Data Mining, Data Processing, Cloud Computing, Parallel Programming, Java, Python, Database Storage & Design, Programming Languages 

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 MapReduceBecome familiar with Hadoop’s data and I/O building blocks for compression, data integrity, serialization, and persistenceDiscover common pitfalls and advanced features for writing real-world MapReduce programsDesign, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloudUse Pig, a high-level query language for large-scale data processingAnalyze datasets with Hive, Hadoop’s data warehousing systemTake advantage of HBase, Hadoop’s database for structured and semi-structured dataLearn ZooKeeper, a toolkit of coordination primitives for building distributed systems"Now you have the opportunity to learn about Hadoop from a master -- not only of the technology, but also of common sense and plain talk."--Doug Cutting, Cloudera - from Amzon