Hadoop: The Definitive Guide

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Overview

Hadoop: The Definitive Guide helps you harness the power of your data. Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its empire. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoop clusters.

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Hadoop: The Definitive Guide

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More About This Book

Overview

Hadoop: The Definitive Guide helps you harness the power of your data. Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its empire. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoop clusters.

Complete with case studies that illustrate how Hadoop solves specific problems, this book helps you:

  • Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduce
  • Become familiar with Hadoop's 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
  • Take advantage of HBase, Hadoop's database for structured and semi-structured data
  • Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems

If you have lots of data — whether it's gigabytes or petabytes — Hadoop is the perfect solution. Hadoop: The Definitive Guide is the most thorough book available on the subject.

"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, Hadoop Founder, Yahoo!

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Product Details

  • ISBN-13: 9781449311520
  • Publisher: O'Reilly Media, Incorporated
  • Publication date: 5/29/2012
  • Edition description: Third Edition
  • Edition number: 3
  • Pages: 688
  • Sales rank: 80,454
  • Product dimensions: 7.00 (w) x 9.20 (h) x 1.40 (d)

Meet 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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Table of Contents

ForewordPrefaceChapter 1: Meet HadoopChapter 2: MapReduceChapter 3: The Hadoop Distributed FilesystemChapter 4: Hadoop I/OChapter 5: Developing a MapReduce ApplicationChapter 6: How MapReduce WorksChapter 7: MapReduce Types and FormatsChapter 8: MapReduce FeaturesChapter 9: Setting Up a Hadoop ClusterChapter 10: Administering HadoopChapter 11: PigChapter 12: HBaseChapter 13: ZooKeeperChapter 14: Case StudiesInstalling Apache HadoopCloudera’s Distribution for HadoopPreparing the NCDC Weather DataColophon

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