MapReduce design patterns

Until now, design patterns for the MapReduce framework have been scattered among various research papers, blogs, and books. This handy guide brings together a unique collection of valuable MapReduce patterns that will save you time and effort regardless of the domain, language, or development framew...

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Bibliographic Details
Main Author: Miner, Donald (-)
Other Authors: Shook, Adam, Oram, Andrew, Hendrickson, Mike, Demarest, Rebecca
Format: eBook
Language:Inglés
Published: Sebastopol, California : O'Reilly December 2012
Edition:First edition
Subjects:
See on Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628569006719
Description
Summary:Until now, design patterns for the MapReduce framework have been scattered among various research papers, blogs, and books. This handy guide brings together a unique collection of valuable MapReduce patterns that will save you time and effort regardless of the domain, language, or development framework you're using. Each pattern is explained in context, with pitfalls and caveats clearly identified to help you avoid common design mistakes when modeling your big data architecture. This book also provides a complete overview of MapReduce that explains its origins and implementations, and why de
Item Description:Includes index.
"Building effective algorithms and analytics for Hadoop and other systems"--Cover.
Physical Description:1 online resource (251 p.)
ISBN:9781449341985
9781449341954
9781449341961
9781306811125
9781449341992