Training a 4B model to produce 81% faster query plans than Postgres
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Unless they’ve been elided, there were no indices other than the PK on any table, and no additional statistics. There are correlated columns here: a given country may have produced more movies in a given range of years, as its movie industry built up; a given country may produce more TV series than movies, etc.
Nearly every time I’ve seen someone resorting to hints for a query, it’s because their statistics are incorrect. Adding hints is papering over the problem, and can backfire later if the data shape changes.
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Mentioned elsewhere but classic ml seems the right tool for this problem
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