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Streaming systems : the what, where, when, and how of large-scale data processing / Tyler Akidau, Slava Chernyak, Reuven Lax.

By: Contributor(s): Material type: TextTextPublication details: Sebastopol : O'Reilly Media, Inc., 2018.Edition: First editionDescription: xviii, 329 pages : illustrations (some color) ; 24 cmISBN:
  • 9781491983874
  • 1491983876
Subject(s): DDC classification:
  • 006.7876 23
LOC classification:
  • TK5105.386 AKI 2018
Contents:
Preface Or: What Are You Getting Yourself Into Here? -- Part 1. The beam model. Streaming 101 -- The what, where, when, and how of data processing -- Watermarks -- Advanced windowing -- Exactly-once and side effects -- Part 2. Streams and tables. Streams and tables -- The practicalities of persistent state -- Streaming SQL -- Streaming joints -- The evolution of large-scale data processing.
Summary: Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way. Expanded from Tyler Akidau's popular blog posts "Streaming 101" and "Streaming 102", this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You'll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax.
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Includes index.

Preface Or: What Are You Getting Yourself Into Here? -- Part 1. The beam model. Streaming 101 -- The what, where, when, and how of data processing -- Watermarks -- Advanced windowing -- Exactly-once and side effects -- Part 2. Streams and tables. Streams and tables -- The practicalities of persistent state -- Streaming SQL -- Streaming joints -- The evolution of large-scale data processing.

Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way. Expanded from Tyler Akidau's popular blog posts "Streaming 101" and "Streaming 102", this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You'll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax.

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