Professional Hadoop Solutions

The go-to guidebook for deploying Big Data solutions with Hadoop

Today’s enterprise architects need to understand how the Hadoop frameworks and APIs fit together, and how they can be integrated to deliver real-world solutions. This book is a practical, detailed guide to building and implementing those solutions, with code-level instruction in the popular Wrox tradition. It covers storing data with HDFS and Hbase, processing data with MapReduce, and automating data processing with Oozie. Hadoop security, running Hadoop with Amazon Web Services, best practices, and automating Hadoop processes in real time are also covered in depth.

With in-depth code examples in Java and XML and the latest on recent additions to the Hadoop ecosystem, this complete resource also covers the use of APIs, exposing their inner workings and allowing architects and developers to better leverage and customize them.

• The ultimate guide for developers, designers, and architects who need to build and deploy Hadoop applications
• Covers storing and processing data with various technologies, automating data processing, Hadoop security, and delivering real-time solutions
• Includes detailed, real-world examples and code-level guidelines
• Explains when, why, and how to use these tools effectively
• Written by a team of Hadoop experts in the programmer-to-programmer Wrox style

Professional Hadoop Solutions is the reference enterprise architects and developers need to maximize the power of Hadoop.

Table of Contents

Chapter 1. Big Data and the Hadoop Ecosystem
Chapter 2. Storing Data in Hadoop
Chapter 3. Processing Your Data with MapReduce
Chapter 4. Customizing MapReduce Execution
Chapter 5. Building Reliable MapReduce Apps
Chapter 6. Automating Data Processing with Oozie
Chapter 7. Using Oozie
Chapter 8. Advanced Oozie Features
Chapter 9. Real-Time Hadoop
Chapter 10. Hadoop Security
Chapter 11. Running Hadoop Applications on AWS
Chapter 12. Building Enterprise Security Solutions for Hadoop Implementations
Chapter 13. Hadoop’s Future