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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.
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.
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.
Written for experienced programmers with some background in big data or machine learning.
Petar Zečević and Marko Bonaći are seasoned developers heavily involved in the Spark community.
Dig in and get your hands dirty with one of the hottest data processing engines today. A great guide.
Must-have! Speed up your learning of Spark as a distributed computing framework.
An easy-to-follow, step-by-step guide.
An ambitiously comprehensive overview of Spark and its diverse ecosystem.
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