Apache Hadoop course Expert level by Feria IT Solutions

Introduction

Course Objective Summary

During this course, you will learn:

Introduction to Big Data and Hadoop

Hadoop ecosystem - Concepts

Hadoop Map-reduce concepts and features

Developing the map-reduce Applications

Pig concepts

Hive concepts

HBASE Concepts

Mongo DB Concepts

Sqoop Concepts

Real Life Use Cases

Introduction to Big Data and Hadoop

What is Big Data?

What are the challenges for processing big data?

What technologies support big data?

What is Hadoop?

Why Hadoop?

History of Hadoop

Use Cases of Hadoop

Hadoop eco System

HDFS

Map Reduce

Statistics

Understanding the Cluster

Typical workflow

Writing files to HDFS

Reading files from HDFS

Rack Awareness

5 daemons

Let s talk Map Reduce

Before Map reduce

Map Reduce Overview

Word Count Problem

Word Count Flow and Solution

Map Reduce Flow

Algorithms for simple problems

Algorithms for complex problems

Developing the Map Reduce Application

Data Types

File Formats

Explain the Driver, Mapper and Reducer code

Configuring development environment - Eclipse

Writing Unit Test

Running locally

Running on Cluster

Hands on exercises

c

Anatomy of Map Reduce Job run

Job Submission

Job Initialization

Task Assignment

Job Completion

Job Scheduling

Job Failures

Shuffle and sort

Oozie Workflows

Hands on Exercises

Map Reduce Types and Formats

MapReduce Types

Input Formats - Input splits & records, text input,binary input, multiple inputs & database input.

Output Formats - text Output, binary output, multiple outputs, lazy output and database output

Hands on Exercises.

Map Reduce Features

Counters

Sorting

Joins - Map Side and Reduce Side

Side Data Distribution

MapReduce Combiner

MapReduce Partitioner

MapReduce Distributed Cache

Hands Exercises

Hive and PIG

Fundamentals

When to Use PIG and HIVE

Concepts

Hands on Exercises

HBASE

CAP Theorem

Hbase Architecture and concepts

Programming and Hands on Exercises

Case Studies Discussions