Concurrency Patterns

Worker Pool Pattern

A worker pool limits concurrency by spawning a fixed number of goroutines that process jobs from a shared channel:

func worker(id int, jobs <-chan int, results chan<- int) {
    for job := range jobs {
        fmt.Printf("Worker %d processing job %d\n", id, job)
        time.Sleep(time.Second) // Simulate work
        results <- job * 2
    }
}

func main() {
    jobs := make(chan int, 100)
    results := make(chan int, 100)

    // Start 3 workers
    for w := 1; w <= 3; w++ {
        go worker(w, jobs, results)
    }

    // Send 9 jobs
    for j := 1; j <= 9; j++ {
        jobs <- j
    }
    close(jobs)

    // Collect results
    for r := 1; r <= 9; r++ {
        fmt.Println(<-results)
    }
}

Pipeline Pattern

A pipeline chains stages where each stage is a goroutine reading from an input channel and writing to an output channel:

func generate(nums ...int) <-chan int {
    out := make(chan int)
    go func() {
        for _, n := range nums { out <- n }
        close(out)
    }()
    return out
}

func square(in <-chan int) <-chan int {
    out := make(chan int)
    go func() {
        for n := range in { out <- n * n }
        close(out)
    }()
    return out
}

// Pipeline: generate -> square -> print
for val := range square(generate(2, 3, 4)) {
    fmt.Println(val) // 4, 9, 16
}

Practice Exercises