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MapReduce >> mail # user >> Insight on why distcp becomes slower when adding nodemanager


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Re: Insight on why distcp becomes slower when adding nodemanager
On your second low-memory NM instance, did you ensure to lower the
yarn.nodemanager.resource.memory-mb property specifically to avoid
swapping due to excessive resource grants? The default offered is 8 GB
(>> 1.7 GB you have).

On Mon, Oct 29, 2012 at 8:42 PM, Alexandre Fouche
<[EMAIL PROTECTED]> wrote:
> Hi,
>
> Can someone give some insight on why a "distcp" of 600 files of a few
> hundred bytes from s3n:// to local hdfs is taking 46s when using a
> yarn-nodemanager EC2 instance with 16GB memory (which by the way i think is
> jokingly long), and taking 3mn30s when adding a second yarn-nodemanager (a
> small instance with 1.7GB memory) ?
> I would have expected it to be a bit faster, not 5xlonger !
>
> I have the same issue when i stop the small instance nodemanager and restart
> it to join the processing after the big nodemanager instance was already
> submitted the job.
>
> I am using Cloudera latest Yarn+HDFS on Amazon (rebranded Centos 6)
>
>     #Staging 14:58:04 root@datanode2:hadoop-yarn: rpm -qa |grep hadoop
>     hadoop-hdfs-datanode-2.0.0+545-1.cdh4.1.1.p0.5.el6.x86_64
>     hadoop-mapreduce-2.0.0+545-1.cdh4.1.1.p0.5.el6.x86_64
>     hadoop-0.20-mapreduce-0.20.2+1261-1.cdh4.1.1.p0.4.el6.x86_64
>     hadoop-yarn-nodemanager-2.0.0+545-1.cdh4.1.1.p0.5.el6.x86_64
>     hadoop-mapreduce-historyserver-2.0.0+545-1.cdh4.1.1.p0.5.el6.x86_64
>     hadoop-hdfs-2.0.0+545-1.cdh4.1.1.p0.5.el6.x86_64
>     hadoop-client-2.0.0+545-1.cdh4.1.1.p0.5.el6.x86_64
>     hadoop-2.0.0+545-1.cdh4.1.1.p0.5.el6.x86_64
>     hadoop-yarn-2.0.0+545-1.cdh4.1.1.p0.5.el6.x86_64
>
>
>     #Staging 14:39:51 root@resourcemanager:hadoop-yarn:
> HADOOP_MAPRED_HOME=/usr/lib/hadoop-mapreduce time hadoop distcp -overwrite
> s3n://xxx:[EMAIL PROTECTED]ev/* hdfs:///tmp/something/a
>
>     12/10/29 14:40:12 INFO tools.DistCp: Input Options:
> DistCpOptions{atomicCommit=false, syncFolder=false, deleteMissing=false,
> ignoreFailures=false, maxMaps=20, sslConfigurationFile='null',
> copyStrategy='uniformsize', sourceFileListing=null,
> sourcePaths=[s3n://xxx:[EMAIL PROTECTED]ev/*],
> targetPath=hdfs:/tmp/something/a}
>     12/10/29 14:40:18 WARN conf.Configuration: io.sort.mb is deprecated.
> Instead, use mapreduce.task.io.sort.mb
>     12/10/29 14:40:18 WARN conf.Configuration: io.sort.factor is deprecated.
> Instead, use mapreduce.task.io.sort.factor
>     12/10/29 14:40:19 INFO mapreduce.JobSubmitter: number of splits:15
>     12/10/29 14:40:19 WARN conf.Configuration: mapred.jar is deprecated.
> Instead, use mapreduce.job.jar
>     12/10/29 14:40:19 WARN conf.Configuration:
> mapred.map.tasks.speculative.execution is deprecated. Instead, use
> mapreduce.map.speculative
>     12/10/29 14:40:19 WARN conf.Configuration: mapred.reduce.tasks is
> deprecated. Instead, use mapreduce.job.reduces
>     12/10/29 14:40:19 WARN conf.Configuration: mapred.mapoutput.value.class
> is deprecated. Instead, use mapreduce.map.output.value.class
>     12/10/29 14:40:19 WARN conf.Configuration: mapreduce.map.class is
> deprecated. Instead, use mapreduce.job.map.class
>     12/10/29 14:40:19 WARN conf.Configuration: mapred.job.name is
> deprecated. Instead, use mapreduce.job.name
>     12/10/29 14:40:19 WARN conf.Configuration: mapreduce.inputformat.class
> is deprecated. Instead, use mapreduce.job.inputformat.class
>     12/10/29 14:40:19 WARN conf.Configuration: mapred.output.dir is
> deprecated. Instead, use mapreduce.output.fileoutputformat.outputdir
>     12/10/29 14:40:19 WARN conf.Configuration: mapreduce.outputformat.class
> is deprecated. Instead, use mapreduce.job.outputformat.class
>     12/10/29 14:40:19 WARN conf.Configuration: mapred.map.tasks is
> deprecated. Instead, use mapreduce.job.maps
>     12/10/29 14:40:19 WARN conf.Configuration: mapred.mapoutput.key.class is
> deprecated. Instead, use mapreduce.map.output.key.class
>     12/10/29 14:40:19 WARN conf.Configuration: mapred.working.dir is
> deprecated. Instead, use mapreduce.job.working.dir

Harsh J