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


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Written by Reuven Lax

Published by O'Reilly Media

Oct, 2017

100 pages

Description

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 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 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 of processing 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 code snippets to make examples concrete, it presents a general and broad explanation of streaming that's not tied to a specific framework.

Table of Contents

Part I. The Beam Model
Chapter 1. Streaming 101
Chapter 2. The What, Where, When, And How Of Data Processing
Chapter 3. Watermarks
Chapter 4. Advanced Windowing
Chapter 5. Exactly-Once And Side Effects Part II. Streams And Tables
Chapter 6. Streams And Tables
Chapter 7. The Practicalities Of Persistent State
Chapter 8. Streaming Sql
Chapter 9. Streaming Joins
Chapter 10. The Evolution Of Large-Scale Data Processing

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Title: Streaming Systems: The What, Where, When, and How of Large-Scale Data Processing
Author: Reuven Lax
Language: English
Length: 100
Edition: 1
Publisher: O'Reilly Media
Publication Date: 2017-10-25
ISBN-10: 1491983876
ISBN-13: 9781491983874
NOTICE: BOOK CONTENT AND LINKS HAVE COLLECTED FROM THE INTERNET, YOU MAY GET BROKEN LINK OR COPYRIGHT COMPLAINT. YOU CAN BUY THIS BOOK OR PLEASE MAIL TO daviddlinville at GMX dot COM TO REPORT

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