Details here: https://github.com/LemmyNet/lemmy/issues/3165
This will VASTLY decrease the server load of I/O for PostgreSQL, as this mistaken code is doing writes of ~1700 rows (each known Lemmy instance in the database) on every single comment & post creation. This creates record-locking issues given it is writes, which are harsh on the system. Once this is fixed, some site operators will be able to downgrade their hardware! ;)
Holy shit
It’s not on every comment, it’s mostly triggered on deletions and edits. The problem is actually infintesimally worse and 1700 rows are updated if you delete 3 comments. If you delete more it’s exponential and just straight up fails and locks your database.
I’ll probably put a patch in there later tonight and then see about a PR unless someone else does.
It’s not on every comment,
My testing with latest code is that it is indeed on every single comment INSERT, every new comment. I have the ability to view my live data while using Lemmy: https://lemmyadmin.bulletintree.com/query/raw_site_aggregates?output=table
Every one of the 1486 rows on that table gets +1 on comment when I post a new comment on my instance.
it’s mostly triggered on deletions and edits
That is not correct. Edits do not change the count of comments column on site_aggregates - because the number isn’t changing. Deletes (of a comment or post) in Lemmy are also not SQL DELETE statements, they are just a delete data column in the table. That DELETE PostgreSQL trigger only gets run when a end-user cancels their Lemmy account in their profile.
Man that is some bug, no wonder lemmy had such a rough start performance wise during the reddit migration!
Holy hell. Post this to one of the programming-related communities. That is interesting.
This is fascinating
My biggest takeaway from reading through the GitHub comments though is that it seems like no one actually knows where much of the SQL comes from? As in it’s possible that the bug in question is just one manifestation of old, handwritten Postres code that may or may not be optimized (Or even logical?).
I don’t mean this in a critical way, as things like this are bound to happen in an open-source, federated world. However, I would think a comprehensive audit of the Lemmy Postgres triggers, queries, etc could potentially save us all from some future headaches.
That’s not fascinating, that’s depressing. Lemmy team lacks development skill.
I am always fascinated with these types of comments, specifically for a free and open-source software. There are lemmy instances supporting hundreds of thousands of users and trafic, feedback from both server owners and lemmy devs is almost instantaneous.
A platform like lemmy requires client side knowledge to build both desktop and mobile UI (that are performant), it requires ActivityPub knowledge to integrate with the Fediverse, it requires backend knowledge to build APIs for 100% feature compatibility with 3rd party apps. It requires DB knowledge to optimize queries, it requires devops / platform knowledge to deploy it.
And all of this is built in public.
BuT LEMmY tEaM lAcks dEvEloPmenT SkiLL – sure buddy.
Or there’s just room for improvement and optimization, as each developer has its strengths and weaknesses, as any other professional, and a system like lemmy is very complex and really requires to cover a lot from backend to front end.
And there used to be only 2 developers.
I once check a open source implementation of a niche product from Microsoft, and it was a nightmare of unoptimized code. And Microsoft spent a lot of development resources there.
Creating lemmy as 2 people job is quite impressive. Luckily now there are resources for optimization
This is such a dumb take. Using a database efficiently is not some binary, once-off thing: you build what works based on the data you have at the time. When it works, you move on to other features. It takes analysis of real operation over time to find the bottlenecks, and discipline to focus on fixing the things that will have the most benefit to your users.
There are many successful tech companies who introduce features that create dogshit performance impacts regularly. They work because there are people looking at metrics and catching issues to fix. This is healthy.