I'm working on a Python CLI that uses asyncio/aiohttp to make and process requests to a 3rd party API. Anyways, I ran into the 10,000 socket problem today and ended up using a semaphore, that actually boosted the overall performance. Why is that? Is it just because the CPU is overwhelmed otherwise?
It depends. Maybe you aren't closing the sockets properly (shutdown + close). Or maybe, because of how TCP works, the sockets are stuck in timeouts and don't really close for a long period of time. If its something like that, then your old connections aren't really closing, and new ones can't be created.
Or maybe it's a simple problem of aiohttp performance -- as shown in the blog post, its HTTP parser is a bit slow.
In general, I'd recommend to use a fewer number of sockets and implement some pipelining of API requests.
Are you making all connections within a single session?
Not long ago I saw example here that someone was creating a new session for every single connection. This is not very optimal way of using it. If you use it within same session, aiohttp will make use of keep-alive, which in turn will reuse existing connections and reduce overhead. You also won't need to use a semaphore, since you can define limit in TCPConnector.
Why you had performance issues? As other said, you were making thousands of connections, each socket need to be in TIME_WAIT state for 2 minutes after closing (limitation of TCP, SCTP does not have this problem). So if you use all connections within short time, you'll essentially run out of them. Some people use tcp_tw_reuse/recycle, and that solves this issue, but that makes your connections no longer follow RFC and you might encounter strange issues later on. The advice above should resolve your problem without any hacks.
