Golang function coroutine pool implementation technology sharing

Golang, as a rapid development and high-concurrency language, naturally also has the implementation of coroutine pool. The coroutine pool is a data structure used to manage coroutines. It can limit the total number of coroutines and control the timing of their creation and destruction, thereby optimizing the use of resources in a concurrent environment. Next, I will introduce how to use Golang functions to implement coroutine pools.

1. The concept of coroutine pool

The coroutine pool is a data structure used to manage coroutines. The purpose is to limit the number of coroutines and control their creation and The timing of destruction, thereby improving the concurrency of the program.

In the case of high concurrency, starting a coroutine will generate a lot of overhead every time. If the program needs to open hundreds or thousands of coroutines at the same time, these overheads will become very significant. Similar to common connection pools and thread pools, coroutine pools can better utilize computer resources and complete tasks involving a large number of concurrent operations.

2. Implementation ideas of coroutine pool

Coroutine pool can be divided into scalable pool and fixed pool. Among them, the scalable pool can automatically expand and shrink the capacity according to demand, while the fixed pool has a fixed capacity at the beginning and cannot be changed.

The main idea of ​​Golang function to implement coroutine pool is to communicate through two channels. One is the workerChannel, which is used to assign tasks to coroutine workers, and the other is the task channel, which is used to pass tasks to the workerChannel. When there is a task that needs to be executed, the task is taken out from the task channel, and a coroutine is created based on the number of available workers in the workerChannel or the task is directly assigned to an idle worker for execution. Workers who complete the task will return to the workerChannel and wait for the next task assignment. Of course, in some cases, the coroutine pool can also contain more data structures, such as mutexes or waiting groups, to control how tasks are executed.

3. Implementation code of coroutine pool

The following is the specific code to implement coroutine pool:

package main

import (
    "fmt"
    "sync"
)

type Task struct {
    f func() error
}

var wg sync.WaitGroup

type Pool struct {
    //任务通道
    JobQueue chan Task
    //worker通道
    WorkerQueue chan chan Task
    //worker数量
    MaxWorkers int
}

func NewPool(maxWorkers int) *Pool {
    return &Pool{
        JobQueue:    make(chan Task, 10),
        WorkerQueue: make(chan chan Task, maxWorkers),
        MaxWorkers:  maxWorkers,
    }
}

func (p *Pool) Run() {
    for i := 0; i < p.MaxWorkers; i++ {
        worker := NewWorker(i+1, p.WorkerQueue)
        worker.Start()
    }

    go p.dispatch()
}

func (p *Pool) dispatch() {
    for {
        select {
        case job := <-p.JobQueue:
            fmt.Println("new job")
            worker := <-p.WorkerQueue
            fmt.Println("append job")
            worker <- job
            fmt.Println("after run job")
        }
    }
}

func (p *Pool) AddTask(task Task) {
    p.JobQueue <- task
}

type Worker struct {
    id          int
    WorkerQueue chan chan Task
    JobChannel  chan Task
    quitChan    chan struct{}
}

func NewWorker(id int, workerQueue chan chan Task) Worker {
    fmt.Println("newWorker")
    return Worker{
        id:          id,
        WorkerQueue: workerQueue,
        JobChannel:  make(chan Task),
        quitChan:    make(chan struct{}),
    }
}

func (w *Worker) Start() {
    fmt.Println("worker start")
    go func() {
        for {
            //将自己的jobChannel放入worker队列中
            w.WorkerQueue <- w.JobChannel
            select {
            case task := <-w.JobChannel:
                fmt.Printf("worker%d start job
", w.id)
                task.f()
                fmt.Printf("worker%d finished job
", w.id)
            case <-w.quitChan:
                fmt.Printf("worker%d quit
", w.id)
                return
            }
        }
    }()
}

func (w *Worker) Stop() {
    go func() {
        w.quitChan <- struct{}{}
    }()
}

func Hello() error {
    fmt.Println("Hello World")
    wg.Done()
    return nil
}

func main() {
    p := NewPool(5)
    p.Run()

    for i := 0; i < 100; i++ {
        task := Task{
            f: Hello,
        }
        wg.Add(1)
        p.AddTask(task)
    }
    wg.Wait()
}

By running the above code, you can see the control The log information output by the station. Among them, worker start means that each worker starts running, new job means adding a task to the task channel, append job means that the task is placed in the worker channel and waiting for execution, and after run job means that the task has been successfully executed.

4. Code Analysis

In the above code, the NewPool function is used to initialize the coroutine pool, which includes task channels, worker channels, and the number of workers. The Worker type corresponds to the coroutine worker and includes a task channel and a quit channel to end the running of the worker coroutine. The NewWorker function is responsible for initializing the worker object and adding its task channel to the worker channel in the coroutine pool.

The AddTask function is used to add a new task to the coroutine pool task channel. This function blocks until the task is added. If there is a free worker in the worker channel, the task will be assigned to the worker directly, otherwise it will wait for a worker in the worker channel to be released.

The Start function is responsible for starting the worker coroutine and starting to wait for the arrival of the task. This function will first add its own task channel to the worker channel, and then wait for the task to arrive until the task channel is closed or the quit channel signal is received. If a task is received, execute the task. If the quit channel signal is received within the loop, it means that the running of the coroutine needs to end, and the worker will remove itself from the worker channel at this time.

The dispatch function is a go coroutine that listens to task channels and assigns tasks to them based on available workers. When there are new tasks in the task channel, dispatch will try to get free workers from the worker channel and assign the tasks to them. If there are no free workers in the worker channel, it will wait until a worker is released.

5. Summary

This article introduces the idea and implementation code of Golang function to implement coroutine pool. The number of coroutines can be controlled through the coroutine pool, thereby fully utilizing computer resources and improving program concurrency in a high-concurrency environment.

The above is the detailed content of Golang function coroutine pool implementation technology sharing. For more information, please follow other related articles on the PHP Chinese website!