Hello everyone! In this blog, you are going to learn about how to Master Hadoop Ecosystem and Their Components. Commonly people says Practice Make a Man Perfect but you should practice in a way that it makes you perfect in that thing. So before jumping into mastering Hadoop Let’s talk about some Basics of Hadoop.
What do you mean by Hadoop?
Hadoop is a open source platform for storing large volume of data and running applications on clusters of commodity software. It gives us massive amount of space and data storage facility, ability to handle different virtually limitless tasks. Its main job is to support big data components and support some advanced analytics like Predictive analytics, data mining, ML
Now you get idea about Hadoop lets discuss about it’s components.
All the components of the Hadoop ecosystem, as explicit entities are evident. Hadoop architecture gives prominence to Hadoop common, Hadoop YARN, Hadoop Distributed File Systems (HDFS) and Hadoop Map Reduce of the Hadoop Ecosystem. Hadoop common provides all Java libraries, utilities, OS level abstraction, necessary Java files and script to run Hadoop, while Hadoop YARN is a framework for job scheduling and cluster resource management.
Now Tip to master this ecosystem
Learn Linux commands For installing Hadoop, Linux is preferred to be the operating system and UBUNTU as server distribution. So it’s a advise you should have a basic knowledge of Linux before start learning Hadoop. It is a good practice if you are aware of few commands in Linux.
FOCUS ON UNDERSTANDING all the different components like HDFS, MapReduce, and Yarn in the architecture. Once you get the picture of this architecture, then focus on the overall Hadoop ecosystem which means you need to have knowledge about all the tools.
To understand each and every thing step by step I will suggest Easyshisha Platform to learn the basic components and ecosystem of Hadoop and DataScience.
HDFS (Hadoop Distribution File System)
HDFS is the primary storage system of Hadoop. It is a java based file system that provides scalability, fault tolerance, reliable and cost efficient data storage system.
There are two major components of Hadoop HDFS- NameNode and DataNode. Well name node is also known as master node and it won’t store the data it will store the meta data. DataNode also known as slave node it is use to store the actual data.
Hadoop MapReduce is the core Hadoop ecosystem component which provides data processing. It is a software for easy writing applications. MapReduce programs are parallel in nature, thus are very useful for performing large-scale data analysis using multiple machines in the cluster.