Gal Krispel

Short Abstract "It works, most of the time…" It’s the one warning they don’t provide in the FlinkSQL documentation. While writing standard SQL for streaming apps sounds like a dream, the reality of production often feels like trying to survive the first day of middle school without a map. Between data type inference mapping that misses your target and circular application restarts due to malformed records, you need more than just a SELECT statement to get by. In this session, we’re declassifying the secrets of FlinkSQL. I’ll move past the "Flink 101" tutorials to show you how to utilize a Hybrid API approach to get the flexibility of streaming SQL and the battle -fought reliability of DataStream API and ProcessFunction. ________________________________________________________________________ Full Description The official FlinkSQL interface promises a smooth ride, but as any survivor knows, production is where things get messy. At Riskified, we’ve hit the limits of "pure" SQL and had to write our own rules for survival. This session is your Declassified Survival Guide to the parts of FlinkSQL that aren’t in the handbook. We’ll examine the architecture of a fault-tolerant FlinkSQL…