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Date: Thu, 5 Jan 2012 12:43:40 +0000 (UTC)
From: "Hudson (Commented) (JIRA)" <jira@apache.org>
To: mapreduce-issues@hadoop.apache.org
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Subject: [jira] [Commented] (MAPREDUCE-3490) RMContainerAllocator counts
 failed maps towards Reduce ramp up
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    [ https://issues.apache.org/jira/browse/MAPREDUCE-3490?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13180321#comment-13180321 ] 

Hudson commented on MAPREDUCE-3490:
-----------------------------------

Integrated in Hadoop-Hdfs-trunk #916 (See [https://builds.apache.org/job/Hadoop-Hdfs-trunk/916/])
    MAPREDUCE-3490. Fixed MapReduce AM to count failed maps also towards Reduce ramp up. Contributed by Sharad Agarwal and Arun C Murthy.

vinodkv : http://svn.apache.org/viewcvs.cgi/?root=Apache-SVN&view=rev&rev=1227226
Files : 
* /hadoop/common/trunk/hadoop-mapreduce-project/CHANGES.txt
* /hadoop/common/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-app/src/main/java/org/apache/hadoop/mapreduce/v2/app/rm/RMContainerAllocator.java
* /hadoop/common/trunk/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-app/src/test/java/org/apache/hadoop/mapreduce/v2/app/TestRMContainerAllocator.java

                
> RMContainerAllocator counts failed maps towards Reduce ramp up
> --------------------------------------------------------------
>
>                 Key: MAPREDUCE-3490
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-3490
>             Project: Hadoop Map/Reduce
>          Issue Type: Bug
>          Components: mr-am, mrv2
>    Affects Versions: 0.23.0
>            Reporter: Siddharth Seth
>            Assignee: Sharad Agarwal
>            Priority: Blocker
>             Fix For: 0.23.1
>
>         Attachments: MAPREDUCE-3490.patch, MAPREDUCE-3490.patch, MAPREDUCE-3490.patch, MAPREDUCE-3490.patch, MAPREDUCE-3490.patch, MAPREDUCE-3490.patch, MAPREDUCE-3490.patch, MR-3490-alternate.patch, MR-3490-alternate1.patch
>
>
> The RMContainerAllocator does not differentiate between failed and successful maps while calculating whether reduce tasks are ready to launch. Failed tasks are also counted towards total completed tasks. 
> Example. 4 failed maps, 10 total maps. Map%complete = 4/14 * 100 instead of being 0.

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