Worker Pools

In this example we’ll look at how to implement a worker pool using goroutines and channels.

package main

import (
    "fmt"
    "time"
)

// 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) {
    for j := range jobs {
        fmt.Println("worker", id, "started  job", j)
        time.Sleep(time.Second)
        fmt.Println("worker", id, "finished job", j)
        results <- j * 2
    }
}

func main() {

    // 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
    jobs := make(chan int, numJobs)
    results := make(chan int, numJobs)

    // This starts up 3 workers, initially blocked because there are no jobs yet.
    for w := 1; w <= 3; w++ {
        go worker(w, jobs, results)
    }

    // 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++ {
        jobs <- j
    }
    close(jobs)

    // 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.
    for a := 1; a <= numJobs; a++ {
        <-results
    }
}

Our running program shows the 5 jobs being executed by various workers. The program only takes about 2 seconds despite doing about 5 seconds of total work because there are 3 workers operating concurrently.

$ time go run worker-pools.go 
worker 1 started  job 1
worker 2 started  job 2
worker 3 started  job 3
worker 1 finished job 1
worker 1 started  job 4
worker 2 finished job 2
worker 2 started  job 5
worker 3 finished job 3
worker 1 finished job 4
worker 2 finished job 5
real    0m2.358s