Apache Flink aims to make stream processing easy and accessible for everyone. It should come as no surprise that a high level of abstraction puts more load on the core. Flink's SQL engine is the workhorse behind many on-prem and managed SQL platforms. Yet very few users know what is really going on under the hood when submitting a SQL query. In this talk, we take a deep look into the internals of Flink SQL. Let's take the stack apart! We start with some SQL text and go all the way down to Flink's streaming primitives. I will go through the individual optimizer phases. You will learn how event-time operations are tracked when declaring a watermark, how state is managed when using different kinds of joins, and how changelog modes and upsert keys travel through topology when reading from a Change Data Capture connector. After this talk, you may not be able to write an optimizer rule, but you should, at least, get a feeling for the power of a simple streaming SQL query.