A talk on Foundations of streaming SQL by Tyler Akidau on June 27, 2018 at Lyft's HQ in San Francisco.
This talk will address all of those questions in two parts.
First, we’ll explore the relationship between the Beam Model (as described in The Dataflow Model paper and the Streaming 101 and Streaming 102 blog posts) and stream & table theory (as popularized by Martin Kleppmann and Jay Kreps, etc., but essentially originating out of the database world).
Second, we’ll apply our clear understanding of that relationship towards explaining what is required to provide robust stream processing support in SQL. We’ll discuss concrete efforts that have been made in this area by the Apache Beam, Calcite, and Flink communities, compare to other offerings such as Kafka KSQL & Spark Structured streaming, and talk about new ideas yet to come.
In the end, you can expect to have a much better understanding of the key concepts underpinning data processing, regardless of whether that data processing batch or streaming, SQL or programmatic, as well as a concrete notion of what robust stream processing in SQL looks like.
Speaker bio:
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. He is the author of the 2015 Dataflow Model paper and the Streaming 101 and Streaming 102 articles on the O’Reilly website. His preferred mode of transportation is by cargo bike, with his two young daughters in tow.