- 1. Objective
- 2. Introduction to Best books to learn Big Data Hadoop
- a. Hadoop – The Definitive Guide by Tom White
- b. Hadoop for Dummies by Dirk Deroos
- c. Hadoop in Action by Chuck Lam
- d. Hadoop Operations by Eric Sammers
- e. Map Reduce Design Patterns: Building Effective Algorithms and Analytics for Hadoop by Donald Miner
- f. Programming Pig by Alan Gates
- g. Apache Sqoop Cookbook by Kathleen Ting & Jarek Jarcec Cecho
- h. Programming Hive by Dean Wampler, Edward Capriolo, and Jason Rutherglen
- i. HBase – The Definitive Guide by Lars George
- j. Using Flume by Hari Shreedharan
Through this tutorial, you will learn about best books to learn Big data Hadoop that will help you in becoming Hadoop expert and get various Hadoop job roles in India and abroad. You will learn about various books for Hadoop developer and Hadoop administrator, best book to learn map reduce programming, books for Apache Flume, best book for Apache Sqoop and Pig, best book for Apache HBase and best book to master Apache Hive.
2. Introduction to Best books to learn Big Data Hadoop
Today Big Data is the biggest buzz word in the industry and each and every individual is looking to make a career shift in this emerging and trending technology Apache Hadoop.
Here is our recommendation for some of the best books to learn Hadoop and its ecosystem. Some of them are Hadoop books for beginners while some are for Map Reduce programmers and Big data developers to gain more knowledge.
Below is the list of best Big Data & Hadoop books:
a. Hadoop – The Definitive Guide by Tom White
This is the best book for beginners to learn Hadoop to be Hadoop developers and Hadoop administrators. Language is quite easy and covers concepts of Hadoop and its ecosystem along with features of Hadoop2.x like YARN, HA etc. You will learn how to develop and maintain reliable and scalable multi node systems with Apache Hadoop and how to analyse large datasets with it.
b. Hadoop for Dummies by Dirk Deroos
This book is easy to read and understand. It makes readers understand the value of Big data and covers concepts like origin of Hadoop . its functionality and benefits and few Big Data practical applications. It also covers Hadoop ecosystem and Map Reduce programs and show how Hadoop applications can be used for Data Mining, Problem Solving and Data Analytics and how to avoid common pitfalls while developing Hadoop cluster.
c. Hadoop in Action by Chuck Lam
It provides introduction to Hadoop terminologies and programming in Map Reduce starting with easy examples and gradually moving to show Hadoop usage in complex data analysis tasks. It covers best practices and design patterns of Map Reduce programming.
d. Hadoop Operations by Eric Sammers
This book will explain you methods to maintain large and complex Hadoop clusters. Dedicated chapters are there for Hadoop maintenance, monitoring, backups, troubleshooting in Hadoop etc. to perform these tasks efficiently. It also covers every component of Hadoop to be a Big data Engineer.
e. Map Reduce Design Patterns: Building Effective Algorithms and Analytics for Hadoop by Donald Miner
This book assumes that reader has basic knowledge of Hadoop and is willing to master Map Reduce algorithms. It describes various applications of Map Reduce with Hadoop and various methods to solve Hadoop problems quickly and explains techniques for Map Reduce optimization.
f. Programming Pig by Alan Gates
This is the best book to learn Apache Pig – Hadoop ecosystem component for processing data using Pig Latin scripts. It provides basic to advance level knowledge on Pig including Pig Latin Scripting Language, Grunt Shell and User defined functions for extending Pig. You will also learn how Pig converts these scripts to Map Reduce programs for efficient working in Hadoop.
g. Apache Sqoop Cookbook by Kathleen Ting & Jarek Jarcec Cecho
It is a user guide for Apache Sqoop – Hadoop ecosystem component for transferring data between RDBMS and Hadoop. It focusses on applying parameters that are provided by Command Line Interface. It provides mechanism of how to transfer bulk data from RDBMS to HDFS and vice versa efficiently.
h. Programming Hive by Dean Wampler, Edward Capriolo, and Jason Rutherglen
This comprehensive guide introduces you to Apache Hive – Hadoop data warehouse infrastructure. It will help you in learning Hive’s SQL dialect – Hive QL for summarizing, querying and analysing large datasets stored in HDFS.
i. HBase – The Definitive Guide by Lars George
It covers all aspects of Apache HBase in a very detailed manner. It covers HBase concepts from basics to advanced level and explains how HBase can help you in providing scalable storage solution for accommodating virtually endless data.
j. Using Flume by Hari Shreedharan
Through this guide, you will learn Apache Flume’s features for collecting , aggregating and writing large datasets to HDFS, HBase, etc. It shows how to configure, deploy and monitor Flume cluster and how to write Flume plugins for use cases. It will help you in exploring APIs for sending data to Flume agents from your own applications.