Apache Hadoop is ideal for organizations with a growing need to store and process massive application datasets. Hadoop: The Definitive Guide is a comprehensive resource for using Hadoop to build reliable, scalable, distributed systems. Programmers will find details for analyzing large datasets with Hadoop, and administrators will learn how to set up and run Hadoop clusters. The book includes case studies that illustrate how Hadoop solves specific problems.
Organizations large and small are adopting Apache Hadoop to deal with huge application datasets. Hadoop: The Definitive Guide provides you with the key for unlocking the wealth this data holds. Hadoop is ideal for storing and processing massive amounts of data, but until now, information on this open-source project has been lacking -- especially with regard to best practices. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems. Programmers will find details for analyzing large datasets with Hadoop, and administrators will learn how to set up and run Hadoop clusters.
With case studies that illustrate how Hadoop solves specific problems, this book helps you:
* Learn the Hadoop Distributed File System (HDFS), including ways to use its many APIs to transfer data
* Write distributed computations with MapReduce, Hadoop's most vital component
* Become familiar with Hadoop's data and IO building blocks for compression, data integrity, serialization, and persistence
* Learn the common pitfalls and advanced features for writing real-world MapReduce programs
* Design, build, and administer a dedicated Hadoop cluster
* Use HBase, Hadoop's database for structured and semi-structured data
And more. Hadoop: The Definitive Guide is still in progress, but you can get started on this technology with the Rough Cuts edition, which lets you read the book online or download it in PDF format as the manuscript evolves.
