Hadoop: The Definitive Guide: Storage and Analysis at Internet Scale

by Tom White

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

Product Details

ISBN-13:	9781491901632
Publisher:	O'Reilly Media, Incorporated
Publication date:	04/11/2015
Edition description:	4
Pages:	754
Sales rank:	1,129,021
Product dimensions:	7.00(w) x 9.10(h) x 1.60(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 Universityof Cambridge and a Master's in Philosophy of Science from the Universityof 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