Setting up Hadoop and HBase in a fully distributed mode involves configuring multiple machines to function together as a single unit. This is essential for handling big data tasks efficiently across a cluster of servers, enhancing both performance and data redundancy. Here's an in-depth guide on how to configure Hadoop and HBase for fully-distributed operations.

Prerequisites

Before you begin, ensure the following prerequisites are met:

• At least three server machines (nodes) are recommended to set up the cluster, each having Java installed.
• The same Linux distribution should be installed on all nodes.
• SSH access is required between all nodes without requiring a password.

Step 1: Configuring Hadoop

1.1 Install Hadoop on All Nodes

Download and install the latest version of Hadoop on all nodes. Ensure that Hadoop’s environment variables are correctly set so that the hadoop command is globally accessible.

1.2 Edit Configuration Files

You must configure several XML files in $HADOOP_HOME/etc/hadoop:

• core-site.xml

1  <configuration>
2      <property>
3          <name>fs.defaultFS</name>
4          <value>hdfs://NameNode:9000</value>
5      </property>
6  </configuration>

• hdfs-site.xml

1  <configuration>
2      <property>
3          <name>dfs.replication</name>
4          <value>3</value>
5      </property>
6      <property>
7          <name>dfs.namenode.name.dir</name>
8          <value>file:/hadoop/hdfs/namenode</value>
9      </property>
10      <property>
11          <name>dfs.datanode.data.dir</name>
12          <value>file:/hadoop/hdfs/datanode</value>
13      </property>
14  </configuration>

• mapred-site.xml

1  <configuration>
2      <property>
3          <name>mapreduce.framework.name</name>
4          <value>yarn</value>
5      </property>
6  </configuration>

• yarn-site.xml

1  <configuration>  
2      <property>
3          <name>yarn.resourcemanager.hostname</name>
4          <value>NameNode</value>
5      </property>
6  </configuration>

Replace "NameNode" with the hostname of your master node.

1.3 Configure the master and slave nodes

In the masters file, add the hostname of the master node. In the slaves file, add the hostname of all slave nodes:

nano $HADOOP_HOME/etc/hadoop/masters
nano $HADOOP_HOME/etc/hadoop/slaves

Step 2: Formatting namenode and Starting Hadoop

On the master node, format the Hadoop filesystem:

hadoop namenode -format

Then, start the Hadoop daemons:

start-dfs.sh
start-yarn.sh

Step 3: Configuring HBase

3.1 Install HBase on All Nodes

Download and install HBase on all nodes. Ensure HBase’s environment variables are set correctly.

3.2 Edit Configuration Files

Edit $HBASE_HOME/conf/hbase-site.xml:

1<configuration>
2    <property>
3        <name>hbase.rootdir</name>
4        <value>hdfs://NameNode:9000/hbase</value>
5    </property>
6    <property>
7        <name>hbase.cluster.distributed</name>
8        <value>true</value>
9    </property>
10</configuration>

Adjust the regionservers file in $HBASE_HOME/conf to include the hostnames of all HBase region servers (usually your slave nodes).

Step 4: Starting HBase

From any node, start HBase:

start-hbase.sh

Key Configuration Properties

Monitoring and Maintenance

Once Hadoop and HBase are up, use monitoring tools like Apache Ambari or the Hadoop Resource Manager UI to help monitor the health and performance of your cluster. Regular backups, consistent monitoring, and timely updates to your setup are crucial to maintaining the efficiency and reliability of your big data infrastructure.

This thorough setup allows organizations to manage big data workflows effectively, leveraging fully distributed Hadoop and HBase configurations to their fullest potential.