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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Detalles Bibliográficos
Autor principal: Miner, Donald (-)
Otros Autores: Shook, Adam, Oram, Andrew, Hendrickson, Mike, Demarest, Rebecca
Formato: Libro electrónico
Idioma:Inglés
Publicado: Sebastopol, California : O'Reilly December 2012
Edición:First edition
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628569006719
Descripción
Sumario: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
Notas:Includes index.
"Building effective algorithms and analytics for Hadoop and other systems"--Cover.
Descripción Física:1 online resource (251 p.)
ISBN:9781449341985
9781449341954
9781449341961
9781306811125
9781449341992