Apache* Hadoop*

This tutorial explains the process of installing, configuring, and running Apache Hadoop on Clear Linux* OS.

Description

For this tutorial, you will install Hadoop in a single machine running both the master and slave daemons.

The Apache Hadoop software library is a framework for distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, with each machine offering local computation and storage.

Install Apache Hadoop

Apache Hadoop is included in the big-data-basic bundle. To install the framework, enter the following command:

sudo swupd bundle-add big-data-basic

Configure Apache Hadoop

  1. To create the configuration directory, enter the following command:

    sudo mkdir /etc/hadoop

  2. Copy the defaults from /usr/share/defaults/hadoop to /etc/hadoop with the following command:

    $ sudo cp /usr/share/defaults/hadoop/* /etc/hadoop

    Note

    Since Clear Linux OS is a stateless system, never modify the files under the /usr/share/defaults directory. The software updater will overwrite those files.

    Once all the configuration files are in /etc/hadoop, edit them to fit your needs. The NameNode server is the master server that manages the namespace of the files’ system and regulates the clients’ access to files. The first file to be edited, /etc/hadoop/core-site.xml, informs the Hadoop daemon where NameNode is running. In this tutorial, NameNode runs in the localhost.

  3. Open the /etc/hadoop/core-site.xml file using any editor and modify the file as follows:

    <?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
<property>
<name>fs.default.name</name>
<value>hdfs://localhost:9000</value>
</property>
</configuration>

  4. Edit the /etc/hadoop/hdfs-site.xml file. This file configures the HDFS daemons. This configuration includes the list of permitted and excluded data nodes and the size of those blocks. For this example, set the number of block replication to 1 from the default of 3 as follows:

    <?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
<property>
<name>dfs.replication</name>
<value>1</value>
</property>
<property>
<name>dfs.permission</name>
<value>false</value>
</property>
</configuration>

  5. Edit the /etc/hadoop/mapred-site.xml file. This file configures all daemons related to MapReduce: JobTracker and TaskTrackers. With MapReduce, Hadoop can process big amounts of data in multiple systems. In our example, we set YARN as our runtime framework for executing MapReduce jobs as follows:

    <?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
</configuration>

  6. Edit the /etc/hadoop/yarn-site.xml file. This file configures all daemons related to YARN: ResourceManager and NodeManager. In our example, we implement the mapreduce_shuffle service, which is the default as follows:

    <?xml version="1.0"?>
<configuration>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.nodemanager.auxservices.mapreduce.shuffle.class</name>
<value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>
</configuration>

Configure your SSH key

  1. Create a SSH key. If you already have one, skip this step.

    sudo ssh-keygen -t rsa

  2. Copy the key to your authorized keys.

    sudo cat /root/.ssh/id_rsa.pub | sudo tee -a /root/.ssh/authorized_keys

  3. Log into the localhost. If no password prompt appears, you are ready to run the Hadoop daemons.

    sudo ssh localhost

Run the Hadoop daemons

With all the configuration files properly edited, you are ready to start the daemons.

When you format the NameNode server, it formats the metadata related to data nodes. Thus, all the information on the data nodes is lost and the nodes can be reused for new data.

  1. Format the NameNode server with the following command:

    sudo hdfs namenode -format

  2. Start the DFS in NameNode and DataNodes with the following command:

    sudo start-dfs.sh

    The console output should be similar to:

    Starting namenodes on [localhost]
The authenticity of host 'localhost (::1)' can't be established.
ECDSA key fingerprint is
SHA256:97e+7TnomsS9W7GjFPjzY75HGBp+f1y6sA+ZFcOPIPU.
Are you sure you want to continue connecting (yes/no)?

  3. Enter yes to continue.

  4. Start the YARN daemons ResourceManager and NodeManager with the following command:

    sudo start-yarn.sh

  5. Ensure everything is running as expected with the following command:

    sudo jps

    The console output should be similar to:

    22674 DataNode
26228 Jps
22533 NameNode
23046 ResourceManager
22854 SecondaryNameNode
23150 NodeManager

Run the MapReduce wordcount example

  1. Create the input directory.

    sudo hdfs dfs -mkdir -p /user/root/input

  2. Copy a file from the local file system to the HDFS.

    sudo hdfs dfs -copyFromLocal local-file /user/root/input

  3. Run the wordcount example.

    sudo hadoop jar /usr/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.8.0.jar wordcount input output

  4. Read the output file “part-r-00000”. This file contains the number of times each word appears in the file.

    sudo hdfs dfs -cat /user/root/output/part-r-00000

Congratulations!

You have successfully installed and setup a single node Hadoop cluster. Additionally, you ran a simple wordcount example.

Your single node Hadoop cluster is up and running!