Streaming Systems: The What, Where, When, and How of Large-Scale Data Processing 1st Edition

Streaming data is a big deal in big data these days, and for good reason. Businesses crave ever more timely data, and streaming is a good way to achieve lower latency. Plus, streaming is a much easier way to tame the massive, unbounded data sets that are increasingly common today.

Expanded from co-author Tyler Akidau's series of popular blog posts "Streaming 101" and "Streaming 102", this practical book shows data engineers, data scientists, and developers how to work with streaming or event-time data in a conceptual and platform-agnostic way. You'll go from "101"-level understanding of stream processing to a nuanced grasp of the what, where, when, and how processing of real-time data streams.

Dive deep into topics including watermarks and windowing, as well as state and timers in the context of stream processing.