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From Nirmal Kumar <nirmal.ku...@impetus.co.in>
Subject Doubts: Deployment and Configuration of YARN cluster
Date Wed, 15 Jan 2014 13:21:36 GMT

I am new to YARN and have certain doubts regarding the deployment and configuration of YARN
on a cluster.

As per my understanding to deploy Hadoop 2.x using YARN on a cluster we need to distribute
the below files to all the slave nodes in the cluster:

*         conf/core-site.xml

*         conf/hdfs-site.xml

*         conf/yarn-site.xml

*         conf/mapred-site.xml

Also we need to ONLY change the following file on each slave nodes:

*         conf/hdfs-site.xml
Need to mention the {dfs.datanode.name.dir} value

Do we need to change any other config file on the slave nodes?
Can I change {yarn.nodemanager.resource.memory-mb} for each NM running on the slave nodes?
This is since I might have a *heterogeneous environment* i.e. different nodes with different
memory and cores. For NM1 I might have 40GB memory and for the other say 20GB.

{mapreduce.map.memory.mb}   specifies the *max. virtual memory* allowed by a Hadoop task subprocess.
{mapreduce.map.java.opts}         specify the *max. heap space* of the allocated jvm. If you
exceed the max heap size, the JVM throws an OOM.
are the above properties applicable to all the Map\Reduce tasks(from different Map Reduce
applications) in general, running on different slave nodes?
or Can I change these for a particular slave node.? For e.g. say for a SlaveNode1 I run the
map task with 4GB and for other SlaveNode2 I run the map task with 8GB. Same with the reduce

I need some understanding to *configure processing capacity* in the cluster like Container
Size, No. of Containers, No. of Mappers\Reducers.



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