In this example we'll look at how to implement a _worker pool_ using goroutines and channels. | ||
package main |
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import ( |
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"fmt" |
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"time" |
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) |
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Here's the worker, of which we'll run several concurrent instances. These workers will receive work on the `jobs` channel and send the corresponding results on `results`. We'll sleep a second per job to simulate an expensive task. | func worker(id int, jobs <-chan int, results chan<- int) { |
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for j := range jobs { |
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fmt.Println("worker", id, "started job", j) |
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time.Sleep(time.Second) |
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fmt.Println("worker", id, "finished job", j) |
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results <- j * 2 |
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} |
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} |
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func main() { |
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In order to use our pool of workers we need to send them work and collect their results. We make 2 channels for this. | const numJobs = 5 |
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jobs := make(chan int, numJobs) |
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results := make(chan int, numJobs) |
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This starts up 3 workers, initially blocked because there are no jobs yet. | for w := 1; w <= 3; w++ { |
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go worker(w, jobs, results) |
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} |
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Here we send 5 `jobs` and then `close` that channel to indicate that's all the work we have. | for j := 1; j <= numJobs; j++ { |
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jobs <- j |
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} |
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close(jobs) |
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Finally we collect all the results of the work. This also ensures that the worker goroutines have finished. An alternative way to wait for multiple goroutines is to use a [WaitGroup](waitgroups). | for a := 1; a <= numJobs; a++ { |
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<-results |
worker 3 started job 1 worker 2 started job 3 worker 1 started job 2 worker 1 finished job 2 worker 1 started job 4 worker 2 finished job 3 worker 2 started job 5 worker 3 finished job 1 worker 1 finished job 4 worker 2 finished job 5 |
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} |
worker 2 started job 3 worker 2 started job 4 worker 1 finished job 2 worker 1 started job 5 worker 2 finished job 4 worker 1 finished job 5 |
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} |
worker 1 started job 2 worker 3 started job 5 worker 1 finished job 2 worker 3 finished job 5 |