alt Hacker NewsInteresting to think about how to guard against these cases where query optimisation leads to unexpected results.
I mean this could lead to serious bugs. What can be a way to detect these using linters or in CI before they hit the production.
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On a somewhat related note...
We've moved to MSSQL due to several reasons including customer demand.
We're experiencing the MSSQL query planner occasionally generating terrible plans for core queries which then gets cached, leading to support calls.
Workaround for now has been to have our query geneator append a fixed-value column which and have it change the value every 10 minutes, as a cache defeat.
Still, surprised the engine doesn't figure this out itself, like try regenerating plans frequently if they contain non-trivial table scans say.
Or just expire cache entries every 15 minutes or so, so a bad plan doesn't stick around for too long.
in general end to end tests/whole system tests which mock/stub as little as possible and are focused on testing whole use-case flows is a good starting point (sadly in many teams also a constant uphill battle from convincing PM over allocate time to bootstrap it to making CI harder due to basically having to bootstrap a whole testing system including db etc. to educating devs to write such tests properly, instead of writing unit tests at a end to end test level (which rarely ends well).
Optimal you then combine this with automatic collection and analysis of log traced to detect performance regression (which is hard but just because of the involved tooling but now it needs a CI env with reliable perf. characteristics e.g. not GitHub hosted GitHub action runners).
Through in this case the problem is a trap in the behavior of `IN (...)` sub queries which probably is not specific to WITH clause and might be as deeply rooted as the SQL standard but a you have to pay for being able to read it I'm not sure.