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https://issues.apache.org/jira/browse/MAPREDUCE-6478?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14876129#comment-14876129
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Hudson commented on MAPREDUCE-6478:
-----------------------------------
FAILURE: Integrated in Hadoop-Mapreduce-trunk-Java8 #411 (See
[https://builds.apache.org/job/Hadoop-Mapreduce-trunk-Java8/411/])
MAPREDUCE-6478. Add an option to skip cleanupJob stage or ignore cleanup
failure during commitJob. (Junping Du via wangda) (wangda: rev
372ad270a0d7ea5c581cd9a42b3c3cb189eca204)
* hadoop-yarn-project/CHANGES.txt
*
hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-core/src/main/java/org/apache/hadoop/mapreduce/lib/output/FileOutputCommitter.java
> Add an option to skip cleanupJob stage or ignore cleanup failure during
> commitJob().
> ------------------------------------------------------------------------------------
>
> Key: MAPREDUCE-6478
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-6478
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Reporter: Junping Du
> Assignee: Junping Du
> Fix For: 2.8.0
>
> Attachments: MAPREDUCE-6478-v1.1.patch, MAPREDUCE-6478-v1.patch
>
>
> In some of our test cases for MR on public cloud scenario, a very big MR job
> with hundreds or thousands of reducers cannot finish successfully because of
> Job Cleanup failures which is caused by different scale/performance impact
> for File System on the cloud (like AzureFS) which replacing HDFS's deletion
> for whole directory with REST API calls on deleting each sub-directories
> recursively. Even it get successfully, that could take much longer time
> (hours) which is not necessary and waste time/resources especially in public
> cloud scenario.
> In these scenarios, some failures of cleanupJob can be ignored or user choose
> to skip cleanupJob() completely make more sense. This is because making whole
> job finish successfully with side effect of wasting some user spaces is much
> better as user's jobs are usually comes and goes in public cloud, so have
> choices to tolerant some temporary files exists with get rid of big job
> re-run (or saving job's running time) is quite effective in time/resource
> cost.
> We should allow user to have this option (ignore failure or skip job cleanup
> stage completely) especially when user know the cleanup failure is not due to
> HDFS abnormal status but other FS' different performance trade-off.
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