June 2019
Beginner to intermediate
452 pages
10h 42m
English
Content preview from Stream Processing with Apache Spark
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Foreword
Welcome to Stream Processing with Apache Spark!
It’s very exciting to see how much both the Apache Spark project, as well as stream processing with Apache Spark have come along since it was first started by Matei Zaharia at University of California Berkeley in 2009. Apache Spark started off as the first unified engine for big data processing and has grown into the de-facto standard for all things big data.
Stream Processing with Apache Spark is an excellent introduction to the concepts, tools, and capabilities of Apache Spark as a stream processing engine. This book will first introduce you to the core Spark concepts necessary to understand modern distributed processing. Then it will explore different stream processing architectures and the fundamental architectural trade-offs between then. Finally, it will illustrate how Structured Streaming in Apache Spark makes it easy to implement distributed streaming applications. In addition, it will also cover the older Spark Streaming (aka, DStream) APIs for building streaming applications with legacy connectors.
In all, this book covers everything you’ll need to know to master building and operating streaming applications using Apache Spark! We look forward to hearing about what you’ll build!
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.