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Hadoop: The Definitive Guide 2nd Edition

4.1 out of 5 stars 20 customer reviews
ISBN-13: 978-1449389734
ISBN-10: 1449389732
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Editorial Reviews

About the Author

Tom White has been an Apache Hadoop committer since February 2007, and is a member of the Apache Software Foundation. He works for Cloudera, a company set up to offer Hadoop support and training. Previously he was as an independent Hadoop consultant, working with companies to set up, use, and extend Hadoop. He has written numerous articles for O'Reilly, java.net and IBM's developerWorks, and has spoken at several conferences, including at ApacheCon 2008 on Hadoop. Tom has a Bachelor's degree in Mathematics from the University of Cambridge and a Master's in Philosophy of Science from the University of Leeds, UK.

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Product Details

  • Paperback: 628 pages
  • Publisher: Yahoo Press; 2 edition (October 15, 2010)
  • Language: English
  • ISBN-10: 1449389732
  • ISBN-13: 978-1449389734
  • Product Dimensions: 7 x 1.5 x 9.2 inches
  • Shipping Weight: 2.2 pounds
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (20 customer reviews)
  • Amazon Best Sellers Rank: #812,695 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

Format: Paperback
The second edition of the already fantastic Hadoop: The Definitive Guide adds the last few missing bits to the best Hadoop reference out there.

For those not familiar with the first edition, Hadoop: The Definitive Guide is exactly what it claims to be. If you're not already familiar with Hadoop, the first and second chapters (Meet Hadoop and MapReduce, respectively) take you through the basics in both concept as well as code. For those used to writing data processing applications, the rationale behind Hadoop and why it's useful are immediately apparent. If you've already been exposed to Hadoop, these chapters may be redundant but they're worth reading anyway the first time through.

The chapter on HDFS does a great job at explaining the underbelly of Hadoop's distributed file system including the Java APIs. The section on Hadoop IO is probably introduced a bit too early - Hadoop newbies probably don't care about compression and serialization prior to reading about map reduce - but excellent none the less in its detail. That said, you'll *really* want to go back and read it to understand the details of how compression codecs work after you learn more about map reduce.The "Writing a Map Reduce Application" chapter is probably the one existing users of Hadoop will skip. First timers will definitely get a lot out of a step by step walk through of a Java MR job from beginning to end.

The chapters on how map reduce works, types and formats (including input / output format details), and the advanced features (counters, sorting, the distributed cache, join libraries) are the ones you'll reread and reference constantly.
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Format: Paperback
Hadoop's MapReduce and HBase went through a major API change right around the time this book was finishing up. Consequently, if you try to use the examples in the book as a guide while developing against either the Apache Hadoop latest release or against Cloudera's CDH3, you'll find a mountain of frustration in the form of deprecated or entirely deleted classes.
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Format: Paperback Verified Purchase
This book provides an excellent in-depth overview of all aspects of Hadoop with how-to examples that are easy to follow. It is well written, thorough and exactly what I needed to architect and build a Hadoop-based solution. Related technologies such as Hive, HBase, Sqoop, Pig and Zookeeper are also covered in decent depth.

Other reviewers gave poor reviews due to the APIs being not up to date, which I think is unfair. Those new APIs are still only available in early unstable Hadoop versions, so current developers are best served to use the earlier APIs. The book gives samples with new APIs and shows very clearly the API changes which are minor. The concepts are identical, but a few classes have been combined into a more cohesive "Context" class in the new APIs.

So, for example, to write a data record you call "context.collect(...);" rather than "output.collect(...);" with identical parameters. The structure of applications and the concepts are not changed. The changes to the syntax of Java calls is trivial and covered in the book very clearly. What is the big deal? Understanding the concepts is the most important thing and this book provides this very nicely.

I would recommend this book to anyone who is new to Hadoop and needs to learn it in depth.
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The APIs in this book were all outdated by the time the book hit the shelf. The authors did recognize this and mention it in the book, however you don't need 400 pages to understand the map-reduce concepts.
I think it's a bad idea trying to publish a book on a rapidly changing community project like Hadoop. I found the Cloudera (free) training materials much more helpful.
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Good to have a book about this system; it is much better to have at least some book than no book at all. Also good is the practical approach of the author, who guides you through all steps of configuring, testing and running tasks in Hadoop.

One major drawback is a somehow vague and unclear language of the book. When author tries to explain some complicated matter, his phrases are always impossible to understand without further research, or not at all. The author surely knows what he wants to say, but cannot express it in a clear and precise manner.
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By Al on January 6, 2013
Format: Paperback Verified Purchase
This is a good overview book of Hadoop, how it works, and the software in the Hadoop ecosystem. It's definitely a breadth book, not a depth book, so if you're looking to be an expert on specific subsections of Hadoop, you should buy books on those specific topics.

(Note: there is a newer edition of the book now, you may want to get that one instead of this one.)
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Format: Kindle Edition Verified Purchase
I had bought this book (Kindle edition), hoping it would have a good intro to programming for MapReduce. It is not. This book tries to be a lot of things: a Hadoop administration book, MapReduce programming book using the Java API, an HDFS reference book, Hadoop Streaming book and so on and so forth but succeeds on no front. The examples are trivial and it barely skims the Hadoop Java API.
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