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Hadoop: The Definitive Guide (Englisch) Taschenbuch – 3. November 2010


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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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25 von 27 Kunden fanden die folgende Rezension hilfreich
The canonical reference of all things Hadoop 14. Juni 2011
Von Eric Sammer - Veröffentlicht auf Amazon.com
Format: Taschenbuch
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. The explanation, for instance, on how input splits are calculated demystifies the border between HDFS and the map reduce layer (and finally answers the question of "how does Hadoop know not to split in the middle of a record?"). Buy this book for these chapters, if not for the others.

The chapters on HBase, Pig, ZooKeeper, and Sqoop are excellent and, in some cases, the best reference on the topic to date.

There are enough corrections, updates, and new chapters that it's worth buying the second edition if you already have the first. For anyone new to Hadoop this is a must have. If you already use Hadoop the later chapters are what you're looking for; a deep explanation of not just "how," but "why."

Some reviewers have noted the discussion of deprecated APIs. This really isn't a flaw of the book, but of premature deprecation within Hadoop itself. The newer APIs didn't have all the features of the old and anyone writing production map reduce jobs would wind up needing a lot of those features. I think the author does a great job with a tough situation while still alerting the reader that newer APIs are on the horizon. Besides, the differences are so few that it's almost not worth mentioning. While APIs may change, the core design, execution model, and architecture of Hadoop haven't changed and this is the best book on the subject.
27 von 31 Kunden fanden die folgende Rezension hilfreich
Sadly, already outdated 23. Mai 2011
Von L. Wickland - Veröffentlicht auf Amazon.com
Format: Taschenbuch
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.
11 von 12 Kunden fanden die folgende Rezension hilfreich
Excellant Hadoop Overview 21. Juli 2011
Von David Mark Schramm - Veröffentlicht auf Amazon.com
Format: Taschenbuch Verifizierter Kauf
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.
27 von 37 Kunden fanden die folgende Rezension hilfreich
Outdated by the Time it hit the shelf 18. November 2010
Von Peter Harrington - Veröffentlicht auf Amazon.com
Format: Taschenbuch Verifizierter Kauf
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.
1 von 1 Kunden fanden die folgende Rezension hilfreich
In-depth with lots of examples 8. Juni 2012
Von JUAN JOSE DE LEON - Veröffentlicht auf Amazon.com
Format: Taschenbuch
The book has lots examples and footnote resources that enriched the content. Some people recommend watching Cloudera training videos first and then reading this book if you are a beginner, and i agree.
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