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Hadoop – The Definitive Guide 2e ペーパーバック – 2010/10/22
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Discover how Apache Hadoop can unleash the power of your data. This comprehensive resource shows you how to build and maintain reliable, scalable, distributed systems with the Hadoop framework -- an open source implementation of MapReduce, the algorithm on which Google built its empire. Programmers will find details for analyzing datasets of any size, and administrators will learn how to set up and run Hadoop clusters.
This revised edition covers recent changes to Hadoop, including new features such as Hive, Sqoop, and Avro. It also provides illuminating case studies that illustrate how Hadoop is used to solve specific problems. Looking to get the most out of your data? This is your book.
- Use the Hadoop Distributed File System (HDFS) for storing large datasets, then run distributed computations over those datasets with MapReduce
- Become familiar with Hadoops data and I/O building blocks for compression, data integrity, serialization, and persistence
- Discover common pitfalls and advanced features for writing real-world MapReduce programs
- Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud
- Use Pig, a high-level query language for large-scale data processing
- Analyze datasets with Hive, Hadoops data warehousing system
- Take advantage of HBase, Hadoops database for structured and semi-structured data
- Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems
"Now you have the opportunity to learn about Hadoop from a master -- not only of the technology, but also of common sense and plain talk."
--Doug Cutting, Cloudera
- 本の長さ624ページ
- 言語英語
- 出版社O′Reilly
- 発売日2010/10/22
- 寸法18 x 3.29 x 23.4 cm
- ISBN-101449389732
- ISBN-13978-1449389734
商品の説明
著者について
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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All in all, a well written and very informative book. I found Data-Intensive Text Processing with MapReduce an excellent companion to this book for more detail on MapReduce.

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.

