This tutorial walks you through the process of installing, configuring, and running Apache* Hadoop on Clear Linux* OS. 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.
Before following this tutorial, you should follow the Install Clear Linux* OS on bare metal (automatic) to ensure you have installed Clear Linux OS.
Before you install any new packages, update Clear Linux OS with the following command:
sudo swupd update
For the purposes of this tutorial, we will install Hadoop in a single machine running both the master and slave daemons.
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
To create the configuration directory, enter the following command:
sudo mkdir /etc/hadoop
Copy the defaults from /usr/share/defaults/hadoop to /etc/hadoop with the following command:
$ sudo cp /usr/share/defaults/hadoop/* /etc/hadoop
Since Clear Linux OS is a stateless system, you should 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, we must edit them to fit our needs. The NameNode server is the master server. It manages the namespace of the files system and regulates the clients’ access to files. The first file we edit, /etc/hadoop/core-site.xml, informs the Hadoop daemon where NameNode is running.
In this tutorial, our NameNode runs in our localhost. Follow these steps to set it up correctly:
Open the /etc/hadoop/core-site.xml file using the editor of your choice 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>
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 said blocks. In this example, we are setting 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>
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>
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
Create a SSH key. If you already have one, skip this step.
sudo ssh-keygen -t rsa
Copy the key to your authorized keys.
sudo cat /root/.ssh/id_rsa.pub | sudo tee -a /root/.ssh/authorized_keys
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, we are ready to start the daemons.
When we format the NameNode server, it formats the meta-data related to data nodes. Thus, all the information on the data nodes is lost and the nodes can be reused for new data.
Format the NameNode server with the following command:
sudo hdfs namenode -format
Start the DFS in NameNode and DataNodes with the following command:
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)?
Enter yes to continue.
Start the YARN daemons ResourceManager and NodeManager with the following command:
Ensure everything is running as expected with the following command:
The console output should be similar to:
22674 DataNode 26228 Jps 22533 NameNode 23046 ResourceManager 22854 SecondaryNameNode 23150 NodeManager
Run the MapReduce wordcount example
Create the input directory.
sudo hdfs dfs -mkdir -p /user/root/input
Copy a file from the local file system to the HDFS.
sudo hdfs dfs -copyFromLocal local-file /user/root/input
Run the wordcount example.
sudo hadoop jar /usr/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.8.0.jar wordcount input output
Read 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
You 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!