Given a (partially) filled buffered channel in Go
ch := make(chan *MassiveStruct, n)
for i := 0; i < n; i++ {
ch <- NewMassiveStruct()
}
is it advisable to also drain the channel when closing it (by the writer) in case it is unknown when readers are going read from it (e.g. there is a limited number of those and they are currently busy)? That is
close(ch)
for range ch {}
Is such a loop guaranteed to end if there are other concurrent readers on the channel?
Context: a queue service with a fixed number of workers, which should drop processing anything queued when the service is going down (but not necessarily being GCed right after). So I am closing to indicate to the workers that the service is being terminated. I could drain the remaining "queue" immediately letting the GC free the resources allocated, I could read and ignore the values in the workers and I could leave the channel as is running down the readers and setting the channel to nil in the writer so that the GC cleans up everything. I am not sure which is the cleanest way.
It depends on your program, but generally speaking I would tend to say no (you don't need to clear the channel before closing it): if there is items in your channel when you close it, any reader still reading from the channel will receive the items until the channel is emtpy.
Here is an example:
package main
import (
"sync"
"time"
)
func main() {
var ch = make(chan int, 5)
var wg sync.WaitGroup
wg.Add(1)
for range make([]struct{}, 2) {
go func() {
for i := range ch {
wg.Wait()
println(i)
}
}()
}
for i := 0; i < 5; i++ {
ch <- i
}
close(ch)
wg.Done()
time.Sleep(1 * time.Second)
}
Here, the program will output all the items, despite the fact that the channel is closed strictly before any reader can even read from the channel.
There are better ways to achieve what you're trying to achieve. Your current approach can just lead to throwing away some records, and processing other records randomly (since the draining loop is racing all the consumers). That doesn't really address the goal.
What you want is cancellation. Here's an example from Go Concurrency Patterns: Pipelines and cancellation
func sq(done <-chan struct{}, in <-chan int) <-chan int {
out := make(chan int)
go func() {
defer close(out)
for n := range in {
select {
case out <- n * n:
case <-done:
return
}
}
}()
return out
}
You pass a done channel to all the goroutines, and you close it when you want them all to stop processing. If you do this a lot, you may find the golang.org/x/net/context package useful, which formalizes this pattern, and adds some extra features (like timeout).
I feel that the supplied answers actually do not clarify much apart from the hints that neither drain nor closing is needed. As such the following solution for the described context looks clean to me that terminates the workers and removes all references to them or the channel in question, thus, letting the GC to clean up the channel and its content:
type worker struct {
submitted chan Task
stop chan bool
p *Processor
}
// executed in a goroutine
func (w *worker) run() {
for {
select {
case task := <-w.submitted:
if err := task.Execute(w.p); err != nil {
logger.Error(err.Error())
}
case <-w.stop:
logger.Warn("Worker stopped")
return
}
}
}
func (p *Processor) Stop() {
if atomic.CompareAndSwapInt32(&p.status, running, stopped) {
for _, w := range p.workers {
w.stop <- true
}
// GC all workers as soon as goroutines stop
p.workers = nil
// GC all published data when workers terminate
p.submitted = nil
// no need to do the following above:
// close(p.submitted)
// for range p.submitted {}
}
}
Related
func GoCountColumns(in chan []string, r chan Result, quit chan int) {
for {
select {
case data := <-in:
r <- countColumns(data) // some calculation function
case <-quit:
return // stop goroutine
}
}
}
func main() {
fmt.Println("Welcome to the csv Calculator")
file_path := os.Args[1]
fd, _ := os.Open(file_path)
reader := csv.NewReader(bufio.NewReader(fd))
var totalColumnsCount int64 = 0
var totallettersCount int64 = 0
linesCount := 0
numWorkers := 10000
rc := make(chan Result, numWorkers)
in := make(chan []string, numWorkers)
quit := make(chan int)
t1 := time.Now()
for i := 0; i < numWorkers; i++ {
go GoCountColumns(in, rc, quit)
}
//start worksers
go func() {
for {
record, err := reader.Read()
if err == io.EOF {
break
}
if err != nil {
log.Fatal(err)
}
if linesCount%1000000 == 0 {
fmt.Println("Adding to the channel")
}
in <- record
//data := countColumns(record)
linesCount++
//totalColumnsCount = totalColumnsCount + data.ColumnCount
//totallettersCount = totallettersCount + data.LettersCount
}
close(in)
}()
for i := 0; i < numWorkers; i++ {
quit <- 1 // quit goroutines from main
}
close(rc)
for i := 0; i < linesCount; i++ {
data := <-rc
totalColumnsCount = totalColumnsCount + data.ColumnCount
totallettersCount = totallettersCount + data.LettersCount
}
fmt.Printf("I counted %d lines\n", linesCount)
fmt.Printf("I counted %d columns\n", totalColumnsCount)
fmt.Printf("I counted %d letters\n", totallettersCount)
elapsed := time.Now().Sub(t1)
fmt.Printf("It took %f seconds\n", elapsed.Seconds())
}
My Hello World is a program that reads a csv file and passes it to a channel. Then the goroutines should consume from this channel.
My Problem is I have no idea how to detect from the main thread that all data was processed and I can exit my program.
on top of other answers.
Take (great) care that closing a channel should happen on the write call site, not the read call site. In GoCountColumns the r channel being written, the responsibility to close the channel are onto GoCountColumns function. Technical reasons are, it is the only actor knowing for sure that the channel will not being written anymore and thus is safe for close.
func GoCountColumns(in chan []string, r chan Result, quit chan int) {
defer close(r) // this line.
for {
select {
case data := <-in:
r <- countColumns(data) // some calculation function
case <-quit:
return // stop goroutine
}
}
}
The function parameters naming convention, if i might say, is to have the destination as first parameter, the source as second, and others parameters along. The GoCountColumns is preferably written:
func GoCountColumns(dst chan Result, src chan []string, quit chan int) {
defer close(dst)
for {
select {
case data := <-src:
dst <- countColumns(data) // some calculation function
case <-quit:
return // stop goroutine
}
}
}
You are calling quit right after the process started. Its illogical. This quit command is a force exit sequence, it should be called once an exit signal is detected, to force exit the current processing in best state possible, possibly all broken. In other words, you should be relying on the signal.Notify package to capture exit events, and notify your workers to quit. see https://golang.org/pkg/os/signal/#example_Notify
To write better parallel code, list at first the routines you need to manage the program lifetime, identify those you need to block onto to ensure the program has finished before exiting.
In your code, exists read, map. To ensure complete processing, the program main function must ensure that it captures a signal when map exits before exiting itself. Notice that the read function does not matter.
Then, you will also need the code required to capture an exit event from user input.
Overall, it appears we need to block onto two events to manage lifetime. Schematically,
func main(){
go read()
go map(mapDone)
go signal()
select {
case <-mapDone:
case <-sig:
}
}
This simple code is good to process or die. Indeed, when the user event is caught, the program exits immediately, without giving a chance to others routines to do something required upon stop.
To improve those behaviors, you need first a way to signal the program wants to leave to other routines, second, a way to wait for those routines to finish their stop sequence before leaving.
To signal exit event, or cancellation, you can make use of a context.Context, pass it around to the workers, make them listen to it.
Again, schematically,
func main(){
ctx,cancel := context.WithCancel(context.WithBackground())
go read(ctx)
go map(ctx,mapDone)
go signal()
select {
case <-mapDone:
case <-sig:
cancel()
}
}
(more onto read and map later)
To wait for completion, many things are possible, for as long as they are thread safe. Usually, a sync.WaitGroup is being used. Or, in cases like yours where there is only one routine to wait for, we can re use the current mapDone channel.
func main(){
ctx,cancel := context.WithCancel(context.WithBackground())
go read(ctx)
go map(ctx,mapDone)
go signal()
select {
case <-mapDone:
case <-sig:
cancel()
<-mapDone
}
}
That is simple and straight forward. But it is not totally correct. The last mapDone chan might block forever and make the program unstoppable. So you might implement a second signal handler, or a timeout.
Schematically, the timeout solution is
func main(){
ctx,cancel := context.WithCancel(context.WithBackground())
go read(ctx)
go map(ctx,mapDone)
go signal()
select {
case <-mapDone:
case <-sig:
cancel()
select {
case <-mapDone:
case <-time.After(time.Second):
}
}
}
You might also accumulate a signal handling and a timeout in the last select.
Finally, there are few things to tell about read and map context listening.
Starting with map, the implementation requires to read for context.Done channel regularly to detect cancellation.
It is the easy part, it requires to only update the select statement.
func GoCountColumns(ctx context.Context, dst chan Result, src chan []string) {
defer close(dst)
for {
select {
case <-ctx.Done():
<-time.After(time.Minute) // do something more useful.
return // quit. Notice the defer will be called.
case data := <-src:
dst <- countColumns(data) // some calculation function
}
}
}
Now the read part is bit more tricky as it is an IO it does not provide a selectable programming interface and listening to the context channel cancellation might seem contradictory. It is. As IOs are blocking, impossible to listen the context. And while reading from the context channel, impossible to read the IO. In your case, the solution requires to understand that your read loop is not relevant to your program lifetime (recall we only listen onto mapDone?), and that we can just ignore the context.
In other cases, if for example you wanted to restart at last byte read (so at every read, we increment an n, counting bytes, and we want to save that value upon stop). Then, a new routine is required to be started, and thus, multiple routines are to wait for completion. In such cases a sync.WaitGroup will be more appropriate.
Schematically,
func main(){
var wg sync.WaitGroup
processDone:=make(chan struct{})
ctx,cancel := context.WithCancel(context.WithBackground())
go read(ctx)
wg.Add(1)
go saveN(ctx,&wg)
wg.Add(1)
go map(ctx,&wg)
go signal()
go func(){
wg.Wait()
close(processDone)
}()
select {
case <-processDone:
case <-sig:
cancel()
select {
case <-processDone:
case <-time.After(time.Second):
}
}
}
In this last code, the waitgroup is being passed around. Routines are responsible to call for wg.Done(), when all routines are done, the processDone channel is closed, to signal the select.
func GoCountColumns(ctx context.Context, dst chan Result, src chan []string, wg *sync.WaitGroup) {
defer wg.Done()
defer close(dst)
for {
select {
case <-ctx.Done():
<-time.After(time.Minute) // do something more useful.
return // quit. Notice the defer will be called.
case data := <-src:
dst <- countColumns(data) // some calculation function
}
}
}
It is undecided which patterns is preferred, but you might also see waitgroup being managed at call sites only.
func main(){
var wg sync.WaitGroup
processDone:=make(chan struct{})
ctx,cancel := context.WithCancel(context.WithBackground())
go read(ctx)
wg.Add(1)
go func(){
defer wg.Done()
saveN(ctx)
}()
wg.Add(1)
go func(){
defer wg.Done()
map(ctx)
}()
go signal()
go func(){
wg.Wait()
close(processDone)
}()
select {
case <-processDone:
case <-sig:
cancel()
select {
case <-processDone:
case <-time.After(time.Second):
}
}
}
Beyond all of that and OP questions, you must always evaluate upfront the pertinence of parallel processing for a given task. There is no unique recipe, practice and measure your code performances. see pprof.
There is way too much going on in this code. You should restructure your code into short functions that serve specific purposes to make it possible for someone to help you out easily (and help yourself as well).
You should read the following Go article, which goes into concurrency patterns:
https://blog.golang.org/pipelines
There are multiple ways to make one go-routine wait on some other work to finish. The most common ways are with wait groups (example I have provided) or channels.
func processSomething(...) {
...
}
func main() {
workers := &sync.WaitGroup{}
for i := 0; i < numWorkers; i++ {
workers.Add(1) // you want to call this from the calling go-routine and before spawning the worker go-routine
go func() {
defer workers.Done() // you want to call this from the worker go-routine when the work is done (NOTE the defer, which ensures it is called no matter what)
processSomething(....) // your async processing
}()
}
// this will block until all workers have finished their work
workers.Wait()
}
You can use a channel to block main until completion of a goroutine.
package main
import (
"log"
"time"
)
func main() {
c := make(chan struct{})
go func() {
time.Sleep(3 * time.Second)
log.Println("bye")
close(c)
}()
// This blocks until the channel is closed by the routine
<-c
}
No need to write anything into the channel. Reading is blocked until data is read or, which we use here, the channel is closed.
I've just installed Go on Mac, and here's the code
package main
import (
"fmt"
"time"
)
func Product(ch chan<- int) {
for i := 0; i < 100; i++ {
fmt.Println("Product:", i)
ch <- i
}
}
func Consumer(ch <-chan int) {
for i := 0; i < 100; i++ {
a := <-ch
fmt.Println("Consmuer:", a)
}
}
func main() {
ch := make(chan int, 1)
go Product(ch)
go Consumer(ch)
time.Sleep(500)
}
I "go run producer_consumer.go", there's no output on screen, and then it quits.
Any problem with my program ? How to fix it ?
This is a rather verbose answer, but to put it simply:
Using time.Sleep to wait until hopefully other routines have completed their jobs is bad.
The consumer and producer shouldn't know anything about each other, apart from the type they exchange over the channel. Your code relies on both consumer and producer knowing how many ints will be passed around. Not a realistic scenario
Channels can be iterated over (think of them as a thread-safe, shared slice)
channels should be closed
At the bottom of this rather verbose answer where I attempt to explain some basic concepts and best practices (well, better practices), you'll find your code rewritten to work and display all the values without relying on time.Sleep. I've not tested that code, but should be fine
Right, there's a couple of problems here. Just as a bullet-list:
Your channel is buffered to 1, which is fine, but it's not necessary
Your channel is never closed
You're waiting 500ns, then exit regardless of the routines having completed, or even started processing for that matter.
There's no centralised control on over the routines, once you've started them, you have 0 control. If you hit ctrl+c, you might want to cancel routines when writing code that'll handle important data. Check signal handling, and context for this
Channel buffer
Seeing as you already know how many values you're going to push onto your channel, why not simply create ch := make(chan int, 100)? That way your publisher can continue to push messages onto the channel, regardless of what the consumer does.
You don't need to do this, but adding a sensible buffer to your channel, depending on what you're trying to do, is definitely worth checking out. At the moment, though, both routines are using fmt.Println & co, which is going to be a bottleneck either way. Printing to STDOUT is thread-safe, and buffered. This means that each call to fmt.Print* is going to acquire a lock, to avoid text from both routines to be combined.
Closing the channel
You could simply push all the values onto your channel, and then close it. This is, however, bad form. The rule of thumb WRT channels is that channels are created and closed in the same routine. Meaning: you're creating the channel in the main routine, that's where it should be closed.
You need a mechanism to sync up, or at least keep tabs on whether or not your routines have completed their job. That's done using the sync package, or through a second channel.
// using a done channel
func produce(ch chan<- int) <-chan struct{} {
done := make(chan struct{})
go func() {
for i := 0; i < 100; i++ {
ch <- i
}
// all values have been published
// close done channel
close(done)
}()
return done
}
func main() {
ch := make(chan int, 1)
done := produce(ch)
go consume(ch)
<-done // if producer has done its thing
close(ch) // we can close the channel
}
func consume(ch <-chan int) {
// we can now simply loop over the channel until it's closed
for i := range ch {
fmt.Printf("Consumed %d\n", i)
}
}
OK, but here you'll still need to wait for the consume routine to complete.
You may have already noticed that the done channel technically isn't closed in the same routine that creates it either. Because the routine is defined as a closure, however, this is an acceptable compromise. Now let's see how we could use a waitgroup:
import (
"fmt"
"sync"
)
func product(wg *sync.WaitGroup, ch chan<- int) {
defer wg.Done() // signal we've done our job
for i := 0; i < 100; i++ {
ch <- i
}
}
func main() {
ch := make(chan int, 1)
wg := sync.WaitGroup{}
wg.Add(1) // I'm adding a routine to the channel
go produce(&wg, ch)
wg.Wait() // will return once `produce` has finished
close(ch)
}
OK, so this looks promising, I can have the routines tell me when they've finished their tasks. But if I add both consumer and producer to the waitgroup, I can't simply iterate over the channel. The channel will only ever get closed if both routines invoke wg.Done(), but if the consumer is stuck looping over a channel that'll never get closed, then I've created a deadlock.
Solution:
A hybrid would be the easiest solution at this point: Add the consumer to a waitgroup, and use the done channel in the producer to get:
func produce(ch chan<- int) <-chan struct{} {
done := make(chan struct{})
go func() {
for i := 0; i < 100; i++ {
ch <- i
}
close(done)
}()
return done
}
func consume(wg *sync.WaitGroup, ch <-chan int) {
defer wg.Done()
for i := range ch {
fmt.Printf("Consumer: %d\n", i)
}
}
func main() {
ch := make(chan int, 1)
wg := sync.WaitGroup{}
done := produce(ch)
wg.Add(1)
go consume(&wg, ch)
<- done // produce done
close(ch)
wg.Wait()
// consumer done
fmt.Println("All done, exit")
}
I have changed slightly(expanded time.Sleep) your code. Works fine on my Linux x86_64
func Product(ch chan<- int) {
for i := 0; i < 10; i++ {
fmt.Println("Product:", i)
ch <- i
}
}
func Consumer(ch <-chan int) {
for i := 0; i < 10; i++ {
a := <-ch
fmt.Println("Consmuer:", a)
}
}
func main() {
ch := make(chan int, 1)
go Product(ch)
go Consumer(ch)
time.Sleep(10000)
}
Output
go run s1.go
Product: 0
Product: 1
Product: 2
As JimB hinted at, time.Sleep takes a time.Duration, not an integer. The godoc shows an example of how to call this correctly. In your case, you probably want:
time.Sleep(500 * time.Millisecond)
The reason that your program is exiting quickly (but not giving you an error) is due to the (somewhat surprising) way that time.Duration is implemented.
time.Duration is simply a type alias for int64. Internally, it uses the value to represent the duration in nanoseconds. When you call time.Sleep(500), the compiler will gladly interpret the numeric literal 500 as a time.Duration. Unfortunately, that means 500 ns.
time.Millisecond is a constant equal to the number of nanoseconds in a millisecond (1,000,000). The nice thing is that requiring you to do that multiplication explicitly makes it obvious to that caller what the units are on that argument. Unfortunately, time.Sleep(500) is perfectly valid go code but doesn't do what most beginners would expect.
My specific issue is that I have an unbuffered channel and am spawning multiple goroutines bounded with a semaphore to perform work:
func main() {
sem := make(chan struct{}, 10) // allow ten concurrent parsers
wg := &sync.WaitGroup{}
wg.Add(1)
DoSomething("http://example.com", sem, wg)
wg.Wait()
// all done
}
func DoSomething(u string, sem chan struct{}, wg *sync.WaitGroup) {
defer wg.Done()
sem <- struct{}{} // grab
defer func() { <-sem }() // release
var newSomethings []string
// ...
for u := range newSomethings {
wg.Add(1)
go DoSomething(u)
}
}
If there are multiple DoSomething goroutines on the stack, blocked on the sem write (or inversely on a read) When a write happens is there any ordering to which go routine gets through with the write?? I would guess it were random but I could imagine:
it is random
writes/receives happen in the order they are registered
implementation dependent
I looked at a couple of resources and was unable to find a solution:
https://github.com/golang/go/issues/247
https://golang.org/ref/spec#Receive_operator
https://golang.org/ref/spec#Channel_types
I'm wondering if this is undefined and/or implementation dependent, or if this logic is located and defined somewhere within go core?
The order that goroutines blocked on a send operation are serviced is not defined, but it's implemented as a FIFO. You can see the implementation in runtime/chan.go, which uses a linked list to track the channel's senders and receivers.
We can try to make an example showing the effective ordering like so:
func main() {
ch := make(chan int)
ready := make(chan int)
for i := 0; i < 10; i++ {
i := i
go func() {
ready <- 1
ch <- i
}()
<-ready
runtime.Gosched()
}
for i := 0; i < 10; i++ {
v := <-ch
if i != v {
panic("out of order!")
}
fmt.Println(v)
}
}
https://play.golang.org/p/u0ukR-5Ptw4
This still isn't technically correct, because there's no way to observe blocking on a send operation, so there's still a race between the ready send and the send to ch on the next line. We can try to eliminate that with the runtime.Gosched call here, or even a time.Sleep, but without explicit synchronization there's no guarantee of a "happens before" relationship.
Regardless, this queues up the goroutines and shows the expected output order, and if they weren't queued up already, it would be more likely to process the values out of order.
You can see by this example that we can't truly determine the order that the goroutines are queued up, it is almost always non-deterministic, and therefore reasoning about this isn't usually useful in practice.
This is a good example of workers & controller mode in Go written by #Jimt, in answer to
"Is there some elegant way to pause & resume any other goroutine in golang?"
package main
import (
"fmt"
"runtime"
"sync"
"time"
)
// Possible worker states.
const (
Stopped = 0
Paused = 1
Running = 2
)
// Maximum number of workers.
const WorkerCount = 1000
func main() {
// Launch workers.
var wg sync.WaitGroup
wg.Add(WorkerCount + 1)
workers := make([]chan int, WorkerCount)
for i := range workers {
workers[i] = make(chan int)
go func(i int) {
worker(i, workers[i])
wg.Done()
}(i)
}
// Launch controller routine.
go func() {
controller(workers)
wg.Done()
}()
// Wait for all goroutines to finish.
wg.Wait()
}
func worker(id int, ws <-chan int) {
state := Paused // Begin in the paused state.
for {
select {
case state = <-ws:
switch state {
case Stopped:
fmt.Printf("Worker %d: Stopped\n", id)
return
case Running:
fmt.Printf("Worker %d: Running\n", id)
case Paused:
fmt.Printf("Worker %d: Paused\n", id)
}
default:
// We use runtime.Gosched() to prevent a deadlock in this case.
// It will not be needed of work is performed here which yields
// to the scheduler.
runtime.Gosched()
if state == Paused {
break
}
// Do actual work here.
}
}
}
// controller handles the current state of all workers. They can be
// instructed to be either running, paused or stopped entirely.
func controller(workers []chan int) {
// Start workers
for i := range workers {
workers[i] <- Running
}
// Pause workers.
<-time.After(1e9)
for i := range workers {
workers[i] <- Paused
}
// Unpause workers.
<-time.After(1e9)
for i := range workers {
workers[i] <- Running
}
// Shutdown workers.
<-time.After(1e9)
for i := range workers {
close(workers[i])
}
}
But this code also has an issue: If you want to remove a worker channel in workers when worker() exits, dead lock happens.
If you close(workers[i]), next time controller writes into it will cause a panic since go can't write into a closed channel. If you use some mutex to protect it, then it will be stuck on workers[i] <- Running since the worker is not reading anything from the channel and write will be blocked, and mutex will cause a dead lock. You can also give a bigger buffer to channel as a work-around, but it's not good enough.
So I think the best way to solve this is worker() close channel when exits, if the controller finds a channel closed, it will jump over it and do nothing. But I can't find how to check a channel is already closed or not in this situation. If I try to read the channel in controller, the controller might be blocked. So I'm very confused for now.
PS: Recovering the raised panic is what I have tried, but it will close goroutine which raised panic. In this case it will be controller so it's no use.
Still, I think it's useful for Go team to implement this function in next version of Go.
There's no way to write a safe application where you need to know whether a channel is open without interacting with it.
The best way to do what you're wanting to do is with two channels -- one for the work and one to indicate a desire to change state (as well as the completion of that state change if that's important).
Channels are cheap. Complex design overloading semantics isn't.
[also]
<-time.After(1e9)
is a really confusing and non-obvious way to write
time.Sleep(time.Second)
Keep things simple and everyone (including you) can understand them.
In a hacky way it can be done for channels which one attempts to write to by recovering the raised panic. But you cannot check if a read channel is closed without reading from it.
Either you will
eventually read the "true" value from it (v <- c)
read the "true" value and 'not closed' indicator (v, ok <- c)
read a zero value and the 'closed' indicator (v, ok <- c) (example)
will block in the channel read forever (v <- c)
Only the last one technically doesn't read from the channel, but that's of little use.
I know this answer is so late, I have wrote this solution, Hacking Go run-time, It's not safety, It may crashes:
import (
"unsafe"
"reflect"
)
func isChanClosed(ch interface{}) bool {
if reflect.TypeOf(ch).Kind() != reflect.Chan {
panic("only channels!")
}
// get interface value pointer, from cgo_export
// typedef struct { void *t; void *v; } GoInterface;
// then get channel real pointer
cptr := *(*uintptr)(unsafe.Pointer(
unsafe.Pointer(uintptr(unsafe.Pointer(&ch)) + unsafe.Sizeof(uint(0))),
))
// this function will return true if chan.closed > 0
// see hchan on https://github.com/golang/go/blob/master/src/runtime/chan.go
// type hchan struct {
// qcount uint // total data in the queue
// dataqsiz uint // size of the circular queue
// buf unsafe.Pointer // points to an array of dataqsiz elements
// elemsize uint16
// closed uint32
// **
cptr += unsafe.Sizeof(uint(0))*2
cptr += unsafe.Sizeof(unsafe.Pointer(uintptr(0)))
cptr += unsafe.Sizeof(uint16(0))
return *(*uint32)(unsafe.Pointer(cptr)) > 0
}
Well, you can use default branch to detect it, for a closed channel will be selected, for example: the following code will select default, channel, channel, the first select is not blocked.
func main() {
ch := make(chan int)
go func() {
select {
case <-ch:
log.Printf("1.channel")
default:
log.Printf("1.default")
}
select {
case <-ch:
log.Printf("2.channel")
}
close(ch)
select {
case <-ch:
log.Printf("3.channel")
default:
log.Printf("3.default")
}
}()
time.Sleep(time.Second)
ch <- 1
time.Sleep(time.Second)
}
Prints
2018/05/24 08:00:00 1.default
2018/05/24 08:00:01 2.channel
2018/05/24 08:00:01 3.channel
Note, refer to comment by #Angad under this answer:
It doesn't work if you're using a Buffered Channel and it contains
unread data
I have had this problem frequently with multiple concurrent goroutines.
It may or may not be a good pattern, but I define a a struct for my workers with a quit channel and field for the worker state:
type Worker struct {
data chan struct
quit chan bool
stopped bool
}
Then you can have a controller call a stop function for the worker:
func (w *Worker) Stop() {
w.quit <- true
w.stopped = true
}
func (w *Worker) eventloop() {
for {
if w.Stopped {
return
}
select {
case d := <-w.data:
//DO something
if w.Stopped {
return
}
case <-w.quit:
return
}
}
}
This gives you a pretty good way to get a clean stop on your workers without anything hanging or generating errors, which is especially good when running in a container.
You could set your channel to nil in addition to closing it. That way you can check if it is nil.
example in the playground:
https://play.golang.org/p/v0f3d4DisCz
edit:
This is actually a bad solution as demonstrated in the next example,
because setting the channel to nil in a function would break it:
https://play.golang.org/p/YVE2-LV9TOp
ch1 := make(chan int)
ch2 := make(chan int)
go func(){
for i:=0; i<10; i++{
ch1 <- i
}
close(ch1)
}()
go func(){
for i:=10; i<15; i++{
ch2 <- i
}
close(ch2)
}()
ok1, ok2 := false, false
v := 0
for{
ok1, ok2 = true, true
select{
case v,ok1 = <-ch1:
if ok1 {fmt.Println(v)}
default:
}
select{
case v,ok2 = <-ch2:
if ok2 {fmt.Println(v)}
default:
}
if !ok1 && !ok2{return}
}
}
From the documentation:
A channel may be closed with the built-in function close. The multi-valued assignment form of the receive operator reports whether a received value was sent before the channel was closed.
https://golang.org/ref/spec#Receive_operator
Example by Golang in Action shows this case:
// This sample program demonstrates how to use an unbuffered
// channel to simulate a game of tennis between two goroutines.
package main
import (
"fmt"
"math/rand"
"sync"
"time"
)
// wg is used to wait for the program to finish.
var wg sync.WaitGroup
func init() {
rand.Seed(time.Now().UnixNano())
}
// main is the entry point for all Go programs.
func main() {
// Create an unbuffered channel.
court := make(chan int)
// Add a count of two, one for each goroutine.
wg.Add(2)
// Launch two players.
go player("Nadal", court)
go player("Djokovic", court)
// Start the set.
court <- 1
// Wait for the game to finish.
wg.Wait()
}
// player simulates a person playing the game of tennis.
func player(name string, court chan int) {
// Schedule the call to Done to tell main we are done.
defer wg.Done()
for {
// Wait for the ball to be hit back to us.
ball, ok := <-court
fmt.Printf("ok %t\n", ok)
if !ok {
// If the channel was closed we won.
fmt.Printf("Player %s Won\n", name)
return
}
// Pick a random number and see if we miss the ball.
n := rand.Intn(100)
if n%13 == 0 {
fmt.Printf("Player %s Missed\n", name)
// Close the channel to signal we lost.
close(court)
return
}
// Display and then increment the hit count by one.
fmt.Printf("Player %s Hit %d\n", name, ball)
ball++
// Hit the ball back to the opposing player.
court <- ball
}
}
it's easier to check first if the channel has elements, that would ensure the channel is alive.
func isChanClosed(ch chan interface{}) bool {
if len(ch) == 0 {
select {
case _, ok := <-ch:
return !ok
}
}
return false
}
If you listen this channel you always can findout that channel was closed.
case state, opened := <-ws:
if !opened {
// channel was closed
// return or made some final work
}
switch state {
case Stopped:
But remember, you can not close one channel two times. This will raise panic.
I have a slice of channels that all receive the same message:
func broadcast(c <-chan string, chans []chan<- string) {
for msg := range c {
for _, ch := range chans {
ch <- msg
}
}
}
However, since each of the channels in chans are potentially being read at a different rate, I don't want to block the other channels when I get a slow consumer. I've solved this with goroutines:
func broadcast(c <-chan string, chans []chan<- string) {
for msg := range c {
for _, ch := range chans {
go func() { ch <- msg }()
}
}
}
However, the order of the messages that get passed to each channel is important. I looked to the spec to see if channels preserve order when blocked, and all I found was this:
If the capacity is greater than zero, the channel is asynchronous: communication operations succeed without blocking if the buffer is not full (sends) or not empty (receives), and elements are received in the order they are sent.
To me, if a write is blocked, then it is not "sent", but waiting to be sent. With that assumption, the above says nothing about order of sending when multiple goroutines are blocked on writing.
Are there any guarantees about the order of sends after a channel becomes unblocked?
No, there are no guarantees.
Even when the channel is not full, if two goroutines are started at about the same time to send to it, I don't think there is any guarantee that the goroutine that was started first would actually execute first. So you can't count on the messages arriving in order.
You can drop the message if the channel is full (and then set a flag to pause the client and send them a message that they're dropping messages or whatever).
Something along the lines of (untested):
type Client struct {
Name string
ch chan<-string
}
func broadcast(c <-chan string, chans []*Client) {
for msg := range c {
for _, ch := range chans {
select {
case ch.ch <- msg:
// all okay
default:
log.Printf("Channel was full sending '%s' to client %s", msg, ch.Name)
}
}
}
}
In this code, no guarantees.
The main problem with the given sample code lies not in the channel behavior, but rather in the numerous created goroutines. All the goroutines are "fired" inside the same imbricated loop without further synchronization, so even before they start to send messages, we simply don't know which ones will execute first.
However this rises a legitimate question in general : if we somehow garantee the order of several blocking send instructions, are we guaranteed to receive them in the same order?
The "happens-before" property of the sendings is difficult to create. I fear it is impossible because :
Anything can happen before the sending instruction : for example, other goroutines performing their own sendings or not
A goroutine being blocked in a sending cannot simultaneously manage other sorts of synchronization
For example, if I have 10 goroutines numbered 1 to 10, I have no way of letting them send their own number to the channel, concurrently, in the right order. All I can do is use various kinds of sequential tricks like doing the sorting in 1 single goroutine.
This is an addition to the already posted answers.
As practically everyone stated, that the problem is the order of execution of the goroutines,
you can easily coordinate goroutine execution using channels by passing around the number of the
goroutine you want to run:
func coordinated(coord chan int, num, max int, work func()) {
for {
n := <-coord
if n == num {
work()
coord <- (n+1) % max
} else {
coord <- n
}
}
}
coord := make(chan int)
go coordinated(coord, 0, 3, func() { println("0"); time.Sleep(1 * time.Second) })
go coordinated(coord, 1, 3, func() { println("1"); time.Sleep(1 * time.Second) })
go coordinated(coord, 2, 3, func() { println("2"); time.Sleep(1 * time.Second) })
coord <- 0
or by using a central goroutine which executes the workers in a ordered manner:
func executor(funs chan func()) {
for {
worker := <-funs
worker()
funs <- worker
}
}
funs := make(chan func(), 3)
funs <- func() { println("0"); time.Sleep(1 * time.Second) }
funs <- func() { println("1"); time.Sleep(1 * time.Second) }
funs <- func() { println("2"); time.Sleep(1 * time.Second) }
go executor(funs)
These methods will, of course, remove all parallelism due to synchronization. However,
the concurrent aspect of your program remains.