Hadoop: The Definitive Guide

Hadoop: The Definitive Guide

by Tom White

Paperback(Third Edition)

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Ready to unlock the power of your data? With this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters.

You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN).

  • Store large datasets with the Hadoop Distributed File System (HDFS)
  • Run distributed computations with MapReduce
  • Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), 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
  • Load data from relational databases into HDFS, using Sqoop
  • Perform large-scale data processing with the Pig query language
  • Analyze datasets with Hive, Hadoop’s data warehousing system
  • Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems

Product Details

ISBN-13: 9781449311520
Publisher: O'Reilly Media, Incorporated
Publication date: 05/29/2012
Edition description: Third Edition
Pages: 688
Product dimensions: 7.00(w) x 9.20(h) x 1.40(d)

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.

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 Including Apache Hadoop
  • Preparing the NCDC Weather Data
  • Colophon

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