Hadoop in Practice, Second Edition provides over 100 tested, instantly useful techniques that will help you conquer big data, using Hadoop. This revised new edition covers changes and new features in the Hadoop core architecture, including MapReduce 2. Brand new chapters cover YARN and integrating...

If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as...

I got my start with HBase in the fall of 2008. It was a young project then, released only in the preceding year. As early releases go, it was quite capable, although not without its fair share of embarrassing warts. Not bad for an Apache subproject with fewer than 10 active committers to its name! That was the height of the NoSQL...

Although you don’t need a large computing infrastructure to process massive amounts of data with Apache Hadoop, it can still be difficult to get started. This practical guide shows you how to quickly launch data analysis projects in the cloud by using Amazon Elastic MapReduce (EMR), the hosted Hadoop framework in Amazon Web...

If you are reading this book, then you likely have already installed CouchDB, explored the Futon web administration console, and created a few documents using the cURL command-line tool. You may even have created a CouchApp or other type of application that accesses documents stored in a CouchDB database. However, to use CouchDB for...

Hadoop in Action teaches readers how to use Hadoop and write MapReduce programs. The intended readers are programmers, architects, and project managers who have to process large amounts of data offline. Hadoop in Action will lead the reader from obtaining a copy of Hadoop to setting it up in a cluster and writing data...