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

by Tyler Akidau  (Author), Slava Chernyak  (Author), Reuven Lax (Author)

ll Indian reprints of O’Reilly are printed in grayscale.

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.<Br> 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.<Br> 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