This isn't true. I have use cases that don't require cancellations or timeout. The tasks I'm running don't involve the network, they either succeed or error after an expensive calculation.
This is an interesting post. My understanding: Most of the use case for async code is I/O bound operations. So you fire off a bunch of async I/O requests and wait to be notified. Logically, I/O requests normally need a timeout and/or cancel feature.
However, you raise a different point:
The tasks I'm running don't involve the network, they either succeed or error after an expensive calculation.
This sounds like CPU-bound, not I/O-bound. (Please correct me if I misunderstand.) Can you please confirm if you are using Go or a different language? If Go, I guess it still makes sense, as green threads are preferred over system threads. If not Go, I would be nice to hear more about your specific scenario. HN is a great place to learn about different use cases for a technology.
I think I just responded too hastily. I am working in Go. There is file IO going on in addition to the calculation (which because of a NAS or whatever could also be network IO). As a practical matter I had never felt the need to offer cancellation or timeout for these use cases, but I probably should, so mea culpa.
What's the point of multiplexing tasks on a particular core if the tasks don't do any I/O? It will be strictly faster to execute the tasks serially across as many cores as possible then.
throwaway2037|2 years ago
However, you raise a different point:
This sounds like CPU-bound, not I/O-bound. (Please correct me if I misunderstand.) Can you please confirm if you are using Go or a different language? If Go, I guess it still makes sense, as green threads are preferred over system threads. If not Go, I would be nice to hear more about your specific scenario. HN is a great place to learn about different use cases for a technology.mftb|2 years ago
eptcyka|2 years ago
mftb|2 years ago