Hadoop in Practice
Includes 104 Techniques
2nd Edition
Published on 5. February 2015
Book
Paperback/Softback
511 pages
978-1-61729-222-4 (ISBN)
Description
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For developers working with big data, it's not enough to have a theoretical understanding of Hadoop. They need to solve real challenges like analyzing real-time streams, moving data securely between storage systems, and managing large-scale clusters. The Hadoop ecosystem is constantly growing, and it's important they keep up with the new technologies and practices to stay productive and future-proof data systems.
Hadoop in Practice, Second Edition provides over 100 tested, instantly-useful techniques that will help conquer big data, using Hadoop. This revised new edition covers changes and new features in the Hadoop core architecture, including MapReduce 2. Brand new chapters cover YARN, real-time use cases, and integrating Kafka, Storm, and Spark with Hadoop. There's also a new and updated techniques for Flume, Sqoop, and Mahout, all of which have seen major new versions recently. In short, this is the most practical, up-to-date coverage of Hadoop available anywhere.
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RETAIL SELLING POINTS
Practical up-to-date coverage
Over 100 practical, battle-tested Hadoop techniques
Major updates to key technologies
AUDIENCE
Readers should be familiar with Hadoop and have experience programming in Java or another OOP language.
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 organizations efficient ways to store, manage, and analyze data.
For developers working with big data, it's not enough to have a theoretical understanding of Hadoop. They need to solve real challenges like analyzing real-time streams, moving data securely between storage systems, and managing large-scale clusters. The Hadoop ecosystem is constantly growing, and it's important they keep up with the new technologies and practices to stay productive and future-proof data systems.
Hadoop in Practice, Second Edition provides over 100 tested, instantly-useful techniques that will help conquer big data, using Hadoop. This revised new edition covers changes and new features in the Hadoop core architecture, including MapReduce 2. Brand new chapters cover YARN, real-time use cases, and integrating Kafka, Storm, and Spark with Hadoop. There's also a new and updated techniques for Flume, Sqoop, and Mahout, all of which have seen major new versions recently. In short, this is the most practical, up-to-date coverage of Hadoop available anywhere.
?
RETAIL SELLING POINTS
Practical up-to-date coverage
Over 100 practical, battle-tested Hadoop techniques
Major updates to key technologies
AUDIENCE
Readers should be familiar with Hadoop and have experience programming in Java or another OOP language.
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 organizations efficient ways to store, manage, and analyze data.
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Person
Alex Holmes is a software engineer, author, speaker and blogger specializing in large-scale Hadoop projects and solving tough Big Data problems. Alex blogs at grepalex.com.