2018-06-08 09:50:56 +03:00
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# ants
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2019-01-25 16:25:42 +03:00
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<div align="center"><img src="https://user-images.githubusercontent.com/7496278/51748488-8efd2600-20e7-11e9-91f5-1c5b466dcca1.jpg"/></div>
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2018-06-08 09:50:56 +03:00
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<p align="center">A goroutine pool for Go</p>
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2018-06-29 05:57:03 +03:00
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[![Build Status][1]][2]
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2018-07-16 07:25:25 +03:00
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[![codecov][3]][4]
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2018-06-29 05:57:03 +03:00
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[![goreportcard for panjf2000/ants][5]][6]
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2018-07-16 07:25:25 +03:00
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[![godoc for panjf2000/ants][7]][8]
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[![MIT Licence][9]][10]
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2018-06-08 09:50:56 +03:00
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2019-01-25 15:59:23 +03:00
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[英文](README.md) | [项目介绍文章传送门](http://blog.taohuawu.club/article/goroutine-pool)
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2018-06-08 09:50:56 +03:00
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`ants`是一个高性能的协程池,实现了对大规模goroutine的调度管理、goroutine复用,允许使用者在开发并发程序的时候限制协程数量,复用资源,达到更高效执行任务的效果。
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2019-01-26 21:07:33 +03:00
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## 功能:
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2018-06-08 09:50:56 +03:00
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- 实现了自动调度并发的goroutine,复用goroutine
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2018-07-09 11:36:42 +03:00
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- 定时清理过期的goroutine,进一步节省资源
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2018-06-08 09:50:56 +03:00
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- 提供了友好的接口:任务提交、获取运行中的协程数量、动态调整协程池大小
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2019-01-25 18:00:12 +03:00
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- 优雅处理panic,防止程序崩溃
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2018-06-08 09:50:56 +03:00
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- 资源复用,极大节省内存使用量;在大规模批量并发任务场景下比原生goroutine并发具有更高的性能
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2019-01-26 21:07:33 +03:00
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## 目前测试通过的Golang版本:
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- 1.8.x
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- 1.9.x
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- 1.10.x
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- 1.11.x
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- master
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2018-06-08 09:50:56 +03:00
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## 安装
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``` sh
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go get -u github.com/panjf2000/ants
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```
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使用包管理工具 glide 安装:
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``` sh
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glide get github.com/panjf2000/ants
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```
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## 使用
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写 go 并发程序的时候如果程序会启动大量的 goroutine ,势必会消耗大量的系统资源(内存,CPU),通过使用 `ants`,可以实例化一个协程池,复用 goroutine ,节省资源,提升性能:
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``` go
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package main
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import (
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"fmt"
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"sync"
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"sync/atomic"
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2018-07-02 09:45:25 +03:00
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"time"
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2018-06-08 09:50:56 +03:00
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"github.com/panjf2000/ants"
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)
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var sum int32
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2018-12-03 06:23:37 +03:00
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func myFunc(i interface{}) {
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2018-07-02 09:45:25 +03:00
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n := i.(int32)
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atomic.AddInt32(&sum, n)
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2018-06-08 09:50:56 +03:00
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fmt.Printf("run with %d\n", n)
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}
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2018-12-03 06:23:37 +03:00
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func demoFunc() {
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2018-06-08 09:50:56 +03:00
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time.Sleep(10 * time.Millisecond)
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fmt.Println("Hello World!")
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}
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func main() {
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2018-07-02 09:45:25 +03:00
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defer ants.Release()
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2018-06-08 09:50:56 +03:00
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runTimes := 1000
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2019-02-02 05:30:50 +03:00
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// Use the common pool.
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2018-06-08 09:50:56 +03:00
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var wg sync.WaitGroup
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2019-02-02 05:30:50 +03:00
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syncCalculateSum := func() {
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demoFunc()
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wg.Done()
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}
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2018-06-08 09:50:56 +03:00
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for i := 0; i < runTimes; i++ {
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wg.Add(1)
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2019-02-02 05:30:50 +03:00
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ants.Submit(syncCalculateSum)
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2018-06-08 09:50:56 +03:00
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}
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wg.Wait()
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fmt.Printf("running goroutines: %d\n", ants.Running())
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fmt.Printf("finish all tasks.\n")
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2018-12-06 19:33:43 +03:00
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// Use the pool with a function,
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2019-02-02 05:30:50 +03:00
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// set 10 to the capacity of goroutine pool and 1 second for expired duration.
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2018-12-01 14:41:02 +03:00
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p, _ := ants.NewPoolWithFunc(10, func(i interface{}) {
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2018-06-08 09:50:56 +03:00
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myFunc(i)
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wg.Done()
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})
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2018-07-02 09:45:25 +03:00
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defer p.Release()
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2019-02-02 05:30:50 +03:00
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// Submit tasks one by one.
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2018-06-08 09:50:56 +03:00
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for i := 0; i < runTimes; i++ {
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wg.Add(1)
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2018-07-02 09:45:25 +03:00
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p.Serve(int32(i))
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2018-06-08 09:50:56 +03:00
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}
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wg.Wait()
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fmt.Printf("running goroutines: %d\n", p.Running())
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fmt.Printf("finish all tasks, result is %d\n", sum)
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}
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2018-12-05 19:50:33 +03:00
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```
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2018-12-02 08:48:44 +03:00
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## 与http server集成
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```go
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package main
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import (
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"io/ioutil"
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"net/http"
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"github.com/panjf2000/ants"
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)
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2018-12-02 16:53:43 +03:00
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type Request struct {
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Param []byte
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Result chan []byte
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}
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2018-12-02 08:48:44 +03:00
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func main() {
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pool, _ := ants.NewPoolWithFunc(100, func(payload interface{}) {
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2018-12-03 05:13:53 +03:00
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request, ok := payload.(*Request)
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2018-12-02 08:48:44 +03:00
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if !ok {
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2018-12-03 09:31:49 +03:00
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return
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2018-12-02 08:48:44 +03:00
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}
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reverseParam := func(s []byte) []byte {
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for i, j := 0, len(s)-1; i < j; i, j = i+1, j-1 {
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s[i], s[j] = s[j], s[i]
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}
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return s
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2018-12-02 16:53:43 +03:00
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}(request.Param)
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2018-12-02 08:48:44 +03:00
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2018-12-02 16:53:43 +03:00
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request.Result <- reverseParam
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2018-12-02 08:48:44 +03:00
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})
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defer pool.Release()
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http.HandleFunc("/reverse", func(w http.ResponseWriter, r *http.Request) {
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2018-12-02 16:53:43 +03:00
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param, err := ioutil.ReadAll(r.Body)
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2018-12-02 08:48:44 +03:00
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if err != nil {
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http.Error(w, "request error", http.StatusInternalServerError)
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}
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defer r.Body.Close()
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2018-12-03 05:13:53 +03:00
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request := &Request{Param: param, Result: make(chan []byte)}
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2018-12-02 16:53:43 +03:00
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2018-12-06 19:33:43 +03:00
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// Throttle the requests traffic with ants pool. This process is asynchronous and
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2018-12-02 08:48:44 +03:00
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// you can receive a result from the channel defined outside.
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2018-12-02 16:53:43 +03:00
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if err := pool.Serve(request); err != nil {
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2018-12-02 08:48:44 +03:00
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http.Error(w, "throttle limit error", http.StatusInternalServerError)
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}
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2018-12-02 16:53:43 +03:00
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w.Write(<-request.Result)
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2018-12-02 08:48:44 +03:00
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})
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http.ListenAndServe(":8080", nil)
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}
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2018-06-08 09:50:56 +03:00
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```
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## 任务提交
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提交任务通过调用 `ants.Submit(func())`方法:
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```go
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2018-12-02 08:48:44 +03:00
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ants.Submit(func(){})
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2018-06-08 09:50:56 +03:00
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```
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## 自定义池
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`ants`支持实例化使用者自己的一个 Pool ,指定具体的池容量;通过调用 `NewPool` 方法可以实例化一个新的带有指定容量的 Pool ,如下:
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``` go
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2018-12-06 19:33:43 +03:00
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// Set 10000 the size of goroutine pool
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2018-07-24 16:53:34 +03:00
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p, _ := ants.NewPool(10000)
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2018-12-06 19:33:43 +03:00
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// Submit a task
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2018-12-02 08:48:44 +03:00
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p.Submit(func(){})
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2018-06-08 09:50:56 +03:00
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```
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## 动态调整协程池容量
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2019-01-26 19:05:51 +03:00
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需要动态调整协程池容量可以通过调用`Tune(int)`:
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2018-06-08 09:50:56 +03:00
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``` go
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2019-01-26 19:05:51 +03:00
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pool.Tune(1000) // Tune its capacity to 1000
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pool.Tune(100000) // Tune its capacity to 100000
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2018-06-08 09:50:56 +03:00
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```
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该方法是线程安全的。
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2019-01-26 19:05:51 +03:00
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## 销毁协程池
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```go
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pool.Release()
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```
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2018-06-08 09:50:56 +03:00
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## Benchmarks
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系统参数:
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```
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2019-01-26 21:07:33 +03:00
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OS: macOS High Sierra
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Processor: 2.7 GHz Intel Core i5
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Memory: 8 GB 1867 MHz DDR3
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2018-07-06 15:39:23 +03:00
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2019-01-26 21:07:33 +03:00
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Go Version: 1.9
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2018-06-08 09:50:56 +03:00
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```
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2019-01-22 09:31:45 +03:00
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<div align="center"><img src="https://user-images.githubusercontent.com/7496278/51515466-c7ce9e00-1e4e-11e9-89c4-bd3785b3c667.png"/></div>
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2018-06-08 09:50:56 +03:00
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上图中的前两个 benchmark 测试结果是基于100w任务量的条件,剩下的几个是基于1000w任务量的测试结果,`ants`的默认池容量是5w。
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- BenchmarkGoroutine-4 代表原生goroutine
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- BenchmarkPoolGroutine-4 代表使用协程池`ants`
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### Benchmarks with Pool
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2019-01-22 09:31:45 +03:00
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![](https://user-images.githubusercontent.com/7496278/51515499-f187c500-1e4e-11e9-80e5-3df8f94fa70f.png)
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2018-06-08 09:50:56 +03:00
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2018-06-28 17:27:53 +03:00
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**这里为了模拟大规模goroutine的场景,两次测试的并发次数分别是100w和1000w,前两个测试分别是执行100w个并发任务不使用Pool和使用了`ants`的Goroutine Pool的性能,后两个则是1000w个任务下的表现,可以直观的看出在执行速度和内存使用上,`ants`的Pool都占有明显的优势。100w的任务量,使用`ants`,执行速度与原生goroutine相当甚至略快,但只实际使用了不到5w个goroutine完成了全部任务,且内存消耗仅为原生并发的40%;而当任务量达到1000w,优势则更加明显了:用了70w左右的goroutine完成全部任务,执行速度比原生goroutine提高了100%,且内存消耗依旧保持在不使用Pool的40%左右。**
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2018-06-08 09:50:56 +03:00
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### Benchmarks with PoolWithFunc
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2019-01-22 09:31:45 +03:00
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![](https://user-images.githubusercontent.com/7496278/51515565-1e3bdc80-1e4f-11e9-8a08-452ab91d117e.png)
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2018-06-08 09:50:56 +03:00
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2018-06-28 17:27:53 +03:00
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**因为`PoolWithFunc`这个Pool只绑定一个任务函数,也即所有任务都是运行同一个函数,所以相较于`Pool`对原生goroutine在执行速度和内存消耗的优势更大,上面的结果可以看出,执行速度可以达到原生goroutine的300%,而内存消耗的优势已经达到了两位数的差距,原生goroutine的内存消耗达到了`ants`的35倍且原生goroutine的每次执行的内存分配次数也达到了`ants`45倍,1000w的任务量,`ants`的初始分配容量是5w,因此它完成了所有的任务依旧只使用了5w个goroutine!事实上,`ants`的Goroutine Pool的容量是可以自定义的,也就是说使用者可以根据不同场景对这个参数进行调优直至达到最高性能。**
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2018-06-28 05:52:20 +03:00
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2018-12-05 19:26:28 +03:00
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### 吞吐量测试(适用于那种只管提交异步任务而无须关心结果的场景)
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2018-06-08 09:50:56 +03:00
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#### 10w 任务量
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2019-01-22 09:31:45 +03:00
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![](https://user-images.githubusercontent.com/7496278/51515590-36abf700-1e4f-11e9-91e4-7bd3dcb5f4a5.png)
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2018-06-08 09:50:56 +03:00
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#### 100w 任务量
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2019-01-22 09:31:45 +03:00
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![](https://user-images.githubusercontent.com/7496278/51515596-44617c80-1e4f-11e9-89e3-01e19d2979a1.png)
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2018-06-08 09:50:56 +03:00
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#### 1000w 任务量
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2019-02-19 06:28:13 +03:00
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![](https://user-images.githubusercontent.com/7496278/52987732-537c2000-3437-11e9-86a6-177f00d7a1d6.png)
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2018-06-08 09:50:56 +03:00
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2019-02-19 06:28:13 +03:00
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### 性能小结
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2019-02-19 06:58:05 +03:00
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![](https://user-images.githubusercontent.com/7496278/52989187-4104e500-343d-11e9-880f-9641eec436ca.gif)
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2018-06-08 09:50:56 +03:00
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2018-12-05 19:50:33 +03:00
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**从该demo测试吞吐性能对比可以看出,使用`ants`的吞吐性能相较于原生goroutine可以保持在2-6倍的性能压制,而内存消耗则可以达到10-20倍的节省优势。**
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2018-06-28 05:52:20 +03:00
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2019-01-26 22:17:40 +03:00
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[1]: https://travis-ci.com/panjf2000/ants.svg?branch=master
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2018-06-29 05:57:03 +03:00
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[2]: https://travis-ci.com/panjf2000/ants
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2019-01-26 22:17:40 +03:00
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[3]: https://codecov.io/gh/panjf2000/ants/branch/master/graph/badge.svg
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2018-07-16 07:25:25 +03:00
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[4]: https://codecov.io/gh/panjf2000/ants
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2018-06-29 05:57:03 +03:00
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[5]: https://goreportcard.com/badge/github.com/panjf2000/ants
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[6]: https://goreportcard.com/report/github.com/panjf2000/ants
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2018-07-16 07:25:25 +03:00
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[7]: https://godoc.org/github.com/panjf2000/ants?status.svg
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[8]: https://godoc.org/github.com/panjf2000/ants
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[9]: https://badges.frapsoft.com/os/mit/mit.svg?v=103
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[10]: https://opensource.org/licenses/mit-license.php
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