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From "Sangjin Lee (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MAPREDUCE-5817) mappers get rescheduled on node transition even after all reducers are completed
Date Mon, 31 Mar 2014 21:41:16 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-5817?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13955750#comment-13955750
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Sangjin Lee commented on MAPREDUCE-5817:
----------------------------------------

We're talking about two options for this: (1) modify JobImpl.actOnUnusableNode() so that if
all reducers are completed do not reschedule mappers, and (2) modify checkReadyForCommit()
so that it transitions to COMMITTING if all reducers are completed (if reducers exist) instead
of checking all tasks are completed.

Either approach seems to have some downsides.

For (1), the change is pretty narrow (only affects the rescheduling scenario). However, it
still lets the mapper tasks that were rescheduled prior to reducer completion run. So the
job may linger until those mapper tasks run to completion. And if those mapper tasks fail
for any reason, it may render the job as failed (even though all reducers may have succeeded
in reality).

For (2), it would be effective and would make the job finish much more quickly. On the other
hand, we'd need to do something about the mapper tasks that are running at that point. They
may need to be killed. Also, if the original mapper tasks were successful, we may need to
"resurrect" their status from KILLED to SUCCESSFUL to avoid confusion.



> mappers get rescheduled on node transition even after all reducers are completed
> --------------------------------------------------------------------------------
>
>                 Key: MAPREDUCE-5817
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-5817
>             Project: Hadoop Map/Reduce
>          Issue Type: Bug
>          Components: applicationmaster
>    Affects Versions: 2.3.0
>            Reporter: Sangjin Lee
>
> We're seeing a behavior where a job runs long after all reducers were already finished.
We found that the job was rescheduling and running a number of mappers beyond the point of
reducer completion. In one situation, the job ran for some 9 more hours after all reducers
completed!
> This happens because whenever a node transition (to an unusable state) comes into the
app master, it just reschedules all mappers that already ran on the node in all cases.
> Therefore, if any node transition has a potential to extend the job period. Once this
window opens, another node transition can prolong it, and this can happen indefinitely in
theory.
> If there is some instability in the pool (unhealthy, etc.) for a duration, then any big
job is severely vulnerable to this problem.
> If all reducers have been completed, JobImpl.actOnUnusableNode() should not reschedule
mapper tasks. If all reducers are completed, the mapper outputs are no longer needed, and
there is no need to reschedule mapper tasks as they would not be consumed anyway.



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