Discover how Apache Hadoop can unleash the power of your data. This comprehensive resource shows you how to build and maintain reliable, scalable, distributed systems with the Hadoop framework -- an open source implementation of MapReduce, the algorithm on which Google built its empire. Programmers will find details for analyzing datasets of any size, and administrators will learn how to set up and run Hadoop clusters.

This revised edition covers recent changes to Hadoop, including new features such as Hive, Sqoop, and Avro. It also provides illuminating case studies that illustrate how Hadoop is used to solve specific problems. Looking to get the most out of your data? This is your book.

Use the Hadoop Distributed File System (HDFS) for storing large datasets, then run distributed computations over those datasets with MapReduce
Become familiar with Hadoop’s data and I/O building blocks for compression, data integrity, serialization, 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
Take advantage of HBase, Hadoop’s database for structured and semi-structured data
Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems