Hadoop Beginner’s Guide

Learn how to crunch big data to extract meaning from the data avalanche.

Overview

• Learn tools and techniques that let you approach big data with relish and not fear.
• Shows how to build a complete infrastructure to handle your needs as your data grows.
• Hands-on examples in each chapter give the big picture while also giving direct experience.

In Detail

Data is arriving faster than you can process it and the overall volumes keep growing at a rate that keeps you awake at night. Hadoop can help you tame the data beast. Effective use of Hadoop however requires a mixture of programming, design, and system administration skills.

“Hadoop Beginner’s Guide” removes the mystery from Hadoop, presenting Hadoop and related technologies with a focus on building working systems and getting the job done, using cloud services to do so when it makes sense. From basic concepts and initial setup through developing applications and keeping the system running as the data grows, the book gives the understanding needed to effectively use Hadoop to solve real world problems.

Starting with the basics of installing and configuring Hadoop, the book explains how to develop applications, maintain the system, and how to use additional products to integrate with other systems.

While learning different ways to develop applications to run on Hadoop the book also covers tools such as Hive, Sqoop, and Flume that show how Hadoop can be integrated with relational databases and log collection .

In addition to examples on Hadoop clusters on Ubuntu uses of cloud services such as Amazon, EC2 and Elastic MapReduce are covered.

What you will learn from this book

• The trends that led to Hadoop and cloud services, giving the background to know when to use the technology.
• Best practices for setup and configuration of Hadoop clusters, tailoring the system to the problem at hand
• Developing applications to run on Hadoop with examples in Java and Ruby
• How Amazon Web Services can be used to deliver a hosted Hadoop solution and how this differs from directly-managed environments
• Integration with relational databases, using Hive for SQL queries and Sqoop for data transfer
• How Flume can collect data from multiple sources and deliver it to Hadoop for processing
• What other projects and tools make up the broader Hadoop ecosystem and where to go next

Approach

As a Packt Beginner’s Guide, the book is packed with clear step-by-step instructions for performing the most useful tasks, getting you up and running quickly, and learning by doing.

Who this book is written for

This book assumes no existing experience with Hadoop or cloud services. It assumes you have familiarity with a programming language such as Java or Ruby but gives you the needed background on the other topics.

Table of Contents

Chapter 1: What It’s All About
Chapter 2: Getting Hadoop Up and Running
Chapter 3: Understanding MapReduce
Chapter 4: Developing MapReduce Programs
Chapter 5: Advanced MapReduce Techniques
Chapter 6: When Things Break
Chapter 7: Keeping Things Running
Chapter 8: A Relational View on Data with Hive
Chapter 9: Working with Relational Databases
Chapter 10: Data Collection with Flume
Chapter 11: Where to Go Next
Appendix: Pop Quiz Answers