The Best Free Resource to Learn Hadoop: A Comprehensive Guide

Introduction to Hadoop and Big Data

Hadoop has revolutionized the way large datasets are analyzed, stored, transferred, and processed. At a cost-effective price, it provides numerous benefits such as partial failure support, fault tolerance, consistency, scalability, and flexible schema. It also supports cloud computing, making it an essential tool for large-scale data processing. Many individuals are now looking to master Hadoop skills for their professional growth. This e-book aims to provide a comprehensive guide to learning Hadoop.

What is Big Data

Chapter 1: What Is Big Data

tExamples of Big Data tCategories of Big Data tCharacteristics of Big Data tAdvantages of Big Data Processing

Introduction to Hadoop

Chapter 2: Introduction to Hadoop

tComponents of Hadoop tFeatures of Hadoop tNetwork Topology in Hadoop

Hadoop Installation

Chapter 3: Hadoop Installation

This section covers the installation process of Hadoop, including setting up the environment, configuring nodes, and starting the Hadoop cluster.

Hadoop Distributed File System (HDFS)

Chapter 4: HDFS

tRead Operation tWrite Operation tAccessing HDFS Using JAVA API tAccessing HDFS Using COMMAND-LINE INTERFACE

MapReduce

Chapter 5: MapReduce

tHow MapReduce Works tHow MapReduce Organizes Work

First Program in Hadoop

Chapter 6: First Program

This chapter explains the MapReducer code and provides detailed explanations of key classes:

tExplanation of SalesMapper Class tExplanation of SalesCountryReducer Class tExplanation of SalesCountryDriver Class

Counters and Joins in MapReduce

Chapter 7: Counters and Joins in MapReduce

tTwo types of counters tMapReduce Join

Hadoop MapReduce Program to Join Data

Chapter 8: Hadoop MapReduce Program to Join Data

This chapter illustrates how to join data using MapReduce, covering the step-by-step process and best practices.

Hadoop Ecosystem Tools

Chapter 9: Flume and Sqoop

tIntroduction: What is SQOOP in Hadoop tIntroduction: What is FLUME in Hadoop tImportant features of FLUME

Pig for Hadoop Data Processing

Chapter 10: Pig

tIntroduction to PIG tCreate your First PIG Program tPART 1 Pig Installation tPART 2 Pig Demo

OOZIE for Hadoop Workflow Management

Chapter 11: OOZIE

tIntroduction: What is OOZIE tHow does OOZIE Work tExample Workflow Diagram tOozie workflow application tWhy use Oozie tFeatures of OOZIE

By following this e-book, readers will gain expertise in Hadoop technology and its related components. The book is designed to provide insights into lesser-known Hadoop libraries and packages, making it an invaluable resource for Big Data Analysts and Architects.

Conclusion

After completing this e-book, readers will not only understand the basics of Hadoop but will also acquire knowledge on Hadoop security, which is essential for Hadoop certifications like CCAH and CCDH. This comprehensive guide is a definite resource for anyone looking to learn Hadoop effectively.