Hadoop: The Definitive Guide

Overview

Get ready to unlock the power of your data. With the fourth edition of 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.

Using Hadoop 2 exclusively, author Tom White presents new chapters on YARN and several Hadoop-related projects such as Parquet, Flume, Crunch, ...

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Hadoop: The Definitive Guide

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Overview

Get ready to unlock the power of your data. With the fourth edition of 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.

Using Hadoop 2 exclusively, author Tom White presents new chapters on YARN and several Hadoop-related projects such as Parquet, Flume, Crunch, and Spark. You’ll learn about recent changes to Hadoop, and explore new case studies on Hadoop’s role in healthcare systems and genomics data processing.

  • Learn fundamental components such as MapReduce, HDFS, and YARN
  • Explore MapReduce in depth, including steps for developing applications with it
  • Set up and maintain a Hadoop cluster running HDFS and MapReduce on YARN
  • Learn two data formats: Avro for data serialization and Parquet for nested data
  • Use data ingestion tools such as Flume (for streaming data) and Sqoop (for bulk data transfer)
  • Understand how high-level data processing tools like Pig, Hive, Crunch, and Spark work with Hadoop
  • Learn the HBase distributed database and the ZooKeeper distributed configuration service
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Product Details

  • ISBN-13: 9781491901632
  • Publisher: O'Reilly Media, Incorporated
  • Publication date: 4/10/2015
  • Edition description: 4
  • Edition number: 4
  • Pages: 768
  • Sales rank: 166,151

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 Including Apache Hadoop

Preparing the NCDC Weather Data

Colophon

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