mirror of https://github.com/panjf2000/ants.git
264 lines
8.4 KiB
Markdown
264 lines
8.4 KiB
Markdown
# ants
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<p align="center">
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<img src="https://user-images.githubusercontent.com/7496278/51748488-8efd2600-20e7-11e9-91f5-1c5b466dcca1.jpg"/>
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A goroutine pool for Go
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<br/><br/>
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<a title="Build Status" target="_blank" href="https://travis-ci.com/panjf2000/ants"><img src="https://img.shields.io/travis/com/panjf2000/ants?style=flat-square"></a>
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<a title="Codecov" target="_blank" href="https://codecov.io/gh/panjf2000/ants"><img src="https://img.shields.io/codecov/c/github/panjf2000/ants?style=flat-square"></a>
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<a title="Version" target="_blank" href="https://github.com/panjf2000/ants/releases"><img src="https://img.shields.io/github/tag-pre/panjf2000/ants?style=flat-square"></a>
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<a title="License" target="_blank" href="https://opensource.org/licenses/mit-license.php"><img src="https://img.shields.io/aur/license/pac?style=flat-square"></a>
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<br/>
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<a title="Go Report Card" target="_blank" href="https://goreportcard.com/report/github.com/panjf2000/ants"><img src="https://goreportcard.com/badge/github.com/panjf2000/ants"></a>
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<a title="Godoc for ants" target="_blank" href="https://godoc.org/github.com/panjf2000/ants"><img src="https://godoc.org/github.com/panjf2000/ants?status.svg"></a>
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</p>
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[中文](README_ZH.md) | [Project Blog](https://taohuawu.club/high-performance-implementation-of-goroutine-pool)
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Library `ants` implements a goroutine pool with fixed capacity, managing and recycling a massive number of goroutines, allowing developers to limit the number of goroutines in your concurrent programs.
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## Features:
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- Automatically managing and recycling a massive number of goroutines.
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- Periodically purging overdue goroutines.
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- Friendly interfaces: submitting tasks, getting the number of running goroutines, tuning capacity of pool dynamically, closing pool.
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- Handle panic gracefully to prevent programs from crash.
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- Efficient in memory usage and it even achieves higher performance than unlimited goroutines in golang.
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## Tested in the following Golang versions:
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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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- 1.12.x
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## How to install
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``` sh
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go get -u github.com/panjf2000/ants
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```
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Or, using glide:
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``` sh
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glide get github.com/panjf2000/ants
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```
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## How to use
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Just take a imagination that your program starts a massive number of goroutines, from which a vast amount of memory will be consumed. To mitigate that kind of situation, all you need to do is to import `ants` package and submit all your tasks to a default pool with fixed capacity, activated when package `ants` is imported:
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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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"time"
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"github.com/panjf2000/ants"
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)
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var sum int32
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func myFunc(i interface{}) {
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n := i.(int32)
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atomic.AddInt32(&sum, n)
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fmt.Printf("run with %d\n", n)
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}
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func demoFunc() {
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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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defer ants.Release()
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runTimes := 1000
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// Use the common pool.
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var wg sync.WaitGroup
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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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for i := 0; i < runTimes; i++ {
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wg.Add(1)
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ants.Submit(syncCalculateSum)
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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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// Use the pool with a function,
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// set 10 to the capacity of goroutine pool and 1 second for expired duration.
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p, _ := ants.NewPoolWithFunc(10, func(i interface{}) {
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myFunc(i)
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wg.Done()
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})
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defer p.Release()
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// Submit tasks one by one.
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for i := 0; i < runTimes; i++ {
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wg.Add(1)
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p.Invoke(int32(i))
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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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```
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## Integrate with http server
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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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type Request struct {
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Param []byte
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Result chan []byte
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}
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func main() {
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pool, _ := ants.NewPoolWithFunc(100, func(payload interface{}) {
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request, ok := payload.(*Request)
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if !ok {
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return
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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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}(request.Param)
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request.Result <- reverseParam
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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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param, err := ioutil.ReadAll(r.Body)
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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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request := &Request{Param: param, Result: make(chan []byte)}
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// Throttle the requests traffic with ants pool. This process is asynchronous and
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// you can receive a result from the channel defined outside.
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if err := pool.Invoke(request); err != nil {
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http.Error(w, "throttle limit error", http.StatusInternalServerError)
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}
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w.Write(<-request.Result)
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})
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http.ListenAndServe(":8080", nil)
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}
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```
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## Submit tasks
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Tasks can be submitted by calling `ants.Submit(func())`
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```go
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ants.Submit(func(){})
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```
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## Customize limited pool
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`ants` also supports customizing the capacity of pool. You can invoke the `NewPool` function to instantiate a pool with a given capacity, as following:
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``` go
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// Set 10000 the size of goroutine pool
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p, _ := ants.NewPool(10000)
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// Submit a task
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p.Submit(func(){})
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```
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## Tune pool capacity in runtime
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You can tune the capacity of `ants` pool in runtime with `Tune(int)`:
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``` go
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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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```
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Don't worry about the synchronous problems in this case, the function here is thread-safe (or should be called goroutine-safe).
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## Pre-malloc goroutine queue in pool
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`ants` allows you to pre-allocate memory of goroutine queue in pool, which may get a performance enhancement under some special certain circumstances such as the scenario that requires an pool with ultra-large capacity, meanwhile each task in goroutine lasts for a long time, in this case, pre-mallocing will reduce a lot of costs when re-slicing goroutine queue.
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```go
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// ants will pre-malloc the whole capacity of pool when you invoke this function
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p, _ := ants.NewPoolPreMalloc(AntsSize)
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```
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## Release Pool
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```go
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pool.Release()
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```
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## About sequence
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All tasks submitted to `ants` pool will not be guaranteed to be addressed in order, because those tasks scatter among a series of concurrent workers, thus those tasks would be executed concurrently.
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## Benchmarks
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```
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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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Go Version: 1.9
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```
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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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In that benchmark-picture, the first and second benchmarks performed test cases with 1M tasks and the rest of benchmarks performed test cases with 10M tasks, both in unlimited goroutines and `ants` pool, and the capacity of this `ants` goroutine-pool was limited to 50K.
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- BenchmarkGoroutine-4 represents the benchmarks with unlimited goroutines in golang.
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- BenchmarkPoolGroutine-4 represents the benchmarks with a `ants` pool.
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The test data above is a basic benchmark and more detailed benchmarks are about to be uploaded later.
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### Benchmarks with Pool
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In above benchmark picture, the first and second benchmarks performed test cases with 1M tasks and the rest of benchmarks performed test cases with 10M tasks, both in unlimited goroutines and `ants` pool, and the capacity of this `ants` goroutine-pool was limited to 50K.
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**As you can see, `ants` can up to 2x faster than goroutines without pool (10M tasks) and it only consumes half the memory comparing with goroutines without pool. (both 1M and 10M tasks)**
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### Benchmarks with PoolWithFunc
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### Throughput (it is suitable for scenarios where asynchronous tasks are submitted despite of the final results)
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#### 100K tasks
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#### 1M tasks
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#### 10M tasks
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### Performance Summary
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**In conclusion, `ants` can up to 2x~6x faster than goroutines without a pool and the memory consumption is reduced by 10 to 20 times.**
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