Learn Hadoop in 24 Hours

Hadoop has changed the way large data sets are analyzed, stored, transferred, and processed. At such low cost, it provides benefits like supports partial failure, fault tolerance, consistency, scalability, flexible schema, and so on. It also supports cloud computing. More and more number of individuals are looking forward to mastering their Hadoop skills.

While initiating with Hadoop, most users are unsure about how to proceed with Hadoop. They are not aware of what are the pre-requisite or data structure they should be familiar with. Or How to make the most efficient use of Hadoop and its ecosystem. To help them with all these queries and other issues this e-book is designed.

The book gives insights into many of Hadoop libraries and packages that are not known to many Big data Analysts and Architects. The e-book also tells you about Hadoop MapReduce and HDFS. The example in the e-book is well chosen and demonstrates how to control Hadoop ecosystem through various shell commands. With this book, users will gain expertise in Hadoop technology and its related components. The book leverages you with the best Hadoop content with the lowest price range.

After going through this book, you will also acquire knowledge on Hadoop Security required for Hadoop Certifications like CCAH and CCDH. It is a definite guide to Hadoop.

Table Contents

Chapter 1: What Is Big Data

Examples Of 'Big Data'

Categories Of 'Big Data'

Characteristics Of 'Big Data'

Advantages Of Big Data Processing

Chapter 2: Introduction to Hadoop

Components of Hadoop

Features Of 'Hadoop'

Network Topology In Hadoop

Chapter 3: Hadoop Installation

Chapter 4: HDFS

Read Operation

Write Operation

Access HDFS using JAVA API

Access HDFS Using COMMAND-LINE INTERFACE

Chapter 5: Mapreduce

How MapReduce works

How MapReduce Organizes Work?

Chapter 6: First Program

Understanding MapReducer Code

Explanation of SalesMapper Class

Explanation of SalesCountryReducer Class

Explanation of SalesCountryDriver Class

Chapter 7: Counters & Joins In MapReduce

Two types of counters

MapReduce Join

Chapter 8: MapReduce Hadoop Program To Join Data

Chapter 9: Flume and Sqoop

What is SQOOP in Hadoop?

What is FLUME in Hadoop?

Some Important features of FLUME

Chapter 10: Pig

Introduction to PIG

Create your First PIG Program

PART 1) Pig Installation

PART 2) Pig Demo

Chapter 11: OOZIE

What is OOZIE?

How does OOZIE work?

Example Workflow Diagram

Oozie workflow application

Why use Oozie?

FEATURES OF OOZIE

© 2021 PublishDrive (E-kirja): 6610000317455

Julkaisupäivä

E-kirja: 30. lokakuuta 2021