Here is an example using the sync.WaitGroup
to do what you are looking for,
This example accepts a lenghty list of integers, then sums them all up by handing N parallel workers an equal-sized chunk of the input data. It can be run on go playground:
package main
import (
"fmt"
"sync"
)
const WorkerCount = 10
func main() {
// Some input data to operate on.
// Each worker gets an equal share to work on.
data := make([]int, WorkerCount*10)
for i := range data {
data[i] = i
}
// Sum all the entries.
result := sum(data)
fmt.Printf("Sum: %d\n", result)
}
// sum adds up the numbers in the given list, by having the operation delegated
// to workers operating in parallel on sub-slices of the input data.
func sum(data []int) int {
var sum int
result := make(chan int)
defer close(result)
// Accumulate results from workers.
go func() {
for {
select {
case value := <-result:
sum += value
}
}
}()
// The WaitGroup will track completion of all our workers.
wg := new(sync.WaitGroup)
wg.Add(WorkerCount)
// Divide the work up over the number of workers.
chunkSize := len(data) / WorkerCount
// Spawn workers.
for i := 0; i < WorkerCount; i++ {
go func(i int) {
offset := i * chunkSize
worker(result, data[offset:offset+chunkSize])
wg.Done()
}(i)
}
// Wait for all workers to finish, before returning the result.
wg.Wait()
return sum
}
// worker sums up the numbers in the given list.
func worker(result chan int, data []int) {
var sum int
for _, v := range data {
sum += v
}
result <- sum
}