[MapReduce-user] ReduceTask > ShuffleRamManager : Java Heap memory error

De : Olivier Varene - echo <[email protected]>
Objet : ReduceTask > ShuffleRamManager : Java Heap memory error
Date : 4 décembre 2012 09:34:06 HNEC
À : [email protected]
Répondre à : [email protected]


Hi to all,
first many thanks for the quality of the work you are doing : thanks a lot

I am facing a bug with the memory management at shuffle time, I regularly get

Map output copy failure : java.lang.OutOfMemoryError: Java heap space
at org.apache.hadoop.mapred.ReduceTask$ReduceCopier$MapOutputCopier.shuffleInMemory(ReduceTask.java:1612)


reading the code in org.apache.hadoop.mapred.ReduceTask.java file

the "ShuffleRamManager" is limiting the maximum of RAM allocation to Integer.MAX_VALUE * maxInMemCopyUse ?

maxSize = (int)(conf.getInt("mapred.job.reduce.total.mem.bytes",
(int)Math.min(Runtime.getRuntime().maxMemory(), Integer.MAX_VALUE))
* maxInMemCopyUse);

Why is is so ?
And why is it concatened to an Integer as its raw type is long ?

Does it mean that you can not have a Reduce Task taking advantage of more than 2Gb of memory ?

To explain a little bit my use case,
I am processing some 2700 maps (each working on 128 MB block of data), and when the reduce phase starts, it sometimes stumbles with java heap memory issues.

configuration is : java 1.6.0-27
hadoop 0.20.2
-Xmx1400m
io.sort.mb 400
io.sort.factor 25
io.sort.spill.percent 0.80
mapred.job.shuffle.input.buffer.percent 0.70
ShuffleRamManager: MemoryLimit=913466944, MaxSingleShuffleLimit=228366736

I will decrease
mapred.job.shuffle.input.buffer.percent to limit the errors, but I am not fully confident for the scalability of the process.

Any help would be welcomed

once again, many thanks
Olivier


P.S: sorry if I misunderstood the code, any explanation would be really welcomed

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