Would you please look into the resourcemanager log, and check how many containers are allocated and what the allocated memory is? You may want to search the log with "assignedContainer".
On Tue, Apr 23, 2013 at 10:19 AM, 牛兆捷 <[email protected]> wrote: > I config them in mapred-site.xml like below, I set them less then 1000 for > the normalization as you said: > > " > <property> > <name>yarn.app.mapreduce.am.resource.mb</name> > <value>900</value> > </property> > <property> > <name>mapreduce.map.memory.mb</name> > <value>900</value> > </property> > <property> > <name>mapreduce.reduce.memory.mb</name> > <value>900</value> > </property> > " > > Then I run just one map, as you said there are 2 contained will be > launched, one for A/M master, the other for map task. > However, the 2 container cost 4G memory which I see from yarn UI interface. > > > > > 2013/4/24 Zhijie Shen <[email protected]> > > > Do you mean the memory assigned for the container of M/R's AM? Did you > set > > ContainerLaunchContext.setResource? > > > > AFAIK, by default, yarn.scheduler.minimum-allocation-mb = 1024 and > > yarn.app.mapreduce.am.resource.mb > > = 1536. So, M/R job will request 1536 for its AM, but Yarn's scheduler > will > > normalize the request to 2048, which is no less than 1536, and is > multiple > > times of the min allocation. > > > > > > On Tue, Apr 23, 2013 at 8:43 AM, 牛兆捷 <[email protected]> wrote: > > > > > I am using 2.0.3-alpha, I don't set the map memory capacity explicitly, > > > then "resourceCapacity.setMemory" should set the default memory request > > to > > > 1024mb, > > > However 2048 Memory is assigned to this container. > > > > > > Why it does like this? > > > > > > -- > > > *Sincerely,* > > > *Zhaojie* > > > * > > > * > > > > > > > > > > > -- > > Zhijie Shen > > Hortonworks Inc. > > http://hortonworks.com/ > > > > > > -- > *Sincerely,* > *Zhaojie* > * > * > -- Zhijie Shen Hortonworks Inc. http://hortonworks.com/
