Lemmy currently uses distinct tables like post_like: (post_id, person_id, score) and post_saved. Unfortunately this causes performance issues when we have to join many of these tables to create views.
One suggestion in this PR, is to combine these into a single post_action table, with a lot of optional columns depending on the action. This solution scares me a little, because I’m afraid we might lose data integrity, and many of our constraints with so many optional columns.
Is there a better way of doing this in SQL?
CharGPT has its uses, performance tuning is not (yet) one of them. I think ML in performance tuning will eventually be a huge deal when we can leverage rapid iterations and culling to perform a wide number of small tweaks and compare performance… I haven’t seen a good solution to this yet, it’s a really complex problem, but I think it’s inevitable.
Isn’t that what genetic algorithms were about?