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Date: Tue, 8 Nov 2011 05:54:51 +0000 (UTC)
From: "Hadoop QA (Commented) (JIRA)" <jira@apache.org>
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Subject: [jira] [Commented] (MAPREDUCE-3343) TaskTracker Out of Memory
 because of distributed cache
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    [ https://issues.apache.org/jira/browse/MAPREDUCE-3343?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13146095#comment-13146095 ] 

Hadoop QA commented on MAPREDUCE-3343:
--------------------------------------

-1 overall.  Here are the results of testing the latest attachment 
  http://issues.apache.org/jira/secure/attachment/12502884/mapreduce-3343-release-0.20.205.0.patch
  against trunk revision .

    +1 @author.  The patch does not contain any @author tags.

    +1 tests included.  The patch appears to include 3 new or modified tests.

    -1 patch.  The patch command could not apply the patch.

Console output: https://builds.apache.org/job/PreCommit-MAPREDUCE-Build/1269//console

This message is automatically generated.
                
> TaskTracker Out of Memory because of distributed cache
> ------------------------------------------------------
>
>                 Key: MAPREDUCE-3343
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-3343
>             Project: Hadoop Map/Reduce
>          Issue Type: Bug
>          Components: mrv1
>    Affects Versions: 0.20.205.0
>            Reporter: Ahmed Radwan
>              Labels: mapreduce, patch
>         Attachments: mapreduce-3343-release-0.20.205.0.patch
>
>
> This Out of Memory happens when you run large number of jobs (using the distributed cache) on a TaskTracker. 
> Seems the basic issue is with the distributedCacheManager (instance of TrackerDistributedCacheManager in TaskTracker.java), this gets created during TaskTracker.initialize(), and it keeps references to TaskDistributedCacheManager for every submitted job via the jobArchives Map, also references to CacheStatus via cachedArchives map. I am not seeing these cleaned up between jobs, so this can out of memory problems after really large number of jobs are submitted. We have seen this issue in a number of cases.

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