Preface

JVM has become a clear winner in the race between different methods of scalable data analysis. The power of JVM, strong typing, simplicity of code, composability, and availability of highly abstracted distributed and machine learning frameworks make Scala a clear contender for the top position in large-scale data analysis. Thanks to its dynamic-looking, yet static type system, scientists and programmers coming from Python backgrounds feel at ease with Scala.

This book aims to provide easy-to-use recipes in Apache Spark, a massively scalable distributed computation framework, and Breeze, a linear algebra library on which Spark's machine learning toolkit is built. The book will also help you explore data using interactive visualizations in Apache Zeppelin.

Other than the handful of frameworks and libraries that we will see in this book, there's a host of other popular data analysis libraries and frameworks that are available for Scala. They are by no means lesser beasts, and they could actually fit our use cases well. Unfortunately, they aren't covered as part of this book.