Categories Categories

Hadoop: The Definitive Guide, 4th Edition

MRP: Rs.950.00
Price in points: 950 points
9789352130672
In stock
+

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

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

1. Hadoop Fundamentals

Chapter 1 Meet Hadoop

Chapter 2 MapReduce

Chapter 3 The Hadoop Distributed Filesystem

Chapter 4 YARN

Chapter 5 Hadoop I/O

2. MapReduce

Chapter 1 Developing a MapReduce Application

Chapter 2 How MapReduce Works

Chapter 3 MapReduce Types and Formats

Chapter 4 MapReduce Features

3. Hadoop Operations

Chapter 1 Setting Up a Hadoop Cluster

Chapter 2 Administering Hadoop

4. Related Projects

Chapter 1 Avro

Chapter 2 Parquet

Chapter 3 Flume

Chapter 4 Sqoop

Chapter 5 Pig

Chapter 6 Hive

Chapter 7 Crunch

Chapter 8 Spark

Chapter 9 HBase

Chapter 10 ZooKeeper

5. Case Studies

Chapter 1 Composable Data at Cerner

Chapter 2 Biological Data Science: Saving Lives with Software

Chapter 3 Cascading


Books

Author:
White
Condition Type:
New
Country Origin:
India
Edition:
Fourth
Gift Wrap:
No
Publication Date:
2015
Publisher:
Shroff/O'Reilly