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From sam liu <samliuhad...@gmail.com>
Subject Re: Why my tests shows Yarn is worse than MRv1 for terasort?
Date Fri, 07 Jun 2013 05:21:49 GMT
The terasort execution log shows that reduce spent about 5.5 mins from 33%
to 35% as below.
13/06/10 08:02:22 INFO mapreduce.Job:  map 100% reduce 31%
13/06/10 08:02:25 INFO mapreduce.Job:  map 100% reduce 32%
13/06/10 *08:02:46* INFO mapreduce.Job:  map 100% reduce 33%
13/06/10 *08:08:16* INFO mapreduce.Job:  map 100% reduce 35%
13/06/10 08:08:19 INFO mapreduce.Job:  map 100% reduce 40%
13/06/10 08:08:22 INFO mapreduce.Job:  map 100% reduce 43%

Any way, below are my configurations for your reference. Thanks!
*(A) core-site.xml*
only define 'fs.default.name' and 'hadoop.tmp.dir'

*(B) hdfs-site.xml*
  <property>
    <name>dfs.replication</name>
    <value>1</value>
  </property>

  <property>
    <name>dfs.name.dir</name>
    <value>/opt/hadoop-2.0.4-alpha/temp/hadoop/dfs_name_dir</value>
  </property>

  <property>
    <name>dfs.data.dir</name>
    <value>/opt/hadoop-2.0.4-alpha/temp/hadoop/dfs_data_dir</value>
  </property>

  <property>
    <name>dfs.block.size</name>
    <value>134217728</value><!-- 128MB -->
  </property>

  <property>
    <name>dfs.namenode.handler.count</name>
    <value>64</value>
  </property>

  <property>
    <name>dfs.datanode.handler.count</name>
    <value>10</value>
  </property>

*(C) mapred-site.xml*
  <property>
    <name>mapreduce.cluster.temp.dir</name>
    <value>/opt/hadoop-2.0.4-alpha/temp/hadoop/mapreduce_temp</value>
    <description>No description</description>
    <final>true</final>
  </property>

  <property>
    <name>mapreduce.cluster.local.dir</name>
    <value>/opt/hadoop-2.0.4-alpha/temp/hadoop/mapreduce_local_dir</value>
    <description>No description</description>
    <final>true</final>
  </property>

<property>
  <name>mapreduce.child.java.opts</name>
  <value>-Xmx1000m</value>
</property>

<property>
    <name>mapreduce.framework.name</name>
    <value>yarn</value>
   </property>

 <property>
    <name>mapreduce.tasktracker.map.tasks.maximum</name>
    <value>8</value>
  </property>

  <property>
    <name>mapreduce.tasktracker.reduce.tasks.maximum</name>
    <value>4</value>
  </property>


  <property>
    <name>mapreduce.tasktracker.outofband.heartbeat</name>
    <value>true</value>
  </property>

*(D) yarn-site.xml*
 <property>
    <name>yarn.resourcemanager.resource-tracker.address</name>
    <value>node1:18025</value>
    <description>host is the hostname of the resource manager and
    port is the port on which the NodeManagers contact the Resource Manager.
    </description>
  </property>

  <property>
    <description>The address of the RM web application.</description>
    <name>yarn.resourcemanager.webapp.address</name>
    <value>node1:18088</value>
  </property>


  <property>
    <name>yarn.resourcemanager.scheduler.address</name>
    <value>node1:18030</value>
    <description>host is the hostname of the resourcemanager and port is
the port
    on which the Applications in the cluster talk to the Resource Manager.
    </description>
  </property>


  <property>
    <name>yarn.resourcemanager.address</name>
    <value>node1:18040</value>
    <description>the host is the hostname of the ResourceManager and the
port is the port on
    which the clients can talk to the Resource Manager. </description>
  </property>

  <property>
    <name>yarn.nodemanager.local-dirs</name>
    <value>/opt/hadoop-2.0.4-alpha/temp/hadoop/yarn_nm_local_dir</value>
    <description>the local directories used by the nodemanager</description>
  </property>

  <property>
    <name>yarn.nodemanager.address</name>
    <value>0.0.0.0:18050</value>
    <description>the nodemanagers bind to this port</description>
  </property>

  <property>
    <name>yarn.nodemanager.resource.memory-mb</name>
    <value>10240</value>
    <description>the amount of memory on the NodeManager in GB</description>
  </property>

  <property>
    <name>yarn.nodemanager.remote-app-log-dir</name>
    <value>/opt/hadoop-2.0.4-alpha/temp/hadoop/yarn_nm_app-logs</value>
    <description>directory on hdfs where the application logs are moved to
</description>
  </property>

   <property>
    <name>yarn.nodemanager.log-dirs</name>
    <value>/opt/hadoop-2.0.4-alpha/temp/hadoop/yarn_nm_log</value>
    <description>the directories used by Nodemanagers as log
directories</description>
  </property>

  <property>
    <name>yarn.nodemanager.aux-services</name>
    <value>mapreduce.shuffle</value>
    <description>shuffle service that needs to be set for Map Reduce to run
</description>
  </property>

  <property>
    <name>yarn.resourcemanager.client.thread-count</name>
    <value>64</value>
  </property>

 <property>
    <name>yarn.nodemanager.resource.cpu-cores</name>
    <value>24</value>
  </property>

<property>
    <name>yarn.nodemanager.vcores-pcores-ratio</name>
    <value>3</value>
  </property>

 <property>
    <name>yarn.nodemanager.resource.memory-mb</name>
    <value>22000</value>
  </property>

 <property>
    <name>yarn.nodemanager.vmem-pmem-ratio</name>
    <value>2.1</value>
  </property>



2013/6/7 Harsh J <harsh@cloudera.com>

> Not tuning configurations at all is wrong. YARN uses memory resource
> based scheduling and hence MR2 would be requesting 1 GB minimum by
> default, causing, on base configs, to max out at 8 (due to 8 GB NM
> memory resource config) total containers. Do share your configs as at
> this point none of us can tell what it is.
>
> Obviously, it isn't our goal to make MR2 slower for users and to not
> care about such things :)
>
> On Fri, Jun 7, 2013 at 8:45 AM, sam liu <samliuhadoop@gmail.com> wrote:
> > At the begining, I just want to do a fast comparision of MRv1 and Yarn.
> But
> > they have many differences, and to be fair for comparison I did not tune
> > their configurations at all.  So I got above test results. After
> analyzing
> > the test result, no doubt, I will configure them and do comparison again.
> >
> > Do you have any idea on current test result? I think, to compare with
> MRv1,
> > Yarn is better on Map phase(teragen test), but worse on Reduce
> > phase(terasort test).
> > And any detailed suggestions/comments/materials on Yarn performance
> tunning?
> >
> > Thanks!
> >
> >
> > 2013/6/7 Marcos Luis Ortiz Valmaseda <marcosluis2186@gmail.com>
> >>
> >> Why not to tune the configurations?
> >> Both frameworks have many areas to tune:
> >> - Combiners, Shuffle optimization, Block size, etc
> >>
> >>
> >>
> >> 2013/6/6 sam liu <samliuhadoop@gmail.com>
> >>>
> >>> Hi Experts,
> >>>
> >>> We are thinking about whether to use Yarn or not in the near future,
> and
> >>> I ran teragen/terasort on Yarn and MRv1 for comprison.
> >>>
> >>> My env is three nodes cluster, and each node has similar hardware: 2
> >>> cpu(4 core), 32 mem. Both Yarn and MRv1 cluster are set on the same
> env. To
> >>> be fair, I did not make any performance tuning on their
> configurations, but
> >>> use the default configuration values.
> >>>
> >>> Before testing, I think Yarn will be much better than MRv1, if they all
> >>> use default configuration, because Yarn is a better framework than
> MRv1.
> >>> However, the test result shows some differences:
> >>>
> >>> MRv1: Hadoop-1.1.1
> >>> Yarn: Hadoop-2.0.4
> >>>
> >>> (A) Teragen: generate 10 GB data:
> >>> - MRv1: 193 sec
> >>> - Yarn: 69 sec
> >>> Yarn is 2.8 times better than MRv1
> >>>
> >>> (B) Terasort: sort 10 GB data:
> >>> - MRv1: 451 sec
> >>> - Yarn: 1136 sec
> >>> Yarn is 2.5 times worse than MRv1
> >>>
> >>> After a fast analysis, I think the direct cause might be that Yarn is
> >>> much faster than MRv1 on Map phase, but much worse on Reduce phase.
> >>>
> >>> Here I have two questions:
> >>> - Why my tests shows Yarn is worse than MRv1 for terasort?
> >>> - What's the stratage for tuning Yarn performance? Is any materials?
> >>>
> >>> Thanks!
> >>
> >>
> >>
> >>
> >> --
> >> Marcos Ortiz Valmaseda
> >> Product Manager at PDVSA
> >> http://about.me/marcosortiz
> >>
> >
>
>
>
> --
> Harsh J
>

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