All,
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.
Also,
{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.
{mapreduce.reduce.memory.mb}
{mapreduce.reduce.java.opts}
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 task.
I need some understanding to *configure processing capacity* in the cluster
like Container Size, No. of Containers, No. of Mappers\Reducers.
Thanks,
-Nirmal
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