golang线程池ants-四种使用方法

目录

1、ants介绍

2、使用方式汇总

3、各种使用方式详解

3.1 默认池

3.2 普通模式

3.3 带参函数

3.4 多池多协程

4、总结

---

1、ants介绍

      众所周知，goroutine相比于线程来说，更加轻量、资源占用更少、无线程上下文切换等优势，但是也不能无节制的创建使用，如果系统中开启的goroutine过多而没有及时回收，也会造成系统内存资源耗尽。

      ants是一款高性能的协程管理池，实现了协程的创建、缓存、复用、刷新、停止等功能，同时允许开发者设置线程池中worker的数量、线程池本身的个数以及workder中的任务，从而实现更加高效的运行效果。

github：GitHub - panjf2000/ants: ants is a high-performance and low-cost goroutine pool in Go./ ants 是一个高性能且低损耗的 goroutine 池。

2、使用方式汇总

ants的使用有四种方式，分别如下：

这四种使用方式，前两种最常用，基本能满足日常系统的开发需要，第四种默认池，简单的场景也可以用，但不推荐，多池的情况还没想到特别合适的应用场景。

3、各种使用方式详解

3.1 默认池

ants在启动时，会默认初始化一个协程池，这部分代码位于ants.go文件中：

var (
	// ErrLackPoolFunc will be returned when invokers don't provide function for pool.
	ErrLackPoolFunc = errors.New("must provide function for pool")

	// ErrInvalidPoolExpiry will be returned when setting a negative number as the periodic duration to purge goroutines.
	ErrInvalidPoolExpiry = errors.New("invalid expiry for pool")

	// ErrPoolClosed will be returned when submitting task to a closed pool.
	ErrPoolClosed = errors.New("this pool has been closed")

	// ErrPoolOverload will be returned when the pool is full and no workers available.
	ErrPoolOverload = errors.New("too many goroutines blocked on submit or Nonblocking is set")

	// ErrInvalidPreAllocSize will be returned when trying to set up a negative capacity under PreAlloc mode.
	ErrInvalidPreAllocSize = errors.New("can not set up a negative capacity under PreAlloc mode")

	// ErrTimeout will be returned after the operations timed out.
	ErrTimeout = errors.New("operation timed out")

	// ErrInvalidPoolIndex will be returned when trying to retrieve a pool with an invalid index.
	ErrInvalidPoolIndex = errors.New("invalid pool index")

	// ErrInvalidLoadBalancingStrategy will be returned when trying to create a MultiPool with an invalid load-balancing strategy.
	ErrInvalidLoadBalancingStrategy = errors.New("invalid load-balancing strategy")

	// workerChanCap determines whether the channel of a worker should be a buffered channel
	// to get the best performance. Inspired by fasthttp at
	// https://github.com/valyala/fasthttp/blob/master/workerpool.go#L139
	workerChanCap = func() int {
		// Use blocking channel if GOMAXPROCS=1.
		// This switches context from sender to receiver immediately,
		// which results in higher performance (under go1.5 at least).
		if runtime.GOMAXPROCS(0) == 1 {
			return 0
		}

		// Use non-blocking workerChan if GOMAXPROCS>1,
		// since otherwise the sender might be dragged down if the receiver is CPU-bound.
		return 1
	}()

	// log.Lmsgprefix is not available in go1.13, just make an identical value for it.
	logLmsgprefix = 64
	defaultLogger = Logger(log.New(os.Stderr, "[ants]: ", log.LstdFlags|logLmsgprefix|log.Lmicroseconds))

	// Init an instance pool when importing ants.
	defaultAntsPool, _ = NewPool(DefaultAntsPoolSize)
)

使用起来就比较简单了，直接往池子里提交任务即可。

package main

import (
	"fmt"
	"sync"
	"time"

	"github.com/panjf2000/ants/v2"
)

func add(d int) {
	sum := 0
	for i := 0; i < d; i++ {
		sum += i
	}
}
func main() {
	var wg sync.WaitGroup
	now := time.Now()
	for i := 0; i < 5; i++ {
		wg.Add(1)
		ants.Submit(func() {
			add(10000000000)
			wg.Done()
		})
	}
	wg.Wait()
	fmt.Println(time.Since(now))
	now = time.Now()
	for i := 0; i < 5; i++ {
		add(10000000000)
	}
	fmt.Println(time.Since(now))
}

运行结果：

3.2 普通模式

普通模式和使用默认池非常类似，但是需要自己创建一个线程池：

p, _ := ants.NewPool(5)

函数参数为协程池协程个数，测试代码如下：

package main

import (
	"fmt"
	"sync"
	"time"

	"github.com/panjf2000/ants/v2"
)

func add(d int) {
	sum := 0
	for i := 0; i < d; i++ {
		sum += i
	}
}
func main() {
	var wg sync.WaitGroup
	now := time.Now()
	p, _ := ants.NewPool(5)
	for i := 0; i < 5; i++ {
		wg.Add(1)
		p.Submit(func() {
			add(10000000000)
			wg.Done()
		})
	}
	wg.Wait()
	fmt.Println("协程池运行：", time.Since(now))
	now = time.Now()
	for i := 0; i < 5; i++ {
		add(10000000000)
	}
	fmt.Println("循环运行：", time.Since(now))
}

3.3 带参函数

带参函数，重点是往worker中传递函数执行的参数，每个workder中都是同一个执行函数。

package main

import (
	"fmt"
	"sync"
	"time"

	"github.com/panjf2000/ants/v2"
)

func add(d int) {
	sum := 0
	for i := 0; i < d; i++ {
		sum += i
	}
	fmt.Println("the sum is: ", sum)
}
func main() {
	var wg sync.WaitGroup
	now := time.Now()
	p, _ := ants.NewPoolWithFunc(5, func(i interface{}) {
		add(i.(int))
		wg.Done()
	})
	for i := 0; i < 5; i++ {
		wg.Add(1)
		p.Invoke(1000000000)
	}
	wg.Wait()
	fmt.Println("循环运行：", time.Since(now))
}

运行结果：

liupeng@liupengdeMacBook-Pro ants_study % go run thread_default.go
the sum is:  499999999500000000
the sum is:  499999999500000000
the sum is:  499999999500000000
the sum is:  499999999500000000
the sum is:  499999999500000000
循环运行： 352.447333ms

3.4 多池多协程

这种模式，就是声明了多个协程池，每个池子里有多个协程在跑。

package main

import (
	"fmt"
	"sync"
	"time"

	"github.com/panjf2000/ants/v2"
)

func add(d int) {
	sum := 0
	for i := 0; i < d; i++ {
		sum += i
	}
	fmt.Println("the sum is: ", sum)
}
func main() {
	var wg sync.WaitGroup
	runTimes := 20
	now := time.Now()
	mpf, _ := ants.NewMultiPoolWithFunc(10, runTimes/10, func(i interface{}) {
		add(i.(int))
		wg.Done()
	}, ants.LeastTasks)
	for i := 0; i < runTimes; i++ {
		wg.Add(1)
		mpf.Invoke(1000000000)
	}
	wg.Wait()
	fmt.Println("循环运行：", time.Since(now))
}

运行记录：

4、总结

     以上就是ants协程池所有的使用方式，3.2、3.3章节介绍的两种方式比较常用，也是推荐的使用方式，使用协程池，可以有效的控制系统硬件资源的使用，防止机器被打满，对于高并发服务非常推荐使用。

      后面会学习一下ants的源码，并整理成文档发出来，欢迎围观。