In theory, the same framework still works when you include sub queries and joins in the training dataset. But obviously the more complex your SQL, the harder for the model to learn. Complex SQL is still an area of active research. One thing that has shown consistent improvement is to translate natural language to an intermediate representation with explicit and unambiguous structure like SemQL, and then deterministically generate the final SQL from the intermediate representation.