下面是Stuff类型的结构。它有三个整数。 Number
,Double
及其Power
。让我们假装计算一个给定的int列表的双重和幂是一个昂贵的计算。
type Stuff struct {
Number int
Double int
Power int
}
func main() {
nums := []int{2, 3, 4} // given numbers
stuff := []Stuff{} // struct of stuff with transformed ints
double := make(chan int)
power := make(chan int)
for _, i := range nums {
go doubleNumber(i, double)
go powerNumber(i, power)
}
// How do I get the values back in the right order?
fmt.Println(stuff)
}
func doubleNumber(i int, c chan int) {
c <- i + i
}
func powerNumber(i int, c chan int) {
c <- i * i
}
fmt.Println(stuff)
的结果应该与初始化的内容相同:
stuff := []Stuff{
{Number: 2, Double: 4, Power: 4}
{Number: 3, Double: 6, Power: 9}
{Number: 4, Double: 8, Power: 16}
}
我知道我可以使用<- double
和<- power
来收集频道中的值,但我不知道双/权力属于哪些数字。
答案 0 :(得分:6)
Goroutines独立运行,因此如果没有明确的同步,您就无法预测执行和完成顺序。实际上,您不能将返回的数字与输入数字配对。
您可以返回更多数据(例如输入数字和输出,例如包裹在结构中),或者将指针传递给工作者函数(作为新的goroutines启动),例如: *Stuff
并让goroutines填充Stuff
本身的计算数据。
我将使用chan Pair
所在的频道类型Pair
:
type Pair struct{ Number, Result int }
所以计算将如下所示:
func doubleNumber(i int, c chan Pair) { c <- Pair{i, i + i} }
func powerNumber(i int, c chan Pair) { c <- Pair{i, i * i} }
我将使用map[int]*Stuff
,因为可收集的数据来自多个渠道(double
和power
),我想轻松快速地找到合适的Stuff
(指针是必需的,所以我也可以在地图&#34;)中修改它。
所以主要功能:
nums := []int{2, 3, 4} // given numbers
stuffs := map[int]*Stuff{}
double := make(chan Pair)
power := make(chan Pair)
for _, i := range nums {
go doubleNumber(i, double)
go powerNumber(i, power)
}
// How do I get the values back in the right order?
for i := 0; i < len(nums)*2; i++ {
getStuff := func(number int) *Stuff {
s := stuffs[number]
if s == nil {
s = &Stuff{Number: number}
stuffs[number] = s
}
return s
}
select {
case p := <-double:
getStuff(p.Number).Double = p.Result
case p := <-power:
getStuff(p.Number).Power = p.Result
}
}
for _, v := range nums {
fmt.Printf("%+v\n", stuffs[v])
}
输出(在Go Playground上尝试):
&{Number:2 Double:4 Power:4}
&{Number:3 Double:6 Power:9}
&{Number:4 Double:8 Power:16}
由于我们现在正在传递*Stuff
值,我们可以预先填写&#34; Stuff
本身的输入数字。
但必须小心,只能通过适当的同步读/写值。最简单的是等待所有&#34;工人&#34; goroutines完成他们的工作。
var wg = &sync.WaitGroup{}
func main() {
nums := []int{2, 3, 4} // given numbers
stuffs := make([]Stuff, len(nums))
for i, n := range nums {
stuffs[i].Number = n
wg.Add(2)
go doubleNumber(&stuffs[i])
go powerNumber(&stuffs[i])
}
wg.Wait()
fmt.Printf("%+v", stuffs)
}
func doubleNumber(s *Stuff) {
defer wg.Done()
s.Double = s.Number + s.Number
}
func powerNumber(s *Stuff) {
defer wg.Done()
s.Power = s.Number * s.Number
}
输出(在Go Playground上尝试):
[{Number:2 Double:4 Power:4} {Number:3 Double:6 Power:9} {Number:4 Double:8 Power:16}]
答案 1 :(得分:1)
就个人而言,我会使用chan Stuff
重新传递结果,然后旋转计算完整Stuff
的goroutines并将其传回。如果您需要同时计算单个Stuff
的各个部分,则可以使用专用通道从每个goroutine生成goroutine。收集完所有结果后,您可以(可选)使用累计值对切片进行排序。
我在下面的意思示例(原则上,您可以使用sync.WaitGroup
协调事项,但如果输入计数已知,则严格来说不需要它。)
type Stuff struct {
number int64
double int64
square int64
}
// Compute a Stuff with individual computations in-line, send it out
func computeStuff(n int64, out chan<- Stuff) {
rv := Stuff{number: n}
rv.double = n * 2
rv.square = n * n
out <- rv
}
// Compute a Stuff with individual computations concurrent
func computeStuffConcurrent(n int64, out chan<- Stuff) {
rv := Stuff{number: n}
dc := make(chan int64)
sc := make(chan int64)
defer close(dc)
defer close(sc)
go double(n, dc)
go square(n, sc)
rv.double = <-dc
rv.square = <-sc
out <- rv
}
func double(n int64, result chan<- int) {
result <- n * 2
}
func square(n int64, result chan<- int) {
result <- n * n
}
func main() {
inputs := []int64{1, 2, 3}
results := []Stuff{}
resultChannel := make(chan Stuff)
for _, input := range inputs {
go computeStuff(input, resultChannel)
// Or the concurrent version, if the extra performance is needed
}
for c := 0; c < len(inputs); c++ {
results = append(results, <- resultChannel)
}
// We now have all results, sort them if you need them sorted
}
答案 2 :(得分:-1)
Ordered-concurrently 是一个 go 模块,它同时处理工作并按照提供的顺序返回数据。 https://github.com/tejzpr/ordered-concurrently
示例 - https://play.golang.org/p/hkcIuRHj63h
package main
import (
concurrently "github.com/tejzpr/ordered-concurrently/v2"
"log"
"math/rand"
"time"
)
type loadWorker int
// The work that needs to be performed
// The input type should implement the WorkFunction interface
func (w loadWorker) Run() interface{} {
time.Sleep(time.Millisecond * time.Duration(rand.Intn(10)))
return w
}
func main() {
max := 10
inputChan := make(chan concurrently.WorkFunction)
output := concurrently.Process(inputChan, &concurrently.Options{PoolSize: 10, OutChannelBuffer: 10})
go func() {
for work := 0; work < max; work++ {
inputChan <- loadWorker(work)
}
close(inputChan)
}()
for out := range output {
log.Println(out.Value)
}
}
免责声明:我是模块创建者