that I have come to is
the following.
We should add in a new configuration parameter called
mapreduce.reduce.input.limit.attempt.factor
This value would default to 1.0 and be used to determine the number of times a
reduce task can be rejected because the estimated input size will not fit
before the job is killed. So if (#failedAttempts > (#ofActiveNodes *
attempt.factor)) then kill the job.
> Job should fail if a reduce task can't be scheduled anywhere
> ------------------------------------------------------------
>
> Key: MAPREDUCE-2324
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-2324
> Project: Hadoop Map/Reduce
> Issue Type: Bug
> Affects Versions: 0.20.2, 0.20.205.0
> Reporter: Todd Lipcon
> Assignee: Robert Joseph Evans
>
> If there's a reduce task that needs more disk space than is available on any
> mapred.local.dir in the cluster, that task will stay pending forever. For
> example, we produced this in a QA cluster by accidentally running terasort
> with one reducer - since no mapred.local.dir had 1T free, the job remained in
> pending state for several days. The reason for the "stuck" task wasn't clear
> from a user perspective until we looked at the JT logs.
> Probably better to just fail the job if a reduce task goes through all TTs
> and finds that there isn't enough space.
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