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https://issues.apache.org/jira/browse/MAPREDUCE-5000?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13576097#comment-13576097
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Hadoop QA commented on MAPREDUCE-5000:
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{color:green}+1 overall{color}. Here are the results of testing the latest
attachment
http://issues.apache.org/jira/secure/attachment/12568880/MAPREDUCE-5000.patch
against trunk revision .
{color:green}+1 @author{color}. The patch does not contain any @author
tags.
{color:green}+1 tests included{color}. The patch appears to include 1 new
or modified test files.
{color:green}+1 javac{color}. The applied patch does not increase the
total number of javac compiler warnings.
{color:green}+1 javadoc{color}. The javadoc tool did not generate any
warning messages.
{color:green}+1 eclipse:eclipse{color}. The patch built with
eclipse:eclipse.
{color:green}+1 findbugs{color}. The patch does not introduce any new
Findbugs (version 1.3.9) warnings.
{color:green}+1 release audit{color}. The applied patch does not increase
the total number of release audit warnings.
{color:green}+1 core tests{color}. The patch passed unit tests in
hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-app.
{color:green}+1 contrib tests{color}. The patch passed contrib unit tests.
Test results:
https://builds.apache.org/job/PreCommit-MAPREDUCE-Build/3324//testReport/
Console output:
https://builds.apache.org/job/PreCommit-MAPREDUCE-Build/3324//console
This message is automatically generated.
> TaskImpl.getCounters() can return the counters for the wrong task attempt
> when task is speculating
> --------------------------------------------------------------------------------------------------
>
> Key: MAPREDUCE-5000
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-5000
> Project: Hadoop Map/Reduce
> Issue Type: Bug
> Components: mr-am
> Affects Versions: 0.23.6
> Reporter: Jason Lowe
> Assignee: Jason Lowe
> Priority: Critical
> Attachments: MAPREDUCE-5000.patch
>
>
> When a task is speculating and one attempt completes then sometimes the
> counters for the wrong attempt are aggregated into the total counters for the
> job. The scenario looks like this:
> # Two task attempts are racing, _0 and _1
> # _1 finishes first, causing the task to issue a TA_KILL to attempt _0
> # _0 receives TA_KILL, sets progress to 1.0f and waits for container cleanup
> # if TaskImpl.getCounters() is called now, TaskImpl.selectBestAttempt() can
> return _0 since it is not quite yet in the KILLED state yet progress is maxed
> out and no other attempt has more progress.
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