can you try increasing memory per reducer ?
On Wed, Oct 31, 2012 at 9:15 PM, Eduard Skaley <[email protected]> wrote: > Hello, > > I'm getting this Error through job execution: > > 16:20:26 INFO [main] Job - map 100% reduce 46% > 16:20:27 INFO [main] Job - map 100% reduce 51% > 16:20:29 INFO [main] Job - map 100% reduce 62% > 16:20:30 INFO [main] Job - map 100% reduce 64% > 16:20:32 INFO [main] Job - Task Id : > attempt_1351680008718_0018_r_000006_0, Status : FAILED > Error: org.apache.hadoop.mapreduce.task.reduce.Shuffle$ShuffleError: error > in shuffle in fetcher#2 > at > org.apache.hadoop.mapreduce.task.reduce.Shuffle.run(Shuffle.java:123) > at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:371) > at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:152) > at java.security.AccessController.doPrivileged(Native Method) > at javax.security.auth.Subject.doAs(Subject.java:396) > at > org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1332) > at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:147) > Caused by: java.lang.OutOfMemoryError: Java heap space > at > org.apache.hadoop.io.BoundedByteArrayOutputStream.<init>(BoundedByteArrayOutputStream.java:58) > at > org.apache.hadoop.io.BoundedByteArrayOutputStream.<init>(BoundedByteArrayOutputStream.java:45) > at > org.apache.hadoop.mapreduce.task.reduce.MapOutput.<init>(MapOutput.java:97) > at > org.apache.hadoop.mapreduce.task.reduce.MergeManager.unconditionalReserve(MergeManager.java:286) > at > org.apache.hadoop.mapreduce.task.reduce.MergeManager.reserve(MergeManager.java:276) > at > org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyMapOutput(Fetcher.java:384) > at > org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyFromHost(Fetcher.java:319) > at > org.apache.hadoop.mapreduce.task.reduce.Fetcher.run(Fetcher.java:179) > > 16:20:33 INFO [main] Job - map 100% reduce 65% > 16:20:36 INFO [main] Job - map 100% reduce 67% > 16:20:39 INFO [main] Job - map 100% reduce 69% > 16:20:41 INFO [main] Job - map 100% reduce 70% > 16:20:43 INFO [main] Job - map 100% reduce 71% > > I have no clue what the issue could be for this. I googled this issue and > checked several sources of possible solutions but nothing does fit. > > I saw this jira entry which could fit: > https://issues.apache.org/jira/browse/MAPREDUCE-4655. > > Here somebody recommends to increase the value for the property > dfs.datanode.max.xcievers > / dfs.datanode.max.receiver.threads to 4096, but this is the value for > our cluster. > > http://yaseminavcular.blogspot.de/2011/04/common-hadoop-hdfs-exceptions-with.html > > The issue with the to small input files doesn't fit I think, because the > map phase reads 137 files with each 130MB. Block Size is 128MB. > > The cluster uses version 2.0.0-cdh4.1.1, > 581959ba23e4af85afd8db98b7687662fe9c5f20. > > Thx > > > > > > > -- Nitin Pawar
