YARN that runs on a single node
You can run the MapReduce job on YARN with pseudo-distributed mode by setting several parameters and running the ResourceManager daemon and the NodeManager daemon.
Here are the steps to run.
(1) configuration
Etc/hadoop/mapred-site.xml:
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
</configuration>
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Etc/hadoop/yarn-site.xml:
<configuration>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
</configuration>
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(2) Start the ResourceManager daemon and the NodeManager daemon
$ sbin/start-yarn.sh
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(3) Browse ResourceManager's network interface, their address defaults to:
resourcemanager-http://localhost:8088/
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(4) Running the MapReduce job
(5) After completing all the actions, stop the daemon:
$ sbin/stop-yarn.sh
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- How to operate fully distributed mode
For a fully distributed model, refer to the "Installation configuration on Apache Hadoop cluster" section below.
Installation configuration on Apache Hadoop cluster
This section describes how to install, configure, and manage a Hadoop cluster that can scale from a small cluster of several nodes to a very large cluster of thousands of nodes.
- Prerequisite
Make sure that you have all the necessary software installed on each node in your cluster, and that installing a Hadoop cluster typically extracts the installation software to all the machines in the cluster, referring to the previous section, "Installation configuration on Apache Hadoop single node."
Typically, a machine in a cluster is designated as a NameNode and another machine as a ResourceManager. These are all master. Other services, such as the WEB application proxy server and the MapReduce Job history server, run on a dedicated hardware or shared infrastructure, depending on the load.
The remaining machines in the cluster act as DataNode and NodeManager. These are all slave. "'
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Apache Hadoop Introductory Tutorial Fourth chapter