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

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Название: MapReduce Design Patterns: Building Effective Algorithms and Analytics for Hadoop and Other Systems

автор: Donald Miner, Adam Shook

Издательство: O'Reilly Media

Год выпуска: 2012

ISBN: 978-1449327170

Формат: PDF, EPUB

Размер: 14.48 MB

Количество страниц: 230

Язык: Английский

Описание: 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.