this post was submitted on 15 Jun 2023
187 points (93.9% liked)

Programming

17686 readers
125 users here now

Welcome to the main community in programming.dev! Feel free to post anything relating to programming here!

Cross posting is strongly encouraged in the instance. If you feel your post or another person's post makes sense in another community cross post into it.

Hope you enjoy the instance!

Rules

Rules

  • Follow the programming.dev instance rules
  • Keep content related to programming in some way
  • If you're posting long videos try to add in some form of tldr for those who don't want to watch videos

Wormhole

Follow the wormhole through a path of communities [email protected]



founded 2 years ago
MODERATORS
 

My first experience with Lemmy was thinking that the UI was beautiful, and lemmy.ml (the first instance I looked at) was asking people not to join because they already had 1500 users and were struggling to scale.

1500 users just doesn't seem like much, it seems like the type of load you could handle with a Raspberry Pi in a dusty corner.

Are the Lemmy servers struggling to scale because of the federation process / protocols?

Maybe I underestimate how much compute goes into hosting user generated content? Users generate very little text, but uploading pictures takes more space. Users are generating millions of bytes of content and it's overloading computers that can handle billions of bytes with ease, what happened? Am I missing something here?

Or maybe the code is just inefficient?

Which brings me to the title's question: Does Lemmy benefit from using Rust? None of the problems I can imagine are related to code execution speed.

If the federation process and protocols are inefficient, then everything is being built on sand. Popular protocols are hard to change. How often does the HTTP protocol change? Never. The language used for the code doesn't matter in this case.

If the code is just inefficient, well, inefficient Rust is probably slower than efficient Python or JavaScript. Could the complexity of Rust have pushed the devs towards a simpler but less efficient solution that ends up being slower than garbage collected languages? I'm sure this has happened before, but I don't know anything about the Lemmy code.

Or, again, maybe I'm just underestimating the amount of compute required to support 1500 users sharing a little bit of text and a few images?

you are viewing a single comment's thread
view the rest of the comments
[–] 24Vindustrialdildo 42 points 2 years ago (1 children)

I think the devs openly stated they aren't backend bods and asked for help optimising the database as a priority. There's a bit of work going on on github to sort that out I think. Anyone reading this who can optimise postgresql or contribute to a database agnostic retool should probably speak to the devs as I imagine you'd be welcome.

I wish I could help so much but I doubt they're going to retool into .net haha.

[–] [email protected] 15 points 2 years ago* (last edited 2 years ago) (1 children)

Which is fine. If they wanted to learn Rust and wrote inefficient code, good for them. I appreciate their efforts. Rust can certainly be beaten into shape and perform well enough in the end.

[–] [email protected] 5 points 2 years ago (1 children)

Rust itself or the way the Rust logic is implemented is not the bottleneck. Like most decent web applications the bottleneck is the database and how the decentralized protocols themselves are reconciled there.

Scaling massive amounts of records like Lemmy has been forced to is almost always IO bound at the database level even when a web service is centralized; this is much more difficult in federated architectures. This is why “NoSQL” databases have increased in popularity, but they are also not a magic bullet as there are major ACID trade offs one needs to consider.

[–] [email protected] 7 points 2 years ago

NoSQL databases are no silver bullet and the costs of ACID are usually exaggerated (plus most NoSQL databases actually implement ACID anyway). NoSQL databases and SQL databases often have similar performance characteristics since most of the technology is typically the same under the hood.

Plus from my experience as a database consultant: databases are rarely IO bound, NoSQL or SQL unless you have a strange workload. Most time for query execution is usually spent waiting on loads or executing CPU instructions, not waiting on disk IO.