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Viser: Streaming Systems - The What, Where, When, and How of Large-Scale Data Processing
Streaming Systems Vital Source e-bog
Tyler Akidau, Slava Chernyak og Reuven Lax
(2018)
Streaming Systems
The What, Where, When, and How of Large-Scale Data Processing
Tyler Akidau, Slava Chernyak og Reuven Lax
(2018)
Sprog: Engelsk
om ca. 10 hverdage
Detaljer om varen
- 1. Udgave
- Vital Source searchable e-book (Reflowable pages)
- Udgiver: O'Reilly Media, Inc (Juli 2018)
- Forfattere: Tyler Akidau, Slava Chernyak og Reuven Lax
- ISBN: 9781491983829
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)
Detaljer om varen
- 1. Udgave
- Paperback: 349 sider
- Udgiver: O'Reilly Media, Incorporated (Juli 2018)
- Forfattere: Tyler Akidau, Slava Chernyak og Reuven Lax
- ISBN: 9781491983874
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