000			nam a22 4500
999			_c7617 _d7617
005			20181029171011.0
008			181029b xxu||||| |||| 00| 0 eng d
020			_a9789352137572
040			_cAIKTC-KRRC
041			_aENG
082			_2DDC23 _a006.31 _bOSI
100			_94957 _aOsinga, Douwe
245			_aDeep learning cookbook _b: Practical recipes to get started quickly
250			_a1st
260			_aNavi Mumbai _bShroff Publishers & Distributors _c2018
300			_axv, 234p. _bPaperback _c22.8*17.8 cm
520			_aStreaming 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. _b 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
650		0	_94619 _aEXTC Engineering
942			_2ddc _cBK