Big Data: Principles and best practices of scalable realtime data systems
Nathan Marz,James Warren
ISBN 10: 1617290343 ISBN 13: 9781617290343
Published by Manning, 2015
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Synopsis:
Summary
Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them...
About the Author:
Nathan Marz is currently working on a new startup. Previously, he was the lead engineer at BackType before being acquired by Twitter in 2011. At Twitter, he started the streaming compute team which provides and develops shared infrastructure to support many critical realtime applications throughout the company. Nathan is the creator of Cascalog and Storm, open-source projects which are relied upon by over 50 companies around the world, including Yahoo!, Twitter, Groupon, The Weather Channel, Taobao, and many more companies.
James Warren is an analytics architect at Storm8 with a background in big data processing, machine learning and scientific computing.
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Bibliographic Details
Title: Big Data: Principles and best practices of ...
Publisher: Manning
Publication Date: 2015
Binding: paperback
Condition: Very Good
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ISBN 10: 1617290343
ISBN 13: 9781617290343
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