|Hadoop in Practice
October, 2012 | 536 pages
|$49.99||pBook + eBook (includes PDF, ePub, and Kindle)|
|$39.99||eBook Only (includes PDF, ePub, and Kindle)|
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Hadoop in Practice collects 85 Hadoop examples and presents them in a problem/solution format. Each technique addresses a specific task you'll face, like querying big data using Pig or writing a log file loader. You'll explore each problem step by step, learning both how to build and deploy that specific solution along with the thinking that went into its design. As you work through the tasks, you'll find yourself growing more comfortable with Hadoop and at home in the world of big data.
About the Technology
Hadoop is an open source MapReduce platform designed to query and analyze data distributed across large clusters. Especially effective for big data systems, Hadoop powers mission-critical software at Apple, eBay, LinkedIn, Yahoo, and Facebook. It offers developers handy ways to store, manage, and analyze data.
About the Book
Hadoop in Practice collects 85 battle-tested examples and presents them in a problem/solution format. It balances conceptual foundations with practical recipes for key problem areas like data ingress and egress, serialization, and LZO compression. You'll explore each technique step by step, learning how to build a specific solution along with the thinking that went into it. As a bonus, the book's examples create a well-structured and understandable codebase you can tweak to meet your own needs.
This book assumes the reader knows the basics of Hadoop.
- Conceptual overview of Hadoop and MapReduce
- 85 practical, tested techniques
- Real problems, real solutions
- How to integrate MapReduce and R
About the Author
Alex Holmes is a senior software engineer with extensive expertise in solving big data problems using Hadoop. He has presented at JavaOne and Jazoon and is a technical lead at VeriSign.