Learning Spark

Foreword

In a very short time, Apache Spark has emerged as the next generation big data processing engine, and is being applied throughout the industry faster than ever. Spark improves over Hadoop MapReduce, which helped ignite the big data revolution, in several key dimensions: it is much faster, much easier to use due to its rich APIs, and it goes far beyond batch applications to support a variety of workloads, including interactive queries, streaming, machine learning, and graph processing.

I have been privileged to be closely involved with the development of Spark all the way from the drawing board to what has become the most active big data open source project today, and one of the most active Apache projects! As such, I’m particularly delighted to see Matei Zaharia, the creator of Spark, teaming up with other longtime Spark developers Patrick Wendell, Andy Konwinski, and Holden Karau to write this book.

With Spark’s rapid rise in popularity, a major concern has been lack of good reference material. This book goes a long way to address this concern, with 11 chapters and dozens of detailed examples designed for data scientists, students, and developers looking to learn Spark. It is written to be approachable by readers with no background in big data, making it a great place to start learning about the field in general. I hope that many years from now, you and other readers will fondly remember this as the book that introduced you to this exciting new field.

Ion Stoica, CEO ...