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MapReduce Design Patterns : Building Effective Algorithms and Analytics for Hadoop and Other Systems by Adam Shook and Donald Miner (2013, Trade Paperback)

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MapReduce Design Patterns, Paperback by Miner, Donald; Shook, Adam, ISBN 1449327176, ISBN-13 9781449327170, Brand New, Free shipping in the US Brings together a collection of valuable MapReduce patterns explained in context, with pitfalls and caveats clearly identified to help avoid common design mistakes when modeling big data architecture.

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Design patterns for the MapReduce framework, until now, 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 - so you can avoid some of the 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. Hadoop MapReduce code is provided to help you learn how to apply the design patterns by example. Topics include: Basic patterns, including map-only filter, group by, aggregation, distinct, and limit Joins: traditional reduce-side join, reduce-side join with Bloom filter, replicated join with distributed cache, merge join, Cartesian products, and intersections Binning, sharding for other systems, sorting, sampling, unions, and other patterns for organizing data Job optimization patterns, including multi-job map-only job folding, and overloading the key grouping to perform two jobs at once

Product Identifiers

Publisher
O'reilly Media, Incorporated
ISBN-10
1449327176
ISBN-13
9781449327170
eBay Product ID (ePID)
117235300

Product Key Features

Author
Adam Shook, Donald Miner
Publication Name
Mapreduce Design Patterns : Building Effective Algorithms and Analytics for Hadoop and Other Systems
Format
Trade Paperback
Language
English
Publication Year
2013
Type
Textbook
Number of Pages
250 Pages

Dimensions

Item Length
9.2in
Item Height
0.7in
Item Width
6.9in
Item Weight
15.3 Oz

Additional Product Features

Lc Classification Number
Qa76.9.D3
Table of Content
Dedication;Preface; Intended Audience; Pattern Format; The Examples in This Book; Conventions Used in This Book; Using Code Examples; Safari® Books Online; How to Contact Us; Acknowledgments;Chapter 1: Design Patterns and MapReduce; 1.1 Design Patterns; 1.2 MapReduce History; 1.3 MapReduce and Hadoop Refresher; 1.4 Hadoop Example: Word Count; 1.5 Pig and Hive;Chapter 2: Summarization Patterns; 2.1 Numerical Summarizations; 2.2 Inverted Index Summarizations; 2.3 Counting with Counters;Chapter 3: Filtering Patterns; 3.1 Filtering; 3.2 Bloom Filtering; 3.3 Top Ten; 3.4 Distinct;Chapter 4: Data Organization Patterns; 4.1 Structured to Hierarchical; 4.2 Partitioning; 4.3 Binning; 4.4 Total Order Sorting; 4.5 Shuffling;Chapter 5: Join Patterns; 5.1 A Refresher on Joins; 5.2 Reduce Side Join; 5.3 Replicated Join; 5.4 Composite Join; 5.5 Cartesian Product;Chapter 6: Metapatterns; 6.1 Job Chaining; 6.2 Chain Folding; 6.3 Job Merging;Chapter 7: Input and Output Patterns; 7.1 Customizing Input and Output in Hadoop; 7.2 Generating Data; 7.3 External Source Output; 7.4 External Source Input; 7.5 Partition Pruning;Chapter 8: Final Thoughts and the Future of Design Patterns; 8.1 Trends in the Nature of Data; 8.2 The Effects of YARN; 8.3 Patterns as a Library or Component; 8.4 How You Can Help;Bloom Filters; Overview; Use Cases; Downsides; Tweaking Your Bloom Filter;Colophon;
Copyright Date
2012
Target Audience
Scholarly & Professional
Topic
Data Modeling & Design, Software Development & Engineering / Tools, Programming / Parallel, Databases / General
Dewey Decimal
005.74
Dewey Edition
23
Illustrated
Yes
Genre
Computers

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MapReduce Design Patterns : Building Effective Algorithms and Analytics for Hadoop and Other Systems by Adam Shook and Donald Miner (2013, Trade Paperback)

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