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From "Amar Kamat (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HADOOP-4018) limit memory usage in jobtracker
Date Thu, 18 Sep 2008 04:43:44 GMT

    [ https://issues.apache.org/jira/browse/HADOOP-4018?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12632088#action_12632088
] 

Amar Kamat commented on HADOOP-4018:
------------------------------------

Owen,
I think Dhruba's concern here is of many small/avg sized jobs collectively overloading the
jobtracker, see [here|https://issues.apache.org/jira/browse/HADOOP-4018?focusedCommentId=12625505#action_12625505].
Capping individual jobs might not help as all the jobs will accumulate in JT's memory and
bring it down. I think some kind of local capping, global capping and smart scheduling/initialization
might help. But I agree that in the long term we need to model the memory better but for now
simple heuristics might work.

> limit memory usage in jobtracker
> --------------------------------
>
>                 Key: HADOOP-4018
>                 URL: https://issues.apache.org/jira/browse/HADOOP-4018
>             Project: Hadoop Core
>          Issue Type: Bug
>          Components: mapred
>            Reporter: dhruba borthakur
>            Assignee: dhruba borthakur
>         Attachments: maxSplits.patch, maxSplits2.patch, maxSplits3.patch, maxSplits4.patch,
maxSplits5.patch, maxSplits6.patch, maxSplits7.patch
>
>
> We have seen instances when a user submitted a job with many thousands of mappers. The
JobTracker was running with 3GB heap, but it was still not enough to prevent memory trashing
from Garbage collection; effectively the Job Tracker was not able to serve jobs and had to
be restarted.
> One simple proposal would be to limit the maximum number of tasks per job. This can be
a configurable parameter. Is there other things that eat huge globs of memory in job Tracker?

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