Hi Robert, Jason,
Thank you both for your detailed and thoughtful responses — they helped me see the problem more clearly. Let me share some more details about our specific case: - We have exactly one consumer (worker), and we can’t add more because the underlying resource can only be accessed by one process at a time (think of it as exclusive access to a single connection). - The worker operation is a TCP connection, which is usually fast, but the network can occasionally be unreliable and introduce delays. - We may have lots of producers, and each producer waits for a result after submitting a request. Given these constraints, can an unbuffered channel have any advantage over a buffered one for our case? My understanding is that producers will just end up blocking when the single worker can’t keep up — so whether the blocking happens at “enqueue time” (unbuffered channel) or later (buffered channel). What’s your view — is there any benefit in using an unbuffered/buffered channel in this situation? Thanks again for the guidance! понедельник, 1 сентября 2025 г. в 14:04:48 UTC-5, Jason E. Aten: > Hi Egor, > > To add to what Robert advises -- there is no one-size-fits-all > guidance that covers all situations. You have to understand the > principles of operation and reason/measure from there. There are > heuristics, but even then exceptions to the rules of thumb abound. > > As Robert said, in general the buffered channel will give you > more opportunity for parallelism, and might move your bottleneck > forward or back in the processing pipeline. > > You could try to study the location of your bottleneck, and tracing > ( https://go.dev/blog/execution-traces-2024 ) might help > there (but I've not used it myself--I would just start with a > basic CPU profile and see if there are hot spots). > > An old design heuristic in Go was to always start > with unbuffered channels. Then add buffering to tune > performance. > > However there are plenty of times when I > allocate a channel with a buffer of size 1 so that I know > my initial sender can queue an initial value without itself > blocking. > > Sometimes, for flow-control, I never want to > buffer a channel--in particular when going network <-> channel, > because I want the local back-pressure to propagate > through TCP/QUIC to the result in back-pressure on the > remote side, and if I buffer then in effect I'm asking for work I cannot > yet handle. > > If I'm using a channel as a test event history, then I typically > give it a massive buffer, and even then also wrap it in a function > that will panic if the channel reaches cap() capacity; because > I never really want my tests to be blocked on creating > a test execution event-specific "trace" that I'm going to > assert over in the test. So in that case I always want big buffers. > > As above, exceptions to most heuristics are common. > > In your particular example, I suspect your colleague is right > and you are not gaining anything from channel buffering--of course > it is impossible to know for sure without the system in front > of you to measure. > > Lastly, you likely already realize this, but the request+response > wait pattern you cited typically needs both request and waiting > for the response to be wrapped in selects with a "bail-out" or shutdown > channel: > > jobTicket := makeJobTicketWithDoneChannel() > select { > case sendRequestToDoJobChan <- jobTicket: > case <-bailoutOnShutDownChan: // or context.Done, etc > // exit/cleanup here > } > select { > case <-jobTicket.Done: > case <-bailoutOnShutDownChan: > // exit/cleanup here > } > in order to enable graceful stopping/shutdown of goroutines. > On Monday, September 1, 2025 at 5:13:32 PM UTC+1 robert engels wrote: > >> There is not enough info to give a full recommendation but I suspect you >> are misunderstanding how it works. >> >> The buffered channels allow the producers to continue while waiting for >> the consumer to finish. >> >> If the producer can’t continue until the consumer runs and provides a >> value via a callback or other channel, then yes the buffered channel might >> not seem to provide any value - expect that in a highly concurrent >> environment go routines are usually not in a pure ‘reading the channel’ >> mode - they are finishing up a previous request - so the buffering allows >> some level of additional concurrency in the state. >> >> When requests are extremely short in duration this can matter a lot. >> >> Usually though, a better solution is to simply have N+1 consumers for N >> producers and use a handoff channel (unbuffered) - but if the workload is >> CPU bound you will expend extra resources context switching (ie. thrashing) >> - because these Go routines will be timesliced. >> >> Better to cap the consumers and use a buffered channel. >> >> >> >> On Sep 1, 2025, at 08:37, Egor Ponomarev <egorvpo...@gmail.com> wrote: >> >> We’re using a typical producer-consumer pattern: goroutines send messages >> to a channel, and a worker processes them. A colleague asked me why we even >> bother with a buffered channel (say, size 1000) if we’re waiting for the >> result anyway. >> >> I tried to explain it like this: there are two kinds of waiting. >> >> >> “Bad” waiting – when a goroutine is blocked trying to send to a full >> channel: >> requestChan <- req // goroutine just hangs here, blocking the system >> >> “Good” waiting – when the send succeeds quickly, and you wait for the >> result afterwards: >> requestChan <- req // quickly enqueued >> result := <-resultChan // wait for result without holding up others >> >> The point: a big buffer lets goroutines hand off tasks fast and free >> themselves for new work. Under burst load, this is crucial — it lets the >> system absorb spikes without slowing everything down. >> >> But here’s the twist: my colleague tested it with 2000 goroutines and got >> roughly the same processing time. His argument: “waiting to enqueue or >> dequeue seems to perform the same no matter how many goroutines are >> waiting.” >> >> So my question is: does Go have any official docs that describe this >> idea? *Effective Go* shows semaphores, but it doesn’t really spell out >> this difference in blocking types. >> >> Am I misunderstanding something, or is this just one of those “implicit >> Go concurrency truths” that everyone sort of knows but isn’t officially >> documented? >> >> -- >> You received this message because you are subscribed to the Google Groups >> "golang-nuts" group. >> To unsubscribe from this group and stop receiving emails from it, send an >> email to golang-nuts...@googlegroups.com. >> To view this discussion visit >> https://groups.google.com/d/msgid/golang-nuts/b4194b6b-51ea-42ff-af34-b7aa6093c15fn%40googlegroups.com >> >> <https://groups.google.com/d/msgid/golang-nuts/b4194b6b-51ea-42ff-af34-b7aa6093c15fn%40googlegroups.com?utm_medium=email&utm_source=footer> >> . >> >> >> -- You received this message because you are subscribed to the Google Groups "golang-nuts" group. 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