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MapReduce >> mail # user >> Java Heap memory error : Limit to 2 Gb of ShuffleRamManager ?


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Re: Java Heap memory error : Limit to 2 Gb of ShuffleRamManager ?
Oliver,

 Sorry, missed this.

 The historical reason, if I remember right, is that we used to have a single byte buffer and hence the limit.

 We should definitely remove it now since we don't use a single buffer. Mind opening a jira?

 http://wiki.apache.org/hadoop/HowToContribute

thanks!
Arun

On Dec 6, 2012, at 8:01 AM, Olivier Varene - echo wrote:

> anyone ?
>
> Début du message réexpédié :
>
>> 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
>>
>> --
>>  
>>  
>>  
>>
>>
>

--
Arun C. Murthy
Hortonworks Inc.
http://hortonworks.com/