9781449327170 - mapreduce design patterns: building effective algorithms and analytics for hadoop and other systems von miner, donald; shook, adam (12 Ergebnisse)
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MapReduce Design Patterns : Building Effective Algorithms and Analytics for Hadoop and Other Systems
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MapReduce Design Patterns : Building Effective Algorithms and Analytics for Hadoop and Other Systems
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Paperback. Zustand: Very Good. MapReduce Design Patterns: Building Effective Algorithms and Analytics for Hadoop and Other Systems This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. Thi…s book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping.
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Zustand: New. 2012. 1st Edition. Paperback. 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. Num Pages: 252 pages, Illustrations. BIC Classification: UM; UT. Category: (XV) Technical /…Manuals. Dimension: 179 x 234 x 13. Weight in Grams: 442. . . . . . Books ship from the US and Ireland.
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Paperback. Zustand: Brand New. 1st edition. 232 pages. 9.25x7.00x0.75 inches. In Stock.
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Zustand: New. 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.Until now, design patterns for the MapReduce framework have .
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Taschenbuch. Zustand: Neu. Neuware - 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 data Filtering patterns: view data subsets such as records generated from one user Data organization patterns: reorganize data to work with other systems, or to make MapReduce analysis easier Join patterns: analyze different datasets together to discover interesting relationships Metapatterns: piece together several patterns to solve multi-stage problems, or to perform several analytics in the same job Input 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.
