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I have had tremdendous success with using LLM's to generate SQL. In my use, the majority of the time, ChatGPT gets things spot-on. Even for really sophisticated
by whalesalad 2y ago
I have had tremdendous success with using LLM's to generate SQL. In my use, the majority of the time, ChatGPT gets things spot-on. Even for really sophisticated queries that are going to inspect and aggregate multiple tables into one single output.
I do agree it is not perfect - and things need to be reviewed - but I rarely get the sort of gobbledygook that "resembles" valid SQL and is in fact meaningless.
- vrighter 2y agomeaningless is good. You can take one look and discard it. The problem is that you can't trust there aren't subtle errors though. So you still need to go everything with a fine toothed comb. If you don't, you're just sitting on a ticking timebomb. "it seems to be working" is very very different to "this does what I had in mind and it will work for all inputs"