Hi Harsh, According to above suggestions, I removed the duplication of setting, and reduce the value of 'yarn.nodemanager.resource.cpu-cores', ' yarn.nodemanager.vcores-pcores-ratio' and ' yarn.nodemanager.resource.memory-mb' to 16, 8 and 12000. Ant then, the efficiency improved about 18%. I have questions:
- How to know the container number? Why you say it will be 22 containers due to a 22 GB memory? - My machine has 32 GB memory, how many memory is proper to be assigned to containers? - In mapred-site.xml, if I set 'mapreduce.framework.name' to be 'yarn', will other parameters for mapred-site.xml still work in yarn framework? Like 'mapreduce.task.io.sort.mb' and 'mapreduce.map.sort.spill.percent' Thanks! 2013/6/8 Harsh J <ha...@cloudera.com> > Hey Sam, > > Did you get a chance to retry with Sandy's suggestions? The config > appears to be asking NMs to use roughly 22 total containers (as > opposed to 12 total tasks in MR1 config) due to a 22 GB memory > resource. This could impact much, given the CPU is still the same for > both test runs. > > On Fri, Jun 7, 2013 at 12:23 PM, Sandy Ryza <sandy.r...@cloudera.com> > wrote: > > Hey Sam, > > > > Thanks for sharing your results. I'm definitely curious about what's > > causing the difference. > > > > A couple observations: > > It looks like you've got yarn.nodemanager.resource.memory-mb in there > twice > > with two different values. > > > > Your max JVM memory of 1000 MB is (dangerously?) close to the default > > mapreduce.map/reduce.memory.mb of 1024 MB. Are any of your tasks getting > > killed for running over resource limits? > > > > -Sandy > > > > > > On Thu, Jun 6, 2013 at 10:21 PM, sam liu <samliuhad...@gmail.com> wrote: > >> > >> 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 <ha...@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 <samliuhad...@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 <marcosluis2...@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 <samliuhad...@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 > >> > >> > > > > > > -- > Harsh J >
