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 custom requirements.
- ADVANCE level Mapreduce concepts which are not easily available online.
- Real-time Mapreduce Case studies asked in Hadoop Interviews with its proper Mapreduce code run on cluster.
Mapreduce frameworkis the closest to Hadoop in terms of processing Big 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-timeMapreduce is way more than that. In Live Big data projects we have to override lot many default implementations of Mapreduce framework to make them work according to our requirements.
This course isan answer to thequestion"What conceptsof HadoopMapreduce are used in Live Big data projects and How to implement them in a program ?" To answer this,every Mapreduce concept in the course is explained practicallyvia aMapreduce program.
Every lecture in this course is explained in 2 Steps.
Step1: Explanation of a Hadoop component
Step 2 : Practicals-How to implement that component in a MapReduce program.
The overall inclusions and benefitsof this course:
Complete Hadoop Mapreduce explainedfrom scratch to Real-Time implementation.
Each and Every Hadoop concept is backed by a HANDS-ONMapreduce 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 waythat even a non technical person can understand.
Mapreduce codes and Datasetsused in lectures areattached for your convenience.
Includes multiple sections on 'Case Studies' that are asked generally in Hadoop Interviews.
