C++(20):线程池的实现和使用

线程池作用

线程池能够减少创建的线程个数，线程池的出现着眼于减少线程本身带来的开销

线程池适合场景

(1)单位时间内处理任务频繁而且任务处理时间短
(2)对实时性要求较高。如果接受到任务后在创建线程，可能满足不了实时要求，因此必须采用线程池进行预创建。

实现代码

代码来自github上的一位大神，只用一个简单的头文件就实现了线程池：https://github.com/progschj/ThreadPool

#ifndef THREAD_POOL_H
#define THREAD_POOL_H
 
#include <vector>
#include <queue>
#include <memory>
#include <thread>
#include <mutex>
#include <condition_variable>
#include <future>
#include <functional>
#include <stdexcept>
 
class ThreadPool {
public:
    ThreadPool(size_t);
    template<class F, class... Args>
    auto enqueue(F&& f, Args&&... args) 
        -> std::future<typename std::result_of<F(Args...)>::type>;
    ~ThreadPool();
private:
    // need to keep track of threads so we can join them
    std::vector< std::thread > workers;
    // the task queue
    std::queue< std::function<void()> > tasks;
    
    // synchronization
    std::mutex queue_mutex;
    std::condition_variable condition;
    bool stop;
};
 
// the constructor just launches some amount of workers
inline ThreadPool::ThreadPool(size_t threads)
    :   stop(false)
{
    for(size_t i = 0;i<threads;++i)
        workers.emplace_back(
            [this]
            {
                for(;;)
                {
                    std::function<void()> task;
 
                    {
                        std::unique_lock<std::mutex> lock(this->queue_mutex);
                        this->condition.wait(lock,
                            [this]{ return this->stop || !this->tasks.empty(); });
                        if(this->stop && this->tasks.empty())
                            return;
                        task = std::move(this->tasks.front());
                        this->tasks.pop();
                    }
 
                    task();
                }
            }
        );
}
 
// add new work item to the pool
template<class F, class... Args>
auto ThreadPool::enqueue(F&& f, Args&&... args) 
    -> std::future<typename std::result_of<F(Args...)>::type>
{
    using return_type = typename std::result_of<F(Args...)>::type;
 
    auto task = std::make_shared< std::packaged_task<return_type()> >(
            std::bind(std::forward<F>(f), std::forward<Args>(args)...)
        );
        
    std::future<return_type> res = task->get_future();
    {
        std::unique_lock<std::mutex> lock(queue_mutex);
 
        // don't allow enqueueing after stopping the pool
        if(stop)
            throw std::runtime_error("enqueue on stopped ThreadPool");
 
        tasks.emplace([task](){ (*task)(); });
    }
    condition.notify_one();
    return res;
}
 
// the destructor joins all threads
inline ThreadPool::~ThreadPool()
{
    {
        std::unique_lock<std::mutex> lock(queue_mutex);
        stop = true;
    }
    condition.notify_all();
    for(std::thread &worker: workers)
        worker.join();
}
 
#endif

两个使用的demo

#include <iostream>
#include "ThreadPool.h"
 
int main()
{
    // create thread pool with 4 worker threads
    ThreadPool pool(4);
 
    // enqueue and store future
    auto result = pool.enqueue([](int answer) { return answer; }, 42);
 
    // get result from future, print 42
    std::cout << result.get() << std::endl; 
}

#include <iostream>
#include "ThreadPool.h"
 
void func()
{
    std::this_thread::sleep_for(std::chrono::milliseconds(100));
    std::cout<<"worker thread ID:"<<std::this_thread::get_id()<<std::endl;
}

void func2(int a, string b)
{
    
}

int main()
{
    ThreadPool pool(4);
    while(1)
    {
       pool.enqueue(func);
      //pool.enqueue(func2, 2, "abc");
    }
}