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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