[RMarcus]

This is the main motivation behind learned "steering" query optimizers: even if a DBA finds the right hint for a query, it is difficult to track that hint through data changes, future DB versions, and even query changes (e.g., if you add another condition to the WHERE clause, should you keep the hints or drop them?). Turns out, with a little bit of systems work, ML models can do a reasonably good job of selecting a good hint for a particular query plan.