ants

A goroutine pool for Go

中文 | Project Tutorial

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

Features:

• Automatically managing and recycling a massive number of goroutines.
• Periodically purging overdue goroutines.
• Friendly interfaces: submitting tasks, getting the number of running goroutines, readjusting capacity of pool dynamically, closing pool.
• Handle panic gracefully to prevent programs from crash.
• 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

Just take a imagination that your program startovers a massive number of goroutines, from which a vast amount of memory will be consumed. To mitigate that kind of thing, all you need to do is to import ants package and submit all your tasks to a default pool with fixed capacity created when ants has been 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

	// Use 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")

	// Use the pool with a function,
	// set 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()
	// Submit 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)}

		// Throttle the requests traffic 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(){})

Customize limited pool

ants also supports customizing the capacity of pool. You can call the NewPool function to instantiate a pool with a given capacity, as following:

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

Tune pool capacity

You can tune the capacity of ants pool at any time with Tune(int):

pool.Tune(1000) // Tune its capacity to 1000
pool.Tune(100000) // Tune its capacity to 100000

Don't worry about the synchronous problems in this case, the function here is thread-safe (or should be called goroutine-safe).

Release Pool

pool.Release()

About sequence

All the 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 are executed 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 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.

• 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 more detailed benchmarks are about to be uploaded later.

Benchmarks with Pool

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.

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)

Benchmarks with PoolWithFunc

Throughput (it is suitable for scenarios where asynchronous tasks are submitted despite of the final results)

100K tasks

1M tasks

10M tasks

There was only the test case with ants pool because my program crashed when it reached 10M goroutines without using a pool.

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.