Course Overview

Hadoop framework is a part of Apache project and based on java. It is used to process huge amounts of data on a distributed computing environment. Hadoop supports and provides high data transfer for systems with thousands of nodes having millions of GBs of data without any interruptions. With our course, you will learn all the concepts of Hadoop and you will be able to implement in your projects according to your needs. Join this course now if you are looking to develop an amazing career in this industry.

Big Data Hadoop Course Content:

Introduction of Big Data and Hadoop
  • What is Big Data?
  • Classification of Big Data.
  • Characteristics of Big Data.
  • Challenges Associated with Big Data.
  • Traditional Approach of Storing and Processing Big Data.
  • What is Hadoop?
  • Features of Hadoop.
  • What is Hadoop EcoSystem?
Exploring HDFS
  • What is HDFS?
  • HDFS Daemons: NameNode and DataNode Explained.
  • HDFS Daemons: Secondary NameNode Explained.
  • How HDFS Manages FileSystem MetaData?
  • Reading Data from HDFS.
  • Writing Data to HDFS.
  • What is Rack Awareness?
  • NameNode Federation Explained.
  • What is MapReduce?
  • MapReduce Daemons JobTracker and TaskTracker Explained.
  • What is YARN?
  • How MapReduce Works?
  • What is Key / Value Pair?
  • Hadoop Java API's Explained.
Understanding Hadoop Operating Modes
  • Creating a Virtual Machine in VMWare.
  • Downloading Linux.
  • Installing Linux.
  • Configuring Linux.
  • Downloading and Installing Hadoop.
  • Configuring Hadoop and Starting Up the Hadoop Cluster.
  • Installing a Single Node, Pseudo Hadoop Cluster on a Local Machine
  • Installing a MultiNode, Fully Distributed, Hadoop Cluster on a Local Machine
  • Setting up a MultiNode Apache Hadoop Cluster on Local machine
  • Setting Up and Connecting to an Amazon EC2 Instance.
Maintaining a Hadoop Cluster
  • Finding Data for Practice.
  • Starting and Stopping Hadoop Daemons.
  • Adding a Node to the Cluster.
  • Removing a Node from the Cluster.
  • Checking the Hadoop Distributed File System.
  • Exploring Commands in Hadoop.
  • Adding a TaskTracker.
  • Removing a TaskTracker.
  • Importing Data into HDFS.
  • Exporting Data out of HDFS.
  • Copying Data Using DistCP.
  • Balancing a DataNode.
  • Turning On & Turning Off SafeMode.
  • Programming with MapReduce
  • Setting Up Development Environment.

What are the requirements?

  • Understanding or previous experience of databases.
  • Concepts of java should be clear.

What am I going to get from this course?

  • Be able to download and install Hadoop on your computer
  • Learn to build hadoop cluster from scratch
  • Build strong databases with hadoop fundamentals
  • Learn the concepts related to MapReduce