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Streaming Systems读书介绍

类别 页数 译者 网友评分 年代 出版社
书籍 352页 8.9 2020 O'Reilly Media
定价 出版日期 最近访问 访问指数
USD 39.99 2020-02-20 … 2021-05-22 … 54
主题/类型/题材/标签
大数据,分布式,计算机,数据库,软件工程,数据挖掘,英文版,编程,
作者
Tyler Akidau      ISBN:9781491983874    原作名/别名:《》
内容和作者简介
Streaming Systems摘要

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.

You’ll explore:

How streaming and batch data processing patterns compare

The core principles and concepts behind robust out-of-order data processing

How watermarks track progress and completeness in infinite datasets

How exactly-once data processing techniques ensure correctness

How the concepts of streams and tables form the foundations of both batch and streaming data processing

The practical motivations behind a powerful persistent state mechanism, driven by a real-world example

How time-varying relations provide a link between stream processing and the world of SQL and relational algebra

作者简介

Tyler Akidau is a senior staff software engineer at Google, where he is the technical lead for the Data Processing Languages & Systems group, responsible for Google's Apache Beam efforts, Google Cloud Dataflow, and internal data processing tools like Google Flume, MapReduce, and MillWheel. His also a founding member of the Apache Beam PMC. Though deeply passionate and vocal abo...

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