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MapReduce Design Patterns: Building Effective Algorithms and Analytics for Hadoop and Other Systems
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. Updated to include new versions of Hadoop, this second edition features several new patterns, such as transformation, join with a secondary sort, external join, and MapReduce over HBase. 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.
275 pages, Paperback
First published March 25, 2016
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