Mahout in Action

Part 2. Clustering

This part of the book, including chapters 7 through 12, explores clustering algorithms in Apache Mahout. With the techniques described here, you can group together similar-looking pieces of data into a set or a cluster. Clustering helps uncover interesting groups of information in a large volume of data. This part of the book begins with simple problems in clustering involving examples written in Java. As we progress, you’ll see more real-world examples and learn how to make Apache Mahout run as Hadoop jobs that can cluster large data easily.

Chapter 7 introduces the notion of clustering and explains it with an example of clustering points in a 2-dimensional plane. Chapter 8 introduces the concept of vectors and explains ...