Course Overview:

In this training you will understand Hadoop MapReduce framework and the working of MapReduce on data stored in HDFS. You will learn about YARN concepts in MapReduce. MapReduce Use Cases, Traditional way Vs MapReduce way, Why MapReduce, Hadoop 2.x MapReduce Architecture, Hadoop 2.x MapReduce Components, YARN MR Application Execution Flow, YARN Workflow, Anatomy of MapReduce Program, Demo on MapReduce.

Course Content:


♦ Map Reduce Overview

♦ Map Operation

♦ Job Submissions

♦ Job Initialization

♦ Task Assignment

♦ Job Completion

♦ Job Scheduling

♦ Job Failures

♦ Shuffle and sort

♦ Word Count Problem

♦ Word Count Flow and Solution

♦ Word Count Flow and Solution

♦ Algorithms

♦ Setting up Eclipse Development Environment, Creating Map Reduce Projects, Debugging and Unit Testing

♦ Developing a map-reduce algorithm on a real-world scenario

Advance Map Reduce Concepts

♦ Counters

♦ Sorting

♦ Joins - Map Side and Reduce Side

♦ Side Data Distribution

♦ MapReduce Combiner

♦ MapReduce Partitioner

♦ MapReduce Distributed Cache

Map Reduce Types and Formats

♦ Data Types

♦ File Formats

♦ Input Formats

♦ Output Formats

♦ Explain the Driver, Mapper, and Reducer code

♦ Configuring development environment - Eclipse

♦ Writing Unit Test

♦ Running locally

♦ Running on Cluster.

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