• Articles
  • Tutorials
  • Interview Questions

How to Install and Setup Hadoop Single Node

How to Install and Setup Hadoop Single Node

Setting-up a single Hadoop node needs the administrator to abide by certain essential criteria:

Criteria Hadoop Single Node
Hadoop configuration Windows or Linux
characteristics Non-distributed mode as a single Java process
application Testing, prototyping, future scaling of nodes

One the above criteria are met, following steps need to be carried out:

Step 1: Download Hadoop

For Hadoop to be installed there are some certain pre-requisites such as Supportive platforms like GNU/Linux or Win32 and softwares like Jawed and SSH must be installed and enabled; a proper environment is needed for the system to be installed. If your Hadoop cluster does not come with all the requisites then you will have to download and install them by yourself which is not that difficult. You can download the latest Jaw version compatible with Hadoop by clicking here.

Further Configuration of SSH access is needed to enable master/principal and secondary node to get access to the system and take over the slave nodes and handle local users and machines. Generate an SSH key, log in and run the command of key generation. The last step of this process is to check whether machine/machines are connected and working with the main user enabling the local host to permanently combine with other known hosts.

Step 2: Hadoop Installation

You will need a Hadoop distribution which is available on Apache Download Mirrors:

https://www.apache.org/dyn/closer.cgi/hadoop/common/

To make things lot easier you can install softwares like Ubunto-64 bit or MVPlayer

In Ubuntu you have an option of Downloading Hadoop by its latest release, choose to download a stable release, unpack the download and extract it.

Step 3: Configure jaw path

This will start the Hadoop installation process and the next step of the installation will be configuration of your Jaw path. The step is simple as you just have to edit the pre defined perimeter of the path in the system and change it according to your user defined path.

Step 4: Edit the location

Edit the built in changeable location address according to your own Jaw address and save it.

Step 5: Add Hadoop System User

In the next step would be to add dedicated Hadoop system user to make the system operational. This step isn’t that much important but it will help keeping Hadoop segregated from other applications, user IDs and software.

Now disable IPv6 as it is necessary to unbind Hadoop but if you are connected to IPv6 network then there is no need to disable it.

Certification in Bigdata Analytics

Step 6: Format and Edit the Hadoop nodes

The last step is to format and edit the nodes of Hadoop file system, which is only necessary if the system is not already in use. The process is performed by a simple command

Hadoop namenode-format

Now you can make sure whether the software is fully operational or not by giving a task to the system, hopefully this will work and you will have a smile on your face.

Hadoop can be stopped instantly by commands given below;

  • Stop-dfs.sh
  • Stop-yarn.sh

Hadoop has many web interfaces which are very much user friendly, available at these addresses;

  • http://localhost50070
  • http://localhost50090

This ends the whole process and now you can enjoy the ease of handling your big data conveniently and effectively.

However working on Hadoop system will require a professional to get Hadoop training which will improve his expertise and skill.  As Big data technologies are very imperative to use and are very helpful managing the huge volumes of data. Intellipaat lets you master this popular technology in a most efficient way by emphasizing practical implementation of Big Data Hadoop in numerous ways.

Course Schedule

Name Date Details
Big Data Course 30 Nov 2024(Sat-Sun) Weekend Batch View Details
07 Dec 2024(Sat-Sun) Weekend Batch
14 Dec 2024(Sat-Sun) Weekend Batch

About the Author

Technical Research Analyst - Big Data Engineering

Abhijit is a Technical Research Analyst specialising in Big Data and Azure Data Engineering. He has 4+ years of experience in the Big data domain and provides consultancy services to several Fortune 500 companies. His expertise includes breaking down highly technical concepts into easy-to-understand content.