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

Auteur: Tyler Akidau
Taal: Engels
Uitgever: O'Reilly Media
Co-auteur: Reuven Lax
  • Engels
  • E-book
  • 9781491983829
  • Druk: 1
  • juli 2018
  • Epub zonder kopieerbeveiliging (DRM)
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Samenvatting

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


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Productspecificaties

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Taal
Engels
Bindwijze
E-book
Druk
1
Verschijningsdatum
juli 2018
Ebook formaat
Epub zonder kopieerbeveiliging (DRM)
Illustraties
Nee

Betrokkenen

Auteur
Tyler Akidau Slava Chernyak
Co-auteur
Slava Chernyak
Uitgever
O'Reilly Media

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EAN

EAN
9781491983829

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NUR code
980
Subtitel
The What, Where, When, and How of Large-Scale Data Processing

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