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Streaming Systems
Tyler Akidau
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Description for Streaming Systems
Paperback. 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. Num Pages: 100 pages. BIC Classification: UY. Category: (XV) Technical / Manuals. Dimension: 250 x 150 x 15. Weight in Grams: 666.
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, ... Read more
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, ... Read more
Product Details
Publisher
O´Reilly Media, Inc, USA
Format
Paperback
Publication date
2018
Condition
New
Number of Pages
200
Place of Publication
Sebastopol, United States
ISBN
9781491983874
SKU
V9781491983874
Shipping Time
Usually ships in 4 to 8 working days
Ref
99-2
About Tyler Akidau
Tyler Akidau is a staff software engineer at Google Seattle. He leads technical infrastructure's internal data processing teams (MillWheel & Flume), is a founding member of the Apache Beam PMC, and has spent the last seven years working on massive-scale data processing systems. Though deeply passionate and vocal about the capabilities and importance of stream processing, he is also a ... Read more
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