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

Book Description

Streaming data is a big deal in 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 popular series of blog posts "Streaming 101" and "Streaming 102", this practical book shows data engineers, data scientists, and developers how to work with streaming or -time data in a conceptual and platform-agnostic way. You’ll go from "101"-level understanding of stream to a nuanced grasp of the what, where, when, and how 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. Although the book uses Apache Beam snippets to make examples concrete, it presents a general and broad explanation of streaming that's not tied to a specific .

Table of Contents

Chapter 1. Why Stream Processing?
Chapter 2. Data Processing
Chapter 3. The What, Where, When, and How of Data Processing

Book Details

  • Title: Streaming Systems: The What, Where, When, and How of Large-Scale Data Processing
  • Author: , ,
  • Length: 100 pages
  • Edition: 1
  • Language: English
  • Publisher:
  • Publication Date: 2017-10-25
  • ISBN-10: 1491983876
  • ISBN-13: 9781491983874
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