How to Install Hadoop on Ubuntu 13.10

Prerequisites #

The only prerequisite for this tutorial is a VPS with Ubuntu 13.10 x64 installed.
You will need to execute commands from the command line which you can do in one of the two ways:

Use SSH to access the droplet.

Use the ‘Console Access’ from the Digital Ocean Droplet Management Panel

What is Hadoop? #

Hadoop is a framework (consisting of software libraries) which simplifies the processing of data sets distributed across clusters of servers. Two of the main components of Hadoop are HDFS and MapReduce.
HDFS is the filesystem that is used by Hadoop to store all the data on. This file system spans across all the nodes that are being used by Hadoop. These nodes could be on a single VPS or they can be spread across a large number of virtual servers.
MapReduce is the framework that orchestrates all of Hadoop’s activities. It handles the assignment of work to different nodes in the cluster.

Benefits of using Hadoop #

The architecture of Hadoop allows you to scale your hardware as and when you need to. New nodes can be added incrementally without having to worry about the change in data formats or the handling of applications that sit on the file system.
One of the most important features of Hadoop is that it allows you to save enormous amounts of money by substituting cheap commodity servers for expensive ones. This is possible because Hadoop transfers the responsibility of fault tolerance from the hardware layer to the application layer.

Installing Hadoop #

Installing and getting Hadoop up and running is quite straightforward. However, since this process requires editing multiple configuration and setup files, make sure that each step is properly followed.

1. Install Java #

Hadoop requires Java to be installed, so let’s begin by installing Java:

apt-get update
apt-get install default-jdk

These commands will update the package information on your VPS and then install Java. After executing these commands, execute the following command to verify that Java has been installed:

java -version

If Java has been installed, this should display the version details as illustrated in the following image:
Java Verification

2. Create and Setup SSH Certificates #

Hadoop uses SSH (to access its nodes) which would normally require the user to enter a password. However, this requirement can be eliminated by creating and setting up SSH certificates using the following commands:

ssh-keygen -t rsa -P ''
cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys

After executing the first of these two commands, you might be asked for a filename. Just leave it blank and press the enter key to continue. The second command adds the newly created key to the list of authorized keys so that Hadoop can use SSH without prompting for a password.
Setup SSH Certificates

3. Fetch and Install Hadoop #

First let’s fetch Hadoop from one of the mirrors using the following command:

wget http://www.motorlogy.com/apache/hadoop/common/current/hadoop-2.3.0.tar.gz

Note: This command uses a download a link on one of the mirrors listed on the Hadoop website. The list of mirrors can be found on this link. You can choose any other mirror if you want to. To download the latest stable version, choose the hadoop-X.Y.Z.tar.gz file from the current or the current2 directory on your chosen mirror.
After downloading the Hadoop package, execute the following command to extract it:

tar xfz hadoop-2.3.0.tar.gz

This command will extract all the files in this package in a directory named hadoop-2.3.0. For this tutorial, the Hadoop installation will be moved to the /usr/local/hadoop directory using the following command:

mv hadoop-2.3.0 /usr/local/hadoop 

Note: The name of the extracted folder depends on the Hadoop version your have downloaded and extracted. If your version differs from the one used in this tutorial, change the above command accordingly.

4. Edit and Setup Configuration Files #

To complete the setup of Hadoop, the following files will have to be modified:

~/.bashrc
/usr/local/hadoop/etc/hadoop/hadoop-env.sh
/usr/local/hadoop/etc/hadoop/core-site.xml
/usr/local/hadoop/etc/hadoop/yarn-site.xml
/usr/local/hadoop/etc/hadoop/mapred-site.xml.template
/usr/local/hadoop/etc/hadoop/hdfs-site.xml

i. Editing ~/.bashrc
Before editing the .bashrc file in your home directory, we need to find the path where Java has been installed to set the JAVA_HOME environment variable. Let’s use the following command to do that:

update-alternatives --config java

This will display something like the following:
Get Java Path
The complete path displayed by this command is:

/usr/lib/jvm/java-7-openjdk-amd64/jre/bin/java

The value for JAVA_HOME is everything before /jre/bin/java in the above path – in this case, /usr/lib/jvm/java-7-openjdk-amd64. Make a note of this as we’ll be using this value in this step and in one other step.
Now use nano (or your favored editor) to edit ~/.bashrc using the following command:

nano ~/.bashrc

This will open the .bashrc file in a text editor. Go to the end of the file and paste/type the following content in it:

#HADOOP VARIABLES START
export JAVA_HOME=/usr/lib/jvm/java-7-openjdk-amd64
export HADOOP_INSTALL=/usr/local/hadoop
export PATH=$PATH:$HADOOP_INSTALL/bin
export PATH=$PATH:$HADOOP_INSTALL/sbin
export HADOOP_MAPRED_HOME=$HADOOP_INSTALL
export HADOOP_COMMON_HOME=$HADOOP_INSTALL
export HADOOP_HDFS_HOME=$HADOOP_INSTALL
export YARN_HOME=$HADOOP_INSTALL
export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_INSTALL/lib/native
export HADOOP_OPTS="-Djava.library.path=$HADOOP_INSTALL/lib"
#HADOOP VARIABLES END

Note 1: If the value of JAVA_HOME is different on your VPS, make sure to alter the first export statement in the above content accordingly.
Note 2: Files opened and edited using nano can be saved using Ctrl + X. Upon the prompt to save changes, type Y. If you are asked for a filename, just press the enter key.
The end of the .bashrc file should look something like this:
.bashrc contens
After saving and closing the .bashrc file, execute the following command so that your system recognizes the newly created environment variables:

source ~/.bashrc

Putting the above content in the .bashrc file ensures that these variables are always available when your VPS starts up.

ii. Editing /usr/local/hadoop/etc/hadoop/hadoop-env.sh #

Open the /usr/local/hadoop/etc/hadoop/hadoop-env.sh file with nano using the following command:

nano /usr/local/hadoop/etc/hadoop/hadoop-env.sh

In this file, locate the line that exports the JAVA_HOME variable. Change this line to the following:

export JAVA_HOME=/usr/lib/jvm/java-7-openjdk-amd64

Note: If the value of JAVA_HOME is different on your VPS, make sure to alter this line accordingly.
The hadoop-env.sh file should look something like this:
hadoop-env.sh contents
Save and close this file. Adding the above statement in the hadoop-env.sh file ensures that the value of JAVA_HOME variable will be available to Hadoop whenever it is started up.

iii. Editing /usr/local/hadoop/etc/hadoop/core-site.xml #

The /usr/local/hadoop/etc/hadoop/core-site.xml file contains configuration properties that Hadoop uses when starting up. This file can be used to override the default settings that Hadoop starts with.
Open this file with nano using the following command:

nano /usr/local/hadoop/etc/hadoop/core-site.xml

In this file, enter the following content in between the <configuration></configuration> tag:

<property>
   <name>fs.default.name</name>
   <value>hdfs://localhost:9000</value>
</property>

The core-site.xml file should look something like this:
core-site.xml contents
Save and close this file.

iv. Editing /usr/local/hadoop/etc/hadoop/yarn-site.xml #

The /usr/local/hadoop/etc/hadoop/yarn-site.xml file contains configuration properties that MapReduce uses when starting up. This file can be used to override the default settings that MapReduce starts with.
Open this file with nano using the following command:

nano /usr/local/hadoop/etc/hadoop/yarn-site.xml

In this file, enter the following content in between the <configuration></configuration> tag:

<property>
   <name>yarn.nodemanager.aux-services</name>
   <value>mapreduce_shuffle</value>
</property>
<property>
   <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
   <value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>

The yarn-site.xml file should look something like this:
yarn-site.xml contents
Save and close this file.

v. Creating and Editing /usr/local/hadoop/etc/hadoop/mapred-site.xml #

By default, the /usr/local/hadoop/etc/hadoop/ folder contains the /usr/local/hadoop/etc/hadoop/mapred-site.xml.template file which has to be renamed/copied with the name mapred-site.xml. This file is used to specify which framework is being used for MapReduce.
This can be done using the following command:

cp /usr/local/hadoop/etc/hadoop/mapred-site.xml.template /usr/local/hadoop/etc/hadoop/mapred-site.xml

Once this is done, open the newly created file with nano using the following command:

nano /usr/local/hadoop/etc/hadoop/mapred-site.xml

In this file, enter the following content in between the <configuration></configuration> tag:

<property>
   <name>mapreduce.framework.name</name>
   <value>yarn</value>
</property>

The mapred-site.xml file should look something like this:
mapred-site.xml contents
Save and close this file.

vi. Editing /usr/local/hadoop/etc/hadoop/hdfs-site.xml #

The /usr/local/hadoop/etc/hadoop/hdfs-site.xml has to be configured for each host in the cluster that is being used. It is used to specify the directories which will be used as the namenode and the datanode on that host.
Before editing this file, we need to create two directories which will contain the namenode and the datanode for this Hadoop installation. This can be done using the following commands:

mkdir -p /usr/local/hadoop_store/hdfs/namenode
mkdir -p /usr/local/hadoop_store/hdfs/datanode

Note: You can create these directories in different locations, but make sure to modify the contents of hdfs-site.xml accordingly.
Once this is done, open the /usr/local/hadoop/etc/hadoop/hdfs-site.xml file with nano using the following command:

nano /usr/local/hadoop/etc/hadoop/hdfs-site.xml

In this file, enter the following content in between the <configuration></configuration> tag:

<property>
   <name>dfs.replication</name>
   <value>1</value>
 </property>
 <property>
   <name>dfs.namenode.name.dir</name>
   <value>file:/usr/local/hadoop_store/hdfs/namenode</value>
 </property>
 <property>
   <name>dfs.datanode.data.dir</name>
   <value>file:/usr/local/hadoop_store/hdfs/datanode</value>
 </property>

The hdfs-site.xml file should look something like this:
hdfs-site.xml contents
Save and close this file.

Format the New Hadoop Filesystem #

After completing all the configuration outlined in the above steps, the Hadoop filesystem needs to be formatted so that it can start being used. This is done by executing the following command:

hdfs namenode -format

Note: This only needs to be done once before you start using Hadoop. If this command is executed again after Hadoop has been used, it’ll destroy all the data on the Hadoop file system.

Start Hadoop #

All that remains to be done is starting the newly installed single node cluster:

start-dfs.sh

While executing this command, you’ll be prompted twice with a message similar to the following:

Are you sure you want to continue connecting (yes/no)?

Type in yes for both these prompts and press the enter key. Once this is done, execute the following command:

start-yarn.sh

Executing the above two commands will get Hadoop up and running. You can verify this by typing in the following command:

jps

Executing this command should show you something similar to the following:
jps command
If you can see a result similar to the depicted in the screenshot above, it means that you now have a functional instance of Hadoop running on your VPS.

Next Steps #

If you have an application that is set up to use Hadoop, you can fire that up and start using it with the new installation. On the other hand, if you’re just playing around and exploring Hadoop, you can start by adding/manipulating data or files on the new filesystem to get a feel for it.