Author Description

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 Tyler Akidau, Slava Chernyak, Reuven Lax. Includes Index. Includes Bibliographical References And Index.