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https://issues.apache.org/jira/browse/MAPREDUCE-6447?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16040517#comment-16040517
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Adam Sotona commented on MAPREDUCE-6447:
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With relation to this issue I have manually performed a kind of configuration
"bracketing", where I manually altered the job configuration of a still running
application before another attempt.
To do it manually is a bit complicated as you have to modify the job
configuration in HDFS stagging folder of the application as well as on each
data node in the local appcache/<app>/filecache.
However what if there would be a mechanism to prepare such alternate
configuration(s), which will be used for second and following attempts after a
task fail?
For example in job configuration I would set:
mapreduce.reduce.shuffle.input.buffer.percent=0.70
mapreduce.reduce.shuffle.memory.limit.percent=0.4
mapreduce.reduce.shuffle.parallelcopies=30
attempt-2.mapreduce.reduce.shuffle.input.buffer.percent=0.70
attempt-2.mapreduce.reduce.shuffle.memory.limit.percent=0.2
attempt-2.mapreduce.reduce.shuffle.parallelcopies=4
attempt-3.mapreduce.reduce.shuffle.input.buffer.percent=0.20
attempt-3.mapreduce.reduce.shuffle.memory.limit.percent=0.2
attempt-3.mapreduce.reduce.shuffle.parallelcopies=2
Such mechanism should not be hard to implement and it would allow to have
alternate fail-over configurations prepared in advance instead of long-term
repeated bug hunting.
Thanks
> reduce shuffle throws "java.lang.OutOfMemoryError: Java heap space"
> -------------------------------------------------------------------
>
> Key: MAPREDUCE-6447
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-6447
> Project: Hadoop Map/Reduce
> Issue Type: Bug
> Affects Versions: 2.5.0, 2.6.0, 2.5.1, 2.7.1
> Reporter: shuzhangyao
> Assignee: shuzhangyao
> Priority: Minor
>
> 2015-08-11 14:03:54,550 WARN [main] org.apache.hadoop.mapred.YarnChild:
> Exception running child :
> org.apache.hadoop.mapreduce.task.reduce.Shuffle$ShuffleError: error in
> shuffle in fetcher#10
> at org.apache.hadoop.mapreduce.task.reduce.Shuffle.run(Shuffle.java:134)
> at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:376)
> at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:168)
> at java.security.AccessController.doPrivileged(Native Method)
> at javax.security.auth.Subject.doAs(Subject.java:415)
> at
> org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1614)
> at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:163)
> Caused by: java.lang.OutOfMemoryError: Java heap space
> at
> org.apache.hadoop.io.BoundedByteArrayOutputStream.<init>(BoundedByteArrayOutputStream.java:56)
> at
> org.apache.hadoop.io.BoundedByteArrayOutputStream.<init>(BoundedByteArrayOutputStream.java:46)
> at
> org.apache.hadoop.mapreduce.task.reduce.InMemoryMapOutput.<init>(InMemoryMapOutput.java:63)
> at
> org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl.unconditionalReserve(MergeManagerImpl.java:303)
> at
> org.apache.hadoop.mapreduce.task.reduce.MergeManagerImpl.reserve(MergeManagerImpl.java:293)
> at
> org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyMapOutput(Fetcher.java:511)
> at
> org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyFromHost(Fetcher.java:329)
> at org.apache.hadoop.mapreduce.task.reduce.Fetcher.run(Fetcher.java:193)
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