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https://issues.apache.org/jira/browse/MAPREDUCE-776?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12755782#action_12755782
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Hadoop QA commented on MAPREDUCE-776:
-------------------------------------
-1 overall. Here are the results of testing the latest attachment
http://issues.apache.org/jira/secure/attachment/12419661/M776-4.patch
against trunk revision 815249.
+1 @author. The patch does not contain any @author tags.
+1 tests included. The patch appears to include 6 new or modified tests.
+1 javadoc. The javadoc tool did not generate any warning messages.
+1 javac. The applied patch does not increase the total number of javac
compiler warnings.
+1 findbugs. The patch does not introduce any new Findbugs warnings.
+1 release audit. The applied patch does not increase the total number of
release audit warnings.
+1 core tests. The patch passed core unit tests.
-1 contrib tests. The patch failed contrib unit tests.
Test results:
http://hudson.zones.apache.org/hudson/job/Mapreduce-Patch-h6.grid.sp2.yahoo.net/81/testReport/
Findbugs warnings:
http://hudson.zones.apache.org/hudson/job/Mapreduce-Patch-h6.grid.sp2.yahoo.net/81/artifact/trunk/build/test/findbugs/newPatchFindbugsWarnings.html
Checkstyle results:
http://hudson.zones.apache.org/hudson/job/Mapreduce-Patch-h6.grid.sp2.yahoo.net/81/artifact/trunk/build/test/checkstyle-errors.html
Console output:
http://hudson.zones.apache.org/hudson/job/Mapreduce-Patch-h6.grid.sp2.yahoo.net/81/console
This message is automatically generated.
> Gridmix: Trace-based benchmark for Map/Reduce
> ---------------------------------------------
>
> Key: MAPREDUCE-776
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-776
> Project: Hadoop Map/Reduce
> Issue Type: New Feature
> Components: benchmarks
> Reporter: Chris Douglas
> Assignee: Chris Douglas
> Attachments: M776-1.patch, M776-2.patch, M776-3.patch, M776-4.patch,
> MR776-0.patch
>
>
> Previous benchmarks ( HADOOP-2369 , HADOOP-3770 ), while informed by
> production jobs, were principally load generating tools used to validate
> stability and performance under saturation. The important dimensions of that
> load- submission order/rate, I/O profile, CPU usage, etc- only accidentally
> match that of the real load on the cluster. Given related work that
> characterizes production load ( MAPREDUCE-751 ), it would be worthwhile to
> use mined data to impose a corresponding load for tuning and guiding
> development of the framework.
> The first version will focus on modeling task I/O, submission, and memory
> usage.
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