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Data-Intensive Text Processing with MapReduce (Synthesis Lectures on Human Language Technologies) Paperback – April 30, 2010


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Data-Intensive Text Processing with MapReduce (Synthesis Lectures on Human Language Technologies) + Hadoop: The Definitive Guide + MapReduce Design Patterns: Building Effective Algorithms and Analytics for Hadoop and Other Systems
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Product Details

  • Series: Synthesis Lectures on Human Language Technologies
  • Paperback: 178 pages
  • Publisher: Morgan and Claypool Publishers (April 30, 2010)
  • Language: English
  • ISBN-10: 1608453421
  • ISBN-13: 978-1608453429
  • Product Dimensions: 7.5 x 0.4 x 9.2 inches
  • Shipping Weight: 11.4 ounces (View shipping rates and policies)
  • Average Customer Review: 4.7 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Best Sellers Rank: #838,983 in Books (See Top 100 in Books)

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3 of 3 people found the following review helpful By Photo/Video Gearhead on December 29, 2011
Format: Paperback Verified Purchase
This book provides a valuable discussion of the strategies involved in developing MapReduce algorithms. Although I have done considerable parallel programming using MPI and OpenMP, I find MapReduce algorithms to be somewhat non-intuitive, and this book has helped me to overcome that barrier.
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2 of 2 people found the following review helpful By Dimitri K on February 7, 2012
Format: Paperback Verified Purchase
The book is educating and, hopefully, will be helpful for writing map-reduce programs. It concentrates not on API, but on algorithms, which is rare and should be appreciated. Text-processing is a good example of data-intensive processing, but the book may be useful in many other fields.
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0 of 2 people found the following review helpful By Kenneth Cognoscente on February 11, 2013
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I bought this book for a project at work, to prototype a log analysis system using Hadoop. I haven't bought very many technical books in the last few years, but the quality of most online documentation for Hadoop is poor and books seemed like a better option. This book is a good intro to the Map Reduce algorithm, but once I got my head around that I didn't use it very much (probably because my problem space was nothing like the sort of text processing that the book focuses on).
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