ants/README.md

6.6 KiB

ants

A goroutine pool for Go

Build Status codecov goreportcard for panjf2000/ants godoc for panjf2000/ants MIT Licence

中文项目说明 | Project Tutorial

Package ants implements a fixed goroutine pool for managing and recycling a massive number of goroutines, allowing developers to limit the number of goroutines that created by your concurrent programs.

Features:

  • Automatically managing and recycling a massive number of goroutines.
  • Periodically clearing overdue goroutines.
  • Friendly interfaces: submitting tasks, getting the number of running goroutines, readjusting capacity of pool dynamically, closing pool.
  • Efficient in memory usage and it even achieves higher performance than unlimited goroutines in golang.

How to install

go get -u github.com/panjf2000/ants

Or, using glide:

glide get github.com/panjf2000/ants

How to use

If your program will generate a massive number of goroutines and you don't want them to consume a vast amount of memory, with ants, all you need to do is to import ants package and submit all your tasks to the default limited pool created when ants was imported:

package main

import (
	"fmt"
	"sync"
	"sync/atomic"
	"time"

	"github.com/panjf2000/ants"
)

var sum int32

func myFunc(i interface{}) {
	n := i.(int32)
	atomic.AddInt32(&sum, n)
	fmt.Printf("run with %d\n", n)
}

func demoFunc() {
	time.Sleep(10 * time.Millisecond)
	fmt.Println("Hello World!")
}

func main() {
	defer ants.Release()

	runTimes := 1000

	// Uses the common pool
	var wg sync.WaitGroup
	for i := 0; i < runTimes; i++ {
		wg.Add(1)
		ants.Submit(func() {
			demoFunc()
			wg.Done()
		})
	}
	wg.Wait()
	fmt.Printf("running goroutines: %d\n", ants.Running())
	fmt.Printf("finish all tasks.\n")

	// Uses the pool with a function,
	// sets 10 to the size of goroutine pool and 1 second for expired duration
	p, _ := ants.NewPoolWithFunc(10, func(i interface{}) {
		myFunc(i)
		wg.Done()
	})
	defer p.Release()
	// Submits tasks
	for i := 0; i < runTimes; i++ {
		wg.Add(1)
		p.Serve(int32(i))
	}
	wg.Wait()
	fmt.Printf("running goroutines: %d\n", p.Running())
	fmt.Printf("finish all tasks, result is %d\n", sum)
}

Integrate with http server

package main

import (
	"io/ioutil"
	"net/http"

	"github.com/panjf2000/ants"
)

type Request struct {
	Param  []byte
	Result chan []byte
}

func main() {
	pool, _ := ants.NewPoolWithFunc(100, func(payload interface{}) {
		request, ok := payload.(*Request)
		if !ok {
			return
		}
		reverseParam := func(s []byte) []byte {
			for i, j := 0, len(s)-1; i < j; i, j = i+1, j-1 {
				s[i], s[j] = s[j], s[i]
			}
			return s
		}(request.Param)

		request.Result <- reverseParam
	})
	defer pool.Release()

	http.HandleFunc("/reverse", func(w http.ResponseWriter, r *http.Request) {
		param, err := ioutil.ReadAll(r.Body)
		if err != nil {
			http.Error(w, "request error", http.StatusInternalServerError)
		}
		defer r.Body.Close()

		request := &Request{Param: param, Result: make(chan []byte)}

		// Throttles the requests with ants pool. This process is asynchronous and
		// you can receive a result from the channel defined outside.
		if err := pool.Serve(request); err != nil {
			http.Error(w, "throttle limit error", http.StatusInternalServerError)
		}

		w.Write(<-request.Result)
	})

	http.ListenAndServe(":8080", nil)
}

Submit tasks

Tasks can be submitted by calling ants.Submit(func())

ants.Submit(func(){})

Custom limited pool

Ants also supports custom limited pool. You can use the NewPool method to create a pool with the given capacity, as following:

// Sets 10000 the size of goroutine pool
p, _ := ants.NewPool(10000)
// Submits a task
p.Submit(func(){})

Tuning pool capacity

You can change ants pool capacity at any time with ReSize(int):

pool.ReSize(1000) // Tunes its capacity to 1000
pool.ReSize(100000) // Tunes its capacity to 100000

Don't worry about the synchronous problems in this case, this method is thread-safe.

About sequence

All the tasks submitted to ants pool will not be guaranteed to be processed in order, because those tasks distribute among a series of concurrent workers, thus those tasks are processed concurrently.

Benchmarks

OS : macOS High Sierra
Processor : 2.7 GHz Intel Core i5
Memory : 8 GB 1867 MHz DDR3

Go1.9

In that benchmark-picture, the first and second benchmarks performed test with 1M tasks and the rest of benchmarks performed test with 10M tasks, both unlimited goroutines and ants pool, and the capacity of this ants goroutine-pool was limited to 50K.

  • BenchmarkGoroutine-4 represents the benchmarks with unlimited goroutines in golang.

  • BenchmarkPoolGroutine-4 represents the benchmarks with a ants pool.

The test data above is a basic benchmark and the more detailed benchmarks will be uploaded later.

Benchmarks with Pool

In that benchmark-picture, the first and second benchmarks performed test with 1M tasks and the rest of benchmarks performed test with 10M tasks, both unlimited goroutines and ants pool, and the capacity of this ants goroutine-pool was limited to 50K.

As you can see, ants can up to 2x faster than goroutines without pool (10M tasks) and it only consumes half memory comparing with goroutines without pool. (both 1M and 10M tasks)

Benchmarks with PoolWithFunc

Throughput (it is suitable for scenarios where asynchronous tasks are submitted without concern for results)

100K tasks

1M tasks

10M tasks

There was only the test of ants Pool because my computer was crash when it reached 10M goroutines without pool.

As you can see, ants can up to 2x~6x faster than goroutines without pool and the memory consumption is reduced by 10 to 20 times.