Fr. 55.50

Big Data for Chimps

English · Paperback / Softback

Shipping usually within 3 to 5 weeks

Description

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"Finding patterns in massive event streams can be difficult, but learning how to find them doesn't have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. You'll gain a practical, actionable view of big data by working with real data and real problems. Perfect for beginners, this book's approach will also appeal to experienced practitioners who want to brush up on their skills. Part I explains how Hadoop and MapReduce work, while Part II covers many analytic patterns you can use to process any data. As you work through several exercises, you'll also learn how to use Apache Pig to process data"--

About the author










Flip is the founder and CTO at Infochimps.com, a big data platform that makes acquiring, storing and analyzing massive data streams transformatively easier. He enjoys Bowling, Scrabble, working on old cars or new wood, and rooting for the Red Sox.
Russell Jurney cut his data teeth in casino gaming, building web apps to analyze the performance of slot machines in the US and Mexico. After dabbling in entrepreneurship, interactive media and journalism, he moved to silicon valley to build analytics applications at scale at Ning and LinkedIn. He lives on the ocean in Pacifica, California with his wife Kate and two fuzzy dogs.


Summary

Finding patterns in massive event streams can be difficult, but learning how to find them doesn't have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop.

Product details

Authors Russell Jurney, Philip Kromer, Kromer Philip, Kromer Philip (Flip), Philip Kromer
Publisher O'Reilly
 
Languages English
Product format Paperback / Softback
Released 17.11.2015
 
EAN 9781491923948
ISBN 978-1-4919-2394-8
Dimensions 178 mm x 234 mm x 10 mm
Weight 388 g
Subjects Natural sciences, medicine, IT, technology > IT, data processing > IT

Data Mining, COMPUTERS / Data Science / Data Analytics

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