Spark in Action
Petar Zečević and Marko Bonaći
  • November 2016
  • ISBN 9781617292606
  • 472 pages
  • printed in black & white

Dig in and get your hands dirty with one of the hottest data processing engines today. A great guide.

Jonathan Sharley, Pandora Media

Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. Fully updated for Spark 2.0.

Listen to this book in liveAudio! liveAudio integrates a professional voice recording with the book’s text, graphics, code, and exercises in Manning’s exclusive liveBook online reader. Use the text to search and navigate the audio, or download the audio-only recording for portable offline listening. You can purchase or upgrade to liveAudio here or in liveBook.

About the Technology

Big data systems distribute datasets across clusters of machines, making it a challenge to efficiently query, stream, and interpret them. Spark can help. It is a processing system designed specifically for distributed data. It provides easy-to-use interfaces, along with the performance you need for production-quality analytics and machine learning. Spark 2 also adds improved programming APIs, better performance, and countless other upgrades.

About the book

Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. You'll get comfortable with the Spark CLI as you work through a few introductory examples. Then, you'll start programming Spark using its core APIs. Along the way, you'll work with structured data using Spark SQL, process near-real-time streaming data, apply machine learning algorithms, and munge graph data using Spark GraphX. For a zero-effort startup, you can download the preconfigured virtual machine ready for you to try the book's code.

What's inside

  • Updated for Spark 2.0
  • Real-life case studies
  • Spark DevOps with Docker
  • Examples in Scala, and online in Java and Python

About the reader

Written for experienced programmers with some background in big data or machine learning.

About the authors

Petar Zečević and Marko Bonaći are seasoned developers heavily involved in the Spark community.


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