MapReduce Design Patterns: Building Effective Algorithms and Analytics for Hadoop and Other Systems pdf epub fb2

MapReduce Design Patterns: Building Effective Algorithms and Analytics for Hadoop and Other Systems by Donald Miner, Adam Shook pdf epub fb2

MapReduce Design Patterns: Building Effective Algorithms and Analytics for Hadoop and Other Systems Author: Donald Miner, Adam Shook
Title: MapReduce Design Patterns: Building Effective Algorithms and Analytics for Hadoop and Other Systems
ISBN: 1449327176
ISBN13: 978-1449327170
Other Formats: azw lrf azw mobi
Pages: 250 pages
Publisher: O'Reilly Media; 1 edition (December 17, 2012)
Language: English
Category: Computers & Technology
Size PDF version: 1648 kb
Size EPUB version: 1286 kb
Subcategory: Programming




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 design patterns are so important. All code examples are written for Hadoop.

Summarization patterns: get a top-level view by summarizing and grouping dataFiltering patterns: view data subsets such as records generated from one userData organization patterns: reorganize data to work with other systems, or to make MapReduce analysis easierJoin patterns: analyze different datasets together to discover interesting relationshipsMetapatterns: piece together several patterns to solve multi-stage problems, or to perform several analytics in the same jobInput and output patterns: customize the way you use Hadoop to load or store data

"A clear exposition of MapReduce programs for common data processing patterns—this book is indespensible for anyone using Hadoop."--Tom White, author of Hadoop: The Definitive Guide