A to Z of Hadoop MAPREDUCE - From Scratch to its Real Time Implementation with HANDS-ON Coding of every component of MR

Mapreduce framework is closest to Hadoop in terms of processing data. It is considered as atomic processing unit in Hadoop and that is why it is never going to be obsolete.

Knowing only basics of MapReduce (Mapper, Reducer etc) is not at all sufficient to work in any Real-time Hadoop Mapreduce project of companies. These basics are just tip of the iceberg in Mapreduce programming. Real-time Mapreduce is way more than that. In Live Hadoop Mapreduce projects we have to override lot many default implementations of Mapreduce framework to make them work according to our requirements.

This course is answer to the question "What concepts of Hadoop Mapreduce are used in Live projects and How to implement them in a program ?" To answer this, every Mapreduce concept in the course is explained practically via a Mapreduce program.

Every lecture in this course is explained in 2 Steps.

Step 1 : Explanation of a Hadoop component | Step 2 : Practicals - How to implement that component in a MapReduce program.

The overall inclusions and benefits of this course:

Complete Hadoop Mapreduce explained from scratch to Real-Time implementation.

Each and Every Hadoop concept is backed by a HANDS-ON Mapreduce code.

Advance level Mapreduce concepts which are even not available on Internet.

For non Java backgrounder's help, All Mapreduce Java codes are explained line by line in such a way that even a non technical person can understand.

Mapreduce codes and Datasets used in lectures are attached for your convenience. 

Includes a section 'Case Studies' that are asked generally in Hadoop Interviews.

What you'll learn

Every concept that comes under Hadoop Mapreduce framework from SCRATCH to LIVE PROJECT Implementation.

Learn to write Mapreduce Codes in a Real-Time working environment.

Understand the working of each and every component of Hadoop Mapreduce with HANDS-ON Practicals.

Override the default implementation of Java classes in Mapreduce and Code it according to our requirements.

ADVANCE level Mapreduce concepts which are even not available on Internet.

Real-time Mapreduce Case studies asked in Hadoop Interviews with its proper Mapreduce code run on cluster.