Hadoop: The Definitive Guide

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Overview

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, ...

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Hadoop: The Definitive Guide

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Overview

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 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
  • Analyze datasets with Hive, Hadoop’s data warehousing system
  • Take advantage of HBase, Hadoop’s 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

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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: 83,097
  • 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

Foreword

Preface

Chapter 1: Meet Hadoop

Chapter 2: MapReduce

Chapter 3: The Hadoop Distributed Filesystem

Chapter 4: Hadoop I/O

Chapter 5: Developing a MapReduce Application

Chapter 6: How MapReduce Works

Chapter 7: MapReduce Types and Formats

Chapter 8: MapReduce Features

Chapter 9: Setting Up a Hadoop Cluster

Chapter 10: Administering Hadoop

Chapter 11: Pig

Chapter 12: Hive

Chapter 13: HBase

Chapter 14: ZooKeeper

Chapter 15: Sqoop

Chapter 16: Case Studies

Installing Apache Hadoop

Cloudera’s Distribution for Hadoop

Preparing the NCDC Weather Data

Colophon

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Customer Reviews

Average Rating 4.5
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Sort by: Showing all of 4 Customer Reviews
  • Posted January 8, 2014

    the hadoop book

    opening with an architecture overview and then goes through the components. Hands-on with dataset and step by step from hadoop installation to actually write code and process data to generate output. If you have time only for one book, then this one is.

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    Posted May 21, 2011

    No text was provided for this review.

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    Posted March 7, 2011

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    Posted May 15, 2011

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