Hadoop in Action 1st Edition by Chuck Lam – Ebook PDF Instant Download/Delivery: 1935182196, 9781935182191
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Product details:
ISBN 10: 1935182196
ISBN 13: 9781935182191
Author: Chuck Lam
Hadoop in Action teaches readers how to use Hadoop and write MapReduce programs. The intended readers are programmers, architects, and project managers who have to process large amounts of data offline. Hadoop in Action will lead the reader from obtaining a copy of Hadoop to setting it up in a cluster and writing data analytic programs.
The book begins by making the basic idea of Hadoop and MapReduce easier to grasp by applying the default Hadoop installation to a few easy-to-follow tasks, such as analyzing changes in word frequency across a body of documents. The book continues through the basic concepts of MapReduce applications developed using Hadoop, including a close look at framework components, use of Hadoop for a variety of data analysis tasks, and numerous examples of Hadoop in action.
Hadoop in Action will explain how to use Hadoop and present design patterns and practices of programming MapReduce. MapReduce is a complex idea both conceptually and in its implementation, and Hadoop users are challenged to learn all the knobs and levers for running Hadoop. This book takes you beyond the mechanics of running Hadoop, teaching you to write meaningful programs in a MapReduce framework.
This book assumes the reader will have a basic familiarity with Java, as most code examples will be written in Java. Familiarity with basic statistical concepts (e.g. histogram, correlation) will help the reader appreciate the more advanced data processing examples.
Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.
Table of contents:
Part 1. Hadoop-A Distributed Programming Framework
Chapter 1. Introducing Hadoop
Chapter 2. Starting Hadoop
Chapter 3. Components of Hadoop
Part 2. Hadoop in Action
Chapter 4. Writing basic MapReduce programs
Chapter 5. Advanced MapReduce
Chapter 6. Programming Practices
Chapter 7. Cookbook
Chapter 8. Managing Hadoop
Part 3. Hadoop Gone Wild
Chapter 9. Running Hadoop in the cloud
Chapter 10. Programming with Pig
Chapter 11. Hive and the Hadoop herd
Chapter 12. Case studies
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