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超大规模并发的场景下,不加限制的大规模的goroutine可能造成内存暴涨,给机器带来极大的压力,吞吐量下降和处理速度变慢。 而实现一个Goroutine Pool,复用goroutine,减轻runtime的调度压力以及缓解内存压力,依托这些优化,在大规模goroutine并发的场景下可以极大地提高并发性能。
Pool类型type Pool struct { // capacity of the pool. //capacity是该Pool的容量,也就是开启worker数量的上限,每一个worker需要一个goroutine去执行; //worker类型为任务类。 capacity int32 // running is the number of the currently running goroutines. //running是当前正在执行任务的worker数量 running int32 // expiryDuration set the expired time (second) of every worker. //expiryDuration是worker的过期时长,在空闲队列中的worker的最新一次运行时间与当前时间之差如果大于这个值则表示已过期,定时清理任务会清理掉这个worker; expiryDuration time.Duration // workers is a slice that store the available workers. //任务队列 workers []*Worker // release is used to notice the pool to closed itself. //当关闭该Pool支持通知所有worker退出运行以防goroutine泄露 release chan sig // lock for synchronous operation //用以支持Pool的同步操作 lock sync.Mutex //once用在确保Pool关闭操作只会执行一次 once sync.Once } 初始化Pool// NewPool generates a instance of ants pool func NewPool(size, expiry int) (*Pool, error) { if size <= 0 { return nil, errors.New("Pool Size <0,not Create") } p := &Pool{ capacity: int32(size), release: make(chan sig, 1), expiryDuration: time.Duration(expiry) * time.Second, running: 0, } // 启动定期清理过期worker任务,独立goroutine运行, // 进一步节省系统资源 p.monitorAndClear() return p, nil } 获取Worker// getWorker returns a available worker to run the tasks. func (p *Pool) getWorker() *Worker { var w *Worker // 标志,表示当前运行的worker数量是否已达容量上限 waiting := false // 涉及从workers队列取可用worker,需要加锁 p.lock.Lock() workers := p.workers n := len(workers) - 1 fmt.Println("空闲worker数量:",n+1) fmt.Println("协程池现在运行的worker数量:",p.running) // 当前worker队列为空(无空闲worker) if n < 0 { //没有空闲的worker有两种可能: //1.运行的worker超出了pool容量 //2.当前是空pool,从未往pool添加任务或者一段时间内没有任务添加,被定期清除 // 运行worker数目已达到该Pool的容量上限,置等待标志 if p.running >= p.capacity { //print("超过上限") waiting = true } else { // 当前无空闲worker但是Pool还没有满, // 则可以直接新开一个worker执行任务 p.running++ w = &Worker{ pool: p, task: make(chan functinType), str:make(chan string), } } // 有空闲worker,从队列尾部取出一个使用 } else { //<-p.freeSignal w = workers[n] workers[n] = nil p.workers = workers[:n] p.running++ } // 判断是否有worker可用结束,解锁 p.lock.Unlock() if waiting { //当一个任务执行完以后会添加到池中,有了空闲的任务就可以继续执行: // 阻塞等待直到有空闲worker for len(p.workers) == 0{ continue } p.lock.Lock() workers = p.workers l := len(workers) - 1 w = workers[l] workers[l] = nil p.workers = workers[:l] p.running++ p.lock.Unlock() } return w } 定期清理过期Workerfunc (p *Pool) monitorAndClear() { go func() { for { // 周期性循环检查过期worker并清理 time.Sleep(p.expiryDuration) currentTime := time.Now() p.lock.Lock() idleWorkers := p.workers n := 0 for i, w := range idleWorkers { // 计算当前时间减去该worker的最后运行时间之差是否符合过期时长 if currentTime.Sub(w.recycleTime) <= p.expiryDuration { break } n = i w.stop() idleWorkers[i] = nil } if n > 0 { n++ p.workers = idleWorkers[n:] } p.lock.Unlock() } }() } 复用Worker// putWorker puts a worker back into free pool, recycling the goroutines. func (p *Pool) putWorker(worker *Worker) { // 写入回收时间,亦即该worker的最后运行时间 worker.recycleTime = time.Now() p.lock.Lock() p.running -- p.workers = append(p.workers, worker) p.lock.Unlock() } 动态扩容或者缩小容量// ReSize change the capacity of this pool func (p *Pool) ReSize(size int) { cap := int(p.capacity) if size < cap{ diff := cap - size for i := 0; i < diff; i++ { p.getWorker().stop() } } else if size == cap { return } atomic.StoreInt32(&p.capacity, int32(size)) } 提交Worker// Submit submit a task to pool func (p *Pool) Submit(task functinType,str string) error { if len(p.release) > 0 { return errors.New("Pool is Close") } //创建或得到一个空闲的worker w := p.getWorker() w.run() //将任务参数通过信道传递给它 w.sendarg(str) //将任务通过信道传递给它 w.sendTask(task) return nil }
Worker类package Poolpkg import ( "sync/atomic" "time" ) type functinType func(string) error // Worker is the actual executor who runs the tasks, // it starts a goroutine that accepts tasks and // performs function calls. type Worker struct { // pool who owns this worker. pool *Pool // task is a job should be done. task chan functinType // recycleTime will be update when putting a worker back into queue. recycleTime time.Time str chan string } // run starts a goroutine to repeat the process // that performs the function calls. func (w *Worker) run() { go func() { //监听任务列表,一旦有任务立马取出运行 count := 1 var str string var f functinType for count <=2{ select { case str_temp, ok := <- w.str: if !ok { return } count ++ str = str_temp case f_temp, ok := <-w.task: if !ok { //如果接收到关闭 atomic.AddInt32(&w.pool.running, -1) close(w.task) return } count ++ f = f_temp } } err := f(str) if err != nil{ //fmt.Println("执行任务失败") } //回收复用 w.pool.putWorker(w) return }() } // stop this worker. func (w *Worker) stop() { w.sendTask(nil) close(w.str) } // sendTask sends a task to this worker. func (w *Worker) sendTask(task functinType) { w.task <- task } func (w *Worker) sendarg(str string) { w.str <- str }
总结和实践怎么理解Woreker,task、Pool的关系Woker类型其实就是task的载体,Worker类型有两个很重要的参数: task chan functinType:用来是传递task。 str chan string:用来传递task所需的参数。 task是任务本身,它一般为一个函数,在程序中被定义为函数类型: type functinType func(string) error Pool存储Worker,当用户要执行一个task时,首先要得到一个Worker,必须从池中获取,获取到一个Worker后,就开启一个协程去处理,在这个协程中接收任务task和参数。 //创建或得到一个空闲的worker w := p.getWorker() Worker怎么接收task和参数count定义接收数据的个数,一个Woker必须接收到task和参数才能开始工作。 go func() { //监听任务列表,一旦有任务立马取出运行 count := 1 var str string var f functinType for count <=2{ select { case str_temp, ok := <- w.str: if !ok { return } count ++ str = str_temp case f_temp, ok := <-w.task: if !ok { //如果接收到关闭 atomic.AddInt32(&w.pool.running, -1) close(w.task) return } count ++ f = f_temp } } err := f(str) if err != nil{ //fmt.Println("执行任务失败") } //回收复用 w.pool.putWorker(w) return }() Pool怎么处理用户提交task获取Worker的请求1.先得到Pool池中空闲Worker的数量,然后判断 2.如果小于零,则表示池中没有空闲的Worker,这里有两种原因:
3.如果大于或者等于零,有空闲的Worker直接从池中获取最后一个Worker。 4.如果是第二种的第一种情况,则阻塞等待池中有空闲的Worker。 if waiting { //当一个任务执行完以后会添加到池中,有了空闲的任务就可以继续执行: // 阻塞等待直到有空闲worker for len(p.workers) == 0{ continue } p.lock.Lock() workers = p.workers l := len(workers) - 1 w = workers[l] workers[l] = nil p.workers = workers[:l] p.running++ p.lock.Unlock() } 5.如果是第二种的第二种情况,直接创建一个Worker实例。 // 当前无空闲worker但是Pool还没有满, // 则可以直接新开一个worker执行任务 p.running++ w = &Worker{ pool: p, task: make(chan functinType), str:make(chan string), } 测试package main import ( "Pool/Poolpkg" "fmt" ) func main(){
源码Pool package Poolpkg import ( "errors" "fmt" "sync" "sync/atomic" "time" ) type sig struct{} // Pool accept the tasks from client,it limits the total // of goroutines to a given number by recycling goroutines. type Pool struct { // capacity of the pool. //capacity是该Pool的容量,也就是开启worker数量的上限,每一个worker需要一个goroutine去执行; //worker类型为任务类。 capacity int32 // running is the number of the currently running goroutines. //running是当前正在执行任务的worker数量 running int32 // expiryDuration set the expired time (second) of every worker. //expiryDuration是worker的过期时长,在空闲队列中的worker的最新一次运行时间与当前时间之差如果大于这个值则表示已过期,定时清理任务会清理掉这个worker; expiryDuration time.Duration // workers is a slice that store the available workers. //任务队列 workers []*Worker // release is used to notice the pool to closed itself. //当关闭该Pool支持通知所有worker退出运行以防goroutine泄露 release chan sig // lock for synchronous operation //用以支持Pool的同步操作 lock sync.Mutex //once用在确保Pool关闭操作只会执行一次 once sync.Once } // NewPool generates a instance of ants pool func NewPool(size, expiry int) (*Pool, error) { if size <= 0 { return nil, errors.New("Pool Size <0,not Create") } p := &Pool{ capacity: int32(size), release: make(chan sig, 1), expiryDuration: time.Duration(expiry) * time.Second, running: 0, } // 启动定期清理过期worker任务,独立goroutine运行, // 进一步节省系统资源 p.monitorAndClear() return p, nil } // Submit submit a task to pool func (p *Pool) Submit(task functinType,str string) error { if len(p.release) > 0 { return errors.New("Pool is Close") } //创建或得到一个空闲的worker w := p.getWorker() w.run() //将任务参数通过信道传递给它 w.sendarg(str) //将任务通过信道传递给它 w.sendTask(task) return nil } // getWorker returns a available worker to run the tasks. func (p *Pool) getWorker() *Worker { var w *Worker // 标志,表示当前运行的worker数量是否已达容量上限 waiting := false // 涉及从workers队列取可用worker,需要加锁 p.lock.Lock() workers := p.workers n := len(workers) - 1 fmt.Println("空闲worker数量:",n+1) fmt.Println("协程池现在运行的worker数量:",p.running) // 当前worker队列为空(无空闲worker) if n < 0 { //没有空闲的worker有两种可能: //1.运行的worker超出了pool容量 //2.当前是空pool,从未往pool添加任务或者一段时间内没有任务添加,被定期清除 // 运行worker数目已达到该Pool的容量上限,置等待标志 if p.running >= p.capacity { //print("超过上限") waiting = true } else { // 当前无空闲worker但是Pool还没有满, // 则可以直接新开一个worker执行任务 p.running++ w = &Worker{ pool: p, task: make(chan functinType), str:make(chan string), } } // 有空闲worker,从队列尾部取出一个使用 } else { //<-p.freeSignal w = workers[n] workers[n] = nil p.workers = workers[:n] p.running++ } // 判断是否有worker可用结束,解锁 p.lock.Unlock() if waiting { //当一个任务执行完以后会添加到池中,有了空闲的任务就可以继续执行: // 阻塞等待直到有空闲worker for len(p.workers) == 0{ continue } p.lock.Lock() workers = p.workers l := len(workers) - 1 w = workers[l] workers[l] = nil p.workers = workers[:l] p.running++ p.lock.Unlock() } return w } //定期清理过期Worker func (p *Pool) monitorAndClear() { go func() { for { // 周期性循环检查过期worker并清理 time.Sleep(p.expiryDuration) currentTime := time.Now() p.lock.Lock() idleWorkers := p.workers n := 0 for i, w := range idleWorkers { // 计算当前时间减去该worker的最后运行时间之差是否符合过期时长 if currentTime.Sub(w.recycleTime) <= p.expiryDuration { break } n = i w.stop() idleWorkers[i] = nil p.running-- } if n > 0 { n++ p.workers = idleWorkers[n:] } p.lock.Unlock() } }() } //Worker回收(goroutine复用) // putWorker puts a worker back into free pool, recycling the goroutines. func (p *Pool) putWorker(worker *Worker) { // 写入回收时间,亦即该worker的最后运行时间 worker.recycleTime = time.Now() p.lock.Lock() p.running -- p.workers = append(p.workers, worker) p.lock.Unlock() } //动态扩容或者缩小池容量 // ReSize change the capacity of this pool func (p *Pool) ReSize(size int) { cap := int(p.capacity) if size < cap{ diff := cap - size for i := 0; i < diff; i++ { p.getWorker().stop() } } else if size == cap { return } atomic.StoreInt32(&p.capacity, int32(size)) } Woker package Poolpkg import ( "sync/atomic" "time" ) type functinType func(string) error // Worker is the actual executor who runs the tasks, // it starts a goroutine that accepts tasks and // performs function calls. type Worker struct { // pool who owns this worker. pool *Pool // task is a job should be done. task chan functinType // recycleTime will be update when putting a worker back into queue. recycleTime time.Time str chan string } // run starts a goroutine to repeat the process // that performs the function calls. func (w *Worker) run() { go func() { //监听任务列表,一旦有任务立马取出运行 count := 1 var str string var f functinType for count <=2{ select { case str_temp, ok := <- w.str: if !ok { return } count ++ str = str_temp case f_temp, ok := <-w.task: if !ok { //如果接收到关闭 atomic.AddInt32(&w.pool.running, -1) close(w.task) return } count ++ f = f_temp } } err := f(str) if err != nil{ //fmt.Println("执行任务失败") } //回收复用 w.pool.putWorker(w) return }() } // stop this worker. func (w *Worker) stop() { w.sendTask(nil) close(w.str) } // sendTask sends a task to this worker. func (w *Worker) sendTask(task functinType) { w.task <- task } func (w *Worker) sendarg(str string) { w.str <- str }
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