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From "Hudson (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MAPREDUCE-6478) Add an option to skip cleanupJob stage or ignore cleanup failure during commitJob().
Date Fri, 18 Sep 2015 18:44:04 GMT

    [ https://issues.apache.org/jira/browse/MAPREDUCE-6478?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14876129#comment-14876129
] 

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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