Hadoop: The Definitive Guide, 3rd Edition

ISBN: 1449311520

Category: Uncategorized

Posted on 2012-02-23. By anonymous.


Hadoop: The Definitive Guide, 3rd Edition
Hadoop: The Definitive Guide, 3rd Edition
Publisher: ORM | 2012 | 630 pages | PDF + EPUB | ISBN: 1449311520 | 5.7 + 8.5 Mb

With this digital Early Release edition of Hadoop: The Definitive Guide, you get the entire book bundle in its earliest form – the author’s raw and unedited content – so you can take advantage of this content long before the book’s official release. You’ll also receive updates when significant changes are made, as well as the final ebook version.p>Ready to unleash the power of your massive dataset? With the latest edition of this comprehensive resource, you’ll learn how to use Apache Hadoop to build and maintain reliable, scalable, distributed systems. It’s ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters.

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

Store large datasets with the Hadoop Distributed File System (HDFS), then 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
Use Pig, a high-level query language for large-scale data processing
Analyze datasets with Hive, Hadoop’s data warehousing system
Load data from relational databases into HDFS, using Sqoop
Take advantage of HBase, the database for structured and semi-structured data
Use ZooKeeper, the toolkit for building distributed systems

Table of Contents
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 11. Pig
Chapter 12. Hive
Chapter 13. HBase
Chapter 14. ZooKeeper
Chapter 15. Sqoop
Chapter 16. Case Studies
Appendix. Installing Apache Hadoop

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