Hadoop Administration: Installation scripts of Apache Hadoop (2.6.0) on Ubuntu Unicorn as Multi-Node cluster

Recently , just published a quick step by step guide on deployment of Apache Hadoop (2.6.0) single -node cluster on Ubuntu unicorn(14.10) image, you can get the full installation video here.


Here, the full deployment of Apache Hadoop (2.6.0) multi-node cluster setup details are provided. The primary hardward requirements are needed to run the setup :

1. VMware Player/Workstation(if Windows/Linux) or VMware Fusion(if OSX)

2. More than 4 GB of RAM for primary OS

3. More than 60 GB of Disk space

4. Intel VT-X capable processor.

5. Ubuntu/CentOs/Red Hat/Sese OS Image(as guest OS)

Now, the step by step multinode hadoop clustering  scripts are provided.


Checkout the Ipaddress of each master & slaves node:


Namenode > hadoopmaster >

Datanodes > hadoopslave1 >
hadoopslave2 >
hadoopslave3 >

Clone Hadoop Single node cluster as hadoopmaster

Hadoopmaster Node

$ sudo gedit /etc/hosts


$ sudo gedit /etc/hostname


$ cd /usr/local/hadoop/etc/hadoop

$ sudo gedit core-site.xml

replace localhost as hadoopmaster

$ sudo gedit hdfs-site.xml

replace value as 3 (represents no of datanode)

          $ sudo gedit yarn-site.xml

add the following configuration


$ sudo gedit mapred-site.xml.template
replace mapreduce.framework.name as mapred.job.tracker

replace yarn as hadoopmaster:54311

$ sudo rm -rf /usr/local/hadoop/hadoop_data

Shutdown hadoopmaster node

Clone Hadoopmaster Node as hadoopslave1, hadoopslave2, hadoopslave3

Hadoopslave Node (conf should be done on each slavenode)

$ sudo gedit /etc/hostname


          $ sudo mkdir -p /usr/local/hadoop/hadoop_data/hdfs/datanode

$ sudo chown -R trainer:trainer /usr/local/hadoop

          $ sudo gedit /usr/local/hadoop/etc/hadoop/hdfs-site.xml

remove dfs.namenode.dir property section

reboot all nodes

Hadoopmaster Node

          $ sudo gedit /usr/local/hadoop/etc/hadoop/masters


$ sudo gedit /usr/local/hadoop/etc/hadoop/slaves

remove localhost and add


$ sudo gedit /usr/local/hadoop/etc/hadoop/hdfs-site.xml

   remove dfs.datanode.dir property section

          $ sudo mkdir -p /usr/local/hadoop/hadoop_data/hdfs/namenode

$ sudo chown -R trainer:trainer /usr/local/hadoop

$ sudo ssh-copy-id -i ~/.ssh/id_dsa.pub trainer@hadoopmaster

$ sudo ssh-copy-id -i ~/.ssh/id_dsa.pub trainer@hadoopslave1

$ sudo ssh-copy-id -i ~/.ssh/id_dsa.pub trainer@hadoopslave2

$ sudo ssh-copy-id -i ~/.ssh/id_dsa.pub trainer@hadoopslave3

$ ssh hadoopmaster

$ exit

$ ssh hadoopslave1

$ exit

$  ssh hadoopslave2

$ exit

$ ssh hadoopslave3

$ exit

$ hadoop namenode -format

$ start-all.sh

$ jps (check in all 3 datanodes)

for checking Hadoop web console :

http://hadoopmasteripaddress :8088/
http://hadoopmasteripaddress :50070/
http://hadoopmasteripaddress :50090/

http://hadoopmasteripaddress  :50075/



About Anindita
Anindita Basak is working as Big Data Cloud Consultant in Microsoft. Worked in multiple MNCs as Developer & Senior Developer on Microsoft Azure, Data Platform, IoT & BI , Data Visualization, Data warehousing & ETL & of course in Hadoop platform.She played both as FTE & v- employee in Azure platform teams of Microsoft.Passionate about .NET , Java, Python & Data Science. She is also an active Big Data & Cloud Trainer & would love share her experience in IT Training Industry. She is an author, forum contributor, blogger & technical reviewer of various books on Big Data Hadoop, HDInsight, IoT & Data Science, SQL Server PDW & PowerBI.

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