test_threadPool&test_threadPoolBenchmark 分析

 

1.类图

 

 2.代码注释：

 2.1 test_threadPool.cpp

/**
 * 演示功能说明：
 * 1.线程池异步运行 “X = cpu逻辑核个数*4” 个任务，每个任务执行 task_second = 3秒
 * 2.使用Ticker计时 X个任务执行消耗的时间
 * 3.vec存放执行任务的顺序编号 i
 * 4.linux /mac系统会设置cpu的亲和性
 * 5.使用信号量 sem 进行进程控制
 */
int main() {
    //初始化日志系统
    Logger::Instance().add(std::make_shared<ConsoleChannel>());
    Logger::Instance().setWriter(std::make_shared<AsyncLogWriter>());
    //liu 此笔记本的逻辑处理器是12个
    ThreadPool pool(thread::hardware_concurrency(), ThreadPool::PRIORITY_HIGHEST, true);

    //每个任务耗时3秒
    auto task_second = 3;
    // liu 返回支持的并发线程数 https://zh.cppreference.com/w/cpp/thread/thread/hardware_concurrency
    //每个线程平均执行4次任务，总耗时应该为12秒
    auto task_count = thread::hardware_concurrency() * 4;

    semaphore sem;
    //liu vec中存放的是已经执行的任务的编号 i
    vector<int> vec;
    // liu 重设容器大小以容纳 count 个元素
    vec.resize(task_count);
    Ticker ticker;
    {
        //放在作用域中确保token引用次数减1
        auto token = std::make_shared<onceToken>(nullptr, [&]() {
            // liu v操作 释放资源 加1
            sem.post();
        });

        // liu 异步执行48个任务
        for (auto i = 0; i < task_count; ++i) {
            pool.async([token, i, task_second, &vec]() {
                setThreadName(("thread pool " + to_string(i)).data());
                std::this_thread::sleep_for(std::chrono::seconds(task_second)); //休眠三秒
                InfoL << "task " << i << " done!";
                vec[i] = i;
            });
        }
    }

    //liu p操作 申请资源 减1
    sem.wait();
    InfoL << "all task done, used milliseconds:" << ticker.elapsedTime();

    //打印执行结果
    for (auto i = 0; i < task_count; ++i) {
        InfoL << vec[i];
    }
    return 0;
}

 2.2 threadPool.h

/*
 * Copyright (c) 2016 The ZLToolKit project authors. All Rights Reserved.
 *
 * This file is part of ZLToolKit(https://github.com/ZLMediaKit/ZLToolKit).
 *
 * Use of this source code is governed by MIT license that can be found in the
 * LICENSE file in the root of the source tree. All contributing project authors
 * may be found in the AUTHORS file in the root of the source tree.
 */

#ifndef THREADPOOL_H_
#define THREADPOOL_H_

#include "threadgroup.h"
#include "TaskQueue.h"
#include "TaskExecutor.h"
#include "Util/util.h"
#include "Util/logger.h"

namespace toolkit {

/**
 * liu
 * 理解到关键点：
 * thread_group 管理thread
 * TaskQueue<Task::Ptr> _queue：管理任务
 * 任务需要扔到thread中运行
 */
class ThreadPool : public TaskExecutor {
public:
    //liu 在ThreadPool构造函数中，默认设置最高优先级PRIORITY_HIGHEST
    enum Priority {
        PRIORITY_LOWEST = 0,
        PRIORITY_LOW,
        PRIORITY_NORMAL,
        PRIORITY_HIGH,
        PRIORITY_HIGHEST
    };

    /**
     * liu 构造函数：
     * 1.创建线程池对象，开辟线程，并且运行线程
     * 2.设置cpu亲和性，提高命中率，目前设置的都是index = 0
     * 3.构造函数执行中，已经创建了线程，然后放到thread_group中，并且每个线程开始逐个run()
     * 4.【关键点】管理线程池ThreadPool中的 thread，记录 以thread_id为键，thread对象为值
     *     thread_group _thread_group;
     * 5.【关键点】Task异步任务存放容器，作为缓存，最后任务都得从队列中取出来，在thread中进行执行run；
     * TaskQueue<Task::Ptr> _queue;
     * @param num 线程池开辟的线程个数
     * @param priority 线程池的优先级
     * @param auto_run 是否同步开始运行
     * @param set_affinity 是否设置亲和性，亲和性只设置取模： index % cpu逻辑核数
     * @param pool_name 线程池的名称
     */
    ThreadPool(int num = 1, Priority priority = PRIORITY_HIGHEST, bool auto_run = true, bool set_affinity = true,
               const std::string &pool_name = "thread pool") {
        _thread_num = num;
        _on_setup = [pool_name, priority, set_affinity](int index) {
            std::string name = pool_name + ' ' + std::to_string(index);
            setPriority(priority);
            setThreadName(name.data());
            if (set_affinity) {  // liu win-debug调试 index = 0/ ubuntu-debug index = 0
                setThreadAffinity(index % std::thread::hardware_concurrency());
            }
        };
        _logger = Logger::Instance().shared_from_this();
        if (auto_run) {
            start();
        }
    }

    ~ThreadPool() {
        shutdown();
        wait();
    }

    /**
     * liu 从TaskExecutorInterface 继承来的方法
     * @param task
     * @param may_sync
     * @return
     */
    //把任务打入线程池并异步执行
    Task::Ptr async(TaskIn task, bool may_sync = true) override {
        if (may_sync && _thread_group.is_this_thread_in()) {
            // liu 生成该Task的对象，调用构造函数
            task();
            return nullptr;
        }
        auto ret = std::make_shared<Task>(std::move(task));
        // liu 任务插入到TaskQueue(list)的back
        _queue.push_task(ret);
        return ret;
    }

    // liu 任务插入到TaskQueue(list)的front
    Task::Ptr async_first(TaskIn task, bool may_sync = true) override {
        if (may_sync && _thread_group.is_this_thread_in()) {
            task();
            return nullptr;
        }

        auto ret = std::make_shared<Task>(std::move(task));
        _queue.push_task_first(ret);
        return ret;
    }

    size_t size() {
        return _queue.size();
    }

    /**
     * liu 设置线程池优先级
     * @param priority
     * @param threadId std::thread::native_handle 返回实现定义的底层线程柄
     * 【参考: https://zh.cppreference.com/w/cpp/thread/thread/native_handle】
     * 【参考：重要文章】https://blog.csdn.net/super828/article/details/118683784
     * 返回表示的线程句柄的特定于实现的类型。 特定于实现的方式，可以使用的线程句柄
     * 【参考：https://learn.microsoft.com/zh-cn/previous-versions/jj870808(v=vs.140)】
     * 获取当前线程的线程id，一般就是std::thread提供的接口不满足要求时，需要获取线程id调用底层库进行操作
     * 【参考：https://zhuanlan.zhihu.com/p/547970094】
     * @return
     */
    static bool setPriority(Priority priority = PRIORITY_NORMAL, std::thread::native_handle_type threadId = 0) {
        // set priority
#if defined(_WIN32)
        static int Priorities[] = { THREAD_PRIORITY_LOWEST, THREAD_PRIORITY_BELOW_NORMAL, THREAD_PRIORITY_NORMAL, THREAD_PRIORITY_ABOVE_NORMAL, THREAD_PRIORITY_HIGHEST };
        if (priority != PRIORITY_NORMAL && SetThreadPriority(GetCurrentThread(), Priorities[priority]) == 0) {
            return false;
        }
        return true;
#else
        static int Min = sched_get_priority_min(SCHED_FIFO);
        if (Min == -1) {
            return false;
        }
        static int Max = sched_get_priority_max(SCHED_FIFO);
        if (Max == -1) {
            return false;
        }

        // liu ubuntu20.01 clion-debug
        // Priorities[] = {1,25,50,74,99}; max = 99; min = 1
        static int Priorities[] = {Min, Min + (Max - Min) / 4, Min + (Max - Min) / 2, Min + (Max - Min) * 3 / 4, Max};

        if (threadId == 0) {
            threadId = pthread_self();
        }
        struct sched_param params;
        params.sched_priority = Priorities[priority];
        // liu  params.sched_priority = {int}99
        return pthread_setschedparam(threadId, SCHED_FIFO, &params) == 0;
#endif
    }

    /**
     * liu
     * 1.创建线程，然后放到thread_group中
     * 2.并且开始执行thread.run 线程运行，调用了该类成员函数 run(index i)
     */
    void start() {
        if (_thread_num <= 0) {
            return;
        }
        size_t total = _thread_num - _thread_group.size();
        for (size_t i = 0; i < total; ++i) {
            _thread_group.create_thread([this, i]() {run(i);});
        }
    }

private:
    // liu 循环while不停的取出任务容器_queue中的Task任务，不停的执行任务
    void run(size_t index) {
        _on_setup(index);
        Task::Ptr task;
        while (true) {
            startSleep();
            //liu此task的来源是 async 放入到thread_group对象中的_threads(map)中的对象
            // 所有已经创建的线程都在 _threads 中，map，以thread_id为键，thread对象为值
            if (!_queue.get_task(task)) {
                //空任务，退出线程
                break;
            }
            sleepWakeUp();
            // liu 执行task
            try {
                (*task)();
                task = nullptr;
            } catch (std::exception &ex) {
                ErrorL << "ThreadPool catch a exception: " << ex.what();
            }
        }
    }

    void wait() {
        _thread_group.join_all();
    }

    void shutdown() {
        _queue.push_exit(_thread_num);
    }

private:
    size_t _thread_num;
    Logger::Ptr _logger;
    // liu 【关键点】管理线程池ThreadPool的 thread；
    thread_group _thread_group;
    // liu 【关键点】Task异步任务存放容器，作为缓存，最后任务都得从队列中取出来，在thread中进行执行run；
    TaskQueue<Task::Ptr> _queue;
    /*类模板 std :: function 是一个通用的多态函数包装器。
     * std :: function 的实例可以存储，复制和调用任何可调用的目标 ：包括函数，lambda表达式，绑定表达式或其他函数对象，以及指向成员函数和指向数据成员的指针。
     * 当std::function对象未包裹任何实际的可调用元素，调用该 std::function 对象将抛出std::bad_function_call 异常。
     * 原文链接：https://blog.csdn.net/qq_41317716/article/details/125839126*/
    std::function<void(int)> _on_setup;
};

} /* namespace toolkit */
#endif /* THREADPOOL_H_ */

 2.3 threadgroup.h

/*
 * Copyright (c) 2016 The ZLToolKit project authors. All Rights Reserved.
 *
 * This file is part of ZLToolKit(https://github.com/ZLMediaKit/ZLToolKit).
 *
 * Use of this source code is governed by MIT license that can be found in the
 * LICENSE file in the root of the source tree. All contributing project authors
 * may be found in the AUTHORS file in the root of the source tree.
 */

#ifndef THREADGROUP_H_
#define THREADGROUP_H_

#include <stdexcept>
#include <thread>
#include <unordered_map>

namespace toolkit {

/**
 *  liu
 *  1.所有已经创建的线程都在 _threads 中，map，以thread_id为键，thread对象为值
 *  2.赋值和拷贝构造函数是private权限
 */
class thread_group {
private:
    // liu 拷贝构造
    thread_group(thread_group const &);
    //  liu 赋值构造
    thread_group &operator=(thread_group const &);

public:
    thread_group() {}

    ~thread_group() {
        _threads.clear();
    }


    // liu 判断该this指向的线程是否在该thread_group中
    bool is_this_thread_in() {
        auto thread_id = std::this_thread::get_id();
        if (_thread_id == thread_id) {
            return true;
        }
        return _threads.find(thread_id) != _threads.end();
    }

    //liu 判断该线程thread是否在thread_group中
    bool is_thread_in(std::thread *thrd) {
        if (!thrd) {
            return false;
        }
        auto it = _threads.find(thrd->get_id());
        return it != _threads.end();
    }

    //liu 将线程对象放入到_threads(map)中:thread_id 是键，thread对象是值
    template<typename F>
    std::thread *create_thread(F &&threadfunc) {
        auto thread_new = std::make_shared<std::thread>(threadfunc);
        _thread_id = thread_new->get_id();
        _threads[_thread_id] = thread_new;
        return thread_new.get();
    }

    void remove_thread(std::thread *thrd) {
        auto it = _threads.find(thrd->get_id());
        if (it != _threads.end()) {
            _threads.erase(it);
        }
    }

    void join_all() {
        if (is_this_thread_in()) {
            throw std::runtime_error("Trying joining itself in thread_group");
        }
        for (auto &it : _threads) {
            if (it.second->joinable()) {
                it.second->join(); //等待线程主动退出
            }
        }
        _threads.clear();
    }

    size_t size() {
        return _threads.size();
    }

private:
    std::thread::id _thread_id;
    std::unordered_map<std::thread::id, std::shared_ptr<std::thread>> _threads;
};

} /* namespace toolkit */
#endif /* THREADGROUP_H_ */

2.4  TaskExecutor.h

#ifndef ZLTOOLKIT_TASKEXECUTOR_H
#define ZLTOOLKIT_TASKEXECUTOR_H

#include <mutex>
#include <memory>
#include <functional>
#include "Util/List.h"
#include "Util/util.h"

namespace toolkit {

/**
 * cpu负载计算器
 * liu 按照cpu的 计算负载=运行时间*100/总时间；单位是us；乘以100，是因为按照百分比计算
 */
class ThreadLoadCounter {
public:
    /**
     * 构造函数
     * @param max_size 统计样本数量
     * @param max_usec 统计时间窗口,亦即最近{max_usec}的cpu负载率
     */
    ThreadLoadCounter(uint64_t max_size, uint64_t max_usec);
    ~ThreadLoadCounter() = default;

    /**
     * 线程进入休眠
     */
    void startSleep();

    /**
     * 休眠唤醒,结束休眠
     */
    void sleepWakeUp();

    /**
     * 返回当前线程cpu使用率，范围为 0 ~ 100
     * @return 当前线程cpu使用率
     */
    int load();

private:
    struct TimeRecord {
        TimeRecord(uint64_t tm, bool slp) {
            _time = tm;
            _sleep = slp;
        }

        bool _sleep;
        uint64_t _time;
    };

private:
    bool _sleeping = true;
    uint64_t _last_sleep_time;
    uint64_t _last_wake_time;
    uint64_t _max_size;
    uint64_t _max_usec;
    std::mutex _mtx;
    /*liu 存放runtime-slp、sleeptime—slp的键值对，slp表示是否该时间是运行还是睡眠时间*/
    List<TimeRecord> _time_list;
};

class TaskCancelable : public noncopyable {
public:
    TaskCancelable() = default;
    virtual ~TaskCancelable() = default;
    virtual void cancel() = 0;
};

template<class R, class... ArgTypes>
class TaskCancelableImp;

template<class R, class... ArgTypes>
class TaskCancelableImp<R(ArgTypes...)> : public TaskCancelable {
public:
    using Ptr = std::shared_ptr<TaskCancelableImp>;
    using func_type = std::function<R(ArgTypes...)>;

    ~TaskCancelableImp() = default;

    template<typename FUNC>
    TaskCancelableImp(FUNC &&task) {
        _strongTask = std::make_shared<func_type>(std::forward<FUNC>(task));
        _weakTask = _strongTask;
    }

    void cancel() override {
        _strongTask = nullptr;
    }

    operator bool() {
        return _strongTask && *_strongTask;
    }

    void operator=(std::nullptr_t) {
        _strongTask = nullptr;
    }

    R operator()(ArgTypes ...args) const {
        auto strongTask = _weakTask.lock();
        if (strongTask && *strongTask) {
            return (*strongTask)(std::forward<ArgTypes>(args)...);
        }
        return defaultValue<R>();
    }

    template<typename T>
    static typename std::enable_if<std::is_void<T>::value, void>::type
    defaultValue() {}

    template<typename T>
    static typename std::enable_if<std::is_pointer<T>::value, T>::type
    defaultValue() {
        return nullptr;
    }

    template<typename T>
    static typename std::enable_if<std::is_integral<T>::value, T>::type
    defaultValue() {
        return 0;
    }

protected:
    std::weak_ptr<func_type> _weakTask;
    std::shared_ptr<func_type> _strongTask;
};

using TaskIn = std::function<void()>;
using Task = TaskCancelableImp<void()>;

class TaskExecutorInterface {
public:
    TaskExecutorInterface() = default;
    virtual ~TaskExecutorInterface() = default;

    /**
     * 异步执行任务
     * @param task 任务
     * @param may_sync 是否允许同步执行该任务
     * @return 任务是否添加成功
     */
    virtual Task::Ptr async(TaskIn task, bool may_sync = true) = 0;

    /**
     * 最高优先级方式异步执行任务
     * @param task 任务
     * @param may_sync 是否允许同步执行该任务
     * @return 任务是否添加成功
     */
    virtual Task::Ptr async_first(TaskIn task, bool may_sync = true);

    /**
     * 同步执行任务
     * @param task
     * @return
     */
    void sync(const TaskIn &task);

    /**
     * 最高优先级方式同步执行任务
     * @param task
     * @return
     */
    void sync_first(const TaskIn &task);
};

/**
* 任务执行器
*/
class TaskExecutor : public ThreadLoadCounter, public TaskExecutorInterface {
public:
    using Ptr = std::shared_ptr<TaskExecutor>;

    /**
     * 构造函数
     * @param max_size cpu负载统计样本数
     * @param max_usec cpu负载统计时间窗口大小
     */
    TaskExecutor(uint64_t max_size = 32, uint64_t max_usec = 2 * 1000 * 1000);
    ~TaskExecutor() = default;
};

class TaskExecutorGetter {
public:
    using Ptr = std::shared_ptr<TaskExecutorGetter>;

    virtual ~TaskExecutorGetter() = default;

    /**
     * 获取任务执行器
     * @return 任务执行器
     */
    virtual TaskExecutor::Ptr getExecutor() = 0;

    /**
     * 获取执行器个数
     */
    virtual size_t getExecutorSize() const = 0;
};

class TaskExecutorGetterImp : public TaskExecutorGetter {
public:
    TaskExecutorGetterImp() = default;
    ~TaskExecutorGetterImp() = default;

    /**
     * 根据线程负载情况，获取最空闲的任务执行器
     * @return 任务执行器
     */
    TaskExecutor::Ptr getExecutor() override;

    /**
     * 获取所有线程的负载率
     * @return 所有线程的负载率
     */
    std::vector<int> getExecutorLoad();

    /**
     * 获取所有线程任务执行延时，单位毫秒
     * 通过此函数也可以大概知道线程负载情况
     * @return
     */
    void getExecutorDelay(const std::function<void(const std::vector<int> &)> &callback);

    /**
     * 遍历所有线程
     */
    void for_each(const std::function<void(const TaskExecutor::Ptr &)> &cb);

    /**
     * 获取线程数
     */
    size_t getExecutorSize() const override;

protected:
    size_t addPoller(const std::string &name, size_t size, int priority, bool register_thread, bool enable_cpu_affinity = true);

protected:
    size_t _thread_pos = 0;
    std::vector<TaskExecutor::Ptr> _threads;
};

}//toolkit
#endif //ZLTOOLKIT_TASKEXECUTOR_H

 2.5  运行结果

E:\26_zlmediakit\11_ZLToolKit\__202311141609_202312281011_1_bak\__202311141609_bak\__202311141609\ZLToolKit\cmake-build-debug\bin\test_threadPool.exe
2024-01-03 16:26:03.594 D [test_threadPool.exe] [7824-stamp thread] util.cpp:367 operator () | Stamp thread started
2024-01-03 16:26:06.604 I [test_threadPool.exe] [7824-thread pool 0] test_threadPool.cpp:59 operator () | task 0 done!
2024-01-03 16:26:06.604 I [test_threadPool.exe] [7824-thread pool 1] test_threadPool.cpp:59 operator () | task 1 done!
2024-01-03 16:26:06.605 I [test_threadPool.exe] [7824-thread pool 9] test_threadPool.cpp:59 operator () | task 9 done!
2024-01-03 16:26:06.605 I [test_threadPool.exe] [7824-thread pool 10] test_threadPool.cpp:59 operator () | task 10 done!

2024-01-03 16:26:06.605 I [test_threadPool.exe] [7824-thread pool 2] test_threadPool.cpp:59 operator () | task 2 done!
2024-01-03 16:26:06.605 I [test_threadPool.exe] [7824-thread pool 11] test_threadPool.cpp:59 operator () | task 11 done!

2024-01-03 16:26:06.605 I [test_threadPool.exe] [7824-thread pool 8] test_threadPool.cpp:59 operator () | task 8 done!
2024-01-03 16:26:06.605 I [test_threadPool.exe] [7824-thread pool 5] test_threadPool.cpp:59 operator () | task 5 done!
2024-01-03 16:26:06.605 I [test_threadPool.exe] [7824-thread pool 6] test_threadPool.cpp:59 operator () | task 6 done!
2024-01-03 16:26:06.605 I [test_threadPool.exe] [7824-thread pool 4] test_threadPool.cpp:59 operator () | task 4 done!
2024-01-03 16:26:06.605 I [test_threadPool.exe] [7824-thread pool 3] test_threadPool.cpp:59 operator () | task 3 done!
2024-01-03 16:26:06.605 I [test_threadPool.exe] [7824-thread pool 7] test_threadPool.cpp:59 operator () | task 7 done!
2024-01-03 16:26:09.606 I [test_threadPool.exe] [7824-thread pool 12] test_threadPool.cpp:59 operator () | task 12 done!

2024-01-03 16:26:09.606 I [test_threadPool.exe] [7824-thread pool 21] test_threadPool.cpp:59 operator () | task 21 done!

2024-01-03 16:26:09.606 I [test_threadPool.exe] [7824-thread pool 19] test_threadPool.cpp:59 operator () | task 19 done!

2024-01-03 16:26:09.606 I [test_threadPool.exe] [7824-thread pool 17] test_threadPool.cpp:59 operator () | task 17 done!

2024-01-03 16:26:09.606 I [test_threadPool.exe] [7824-thread pool 13] test_threadPool.cpp:59 operator () | task 13 done!

2024-01-03 16:26:09.606 I [test_threadPool.exe] [7824-thread pool 20] test_threadPool.cpp:59 operator () | task 20 done!

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2024-01-03 16:26:15.622 I [test_threadPool.exe] [7824-9468] test_threadPool.cpp:71 main | 42
2024-01-03 16:26:15.622 I [test_threadPool.exe] [7824-9468] test_threadPool.cpp:71 main | 43
2024-01-03 16:26:15.622 I [test_threadPool.exe] [7824-9468] test_threadPool.cpp:71 main | 44
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2024-01-03 16:26:15.622 I [test_threadPool.exe] [7824-9468] test_threadPool.cpp:71 main | 46
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2024-01-03 16:26:15.691 I [test_threadPool.exe] [7824-9468] logger.cpp:86 ~Logger | 

进程已结束,退出代码0

 3.test_threadPoolBenchmark 注释 

#include <csignal>
#include <atomic>
#include <iostream>
#include "Util/logger.h"
#include "Util/TimeTicker.h"
#include "Thread/ThreadPool.h"

using namespace std;
using namespace toolkit;

int main() {
    signal(SIGINT,[](int ){
        exit(0);
    });
    //初始化日志系统
    Logger::Instance().add(std::make_shared<ConsoleChannel> ());

    atomic_llong count(0);
    // liu 此处的 auto_run 设置的是false，不会直接开启线程执行
    ThreadPool pool(1,ThreadPool::PRIORITY_HIGHEST, false);

    Ticker ticker;
    // liu 1000w个任务入队线程池耗时
    for (int i = 0 ; i < 1000*10000;++i){
        pool.async([&](){
           if(++count >= 1000*10000){
               InfoL << "执行1000万任务总共耗时:" << ticker.elapsedTime() << "ms";
           }
        });
    }
    InfoL << "1000万任务入队耗时:" << ticker.elapsedTime() << "ms" << endl;
    uint64_t  lastCount = 0 ,nowCount = 1;
    ticker.resetTime();
    //此处才开始启动线程
    pool.start();
    while (true){
        sleep(1);
        nowCount = count.load();
        InfoL << "每秒执行任务数:" << nowCount - lastCount;
        if(nowCount - lastCount == 0){
            break;
        }
        lastCount = nowCount;
    }
    return 0;
}
/**
 * 【运行结果对比】
 * 相比与widows：ubuntu20.04下入队耗时时间长，但是每秒的任务执行效率高；
 *
 * ubuntu20.04 下的运行结果：
 * /work/__202311141609_202312281011_bak/__202311141609_bak/__202311141609/ZLToolKit/cmake-build-debug/bin/test_threadPoolBenchmark
2024-01-03 15:36:05.254 D [test_threadPoolBenchmark] [13328-stamp thread] util.cpp:367 operator() | Stamp thread started
2024-01-03 15:36:14.965 I [test_threadPoolBenchmark] [13328-test_threadPool] test_threadPoolBenchmark.cpp:40 main | 1000万任务入队耗时:9709ms
2024-01-03 15:36:15.966 I [test_threadPoolBenchmark] [13328-test_threadPool] test_threadPoolBenchmark.cpp:48 main | 每秒执行任务数:1122279
2024-01-03 15:36:16.966 I [test_threadPoolBenchmark] [13328-test_threadPool] test_threadPoolBenchmark.cpp:48 main | 每秒执行任务数:1141750
2024-01-03 15:36:17.966 I [test_threadPoolBenchmark] [13328-test_threadPool] test_threadPoolBenchmark.cpp:48 main | 每秒执行任务数:1146485
2024-01-03 15:36:18.966 I [test_threadPoolBenchmark] [13328-test_threadPool] test_threadPoolBenchmark.cpp:48 main | 每秒执行任务数:1134105
2024-01-03 15:36:19.967 I [test_threadPoolBenchmark] [13328-test_threadPool] test_threadPoolBenchmark.cpp:48 main | 每秒执行任务数:1109435
2024-01-03 15:36:20.967 I [test_threadPoolBenchmark] [13328-test_threadPool] test_threadPoolBenchmark.cpp:48 main | 每秒执行任务数:1127861
2024-01-03 15:36:21.967 I [test_threadPoolBenchmark] [13328-test_threadPool] test_threadPoolBenchmark.cpp:48 main | 每秒执行任务数:1137880
2024-01-03 15:36:22.968 I [test_threadPoolBenchmark] [13328-test_threadPool] test_threadPoolBenchmark.cpp:48 main | 每秒执行任务数:1131760
2024-01-03 15:36:23.842 I [test_threadPoolBenchmark] [13328-thread pool 0] test_threadPoolBenchmark.cpp:36 operator() | 执行1000万任务总共耗时:8878ms
2024-01-03 15:36:23.968 I [test_threadPoolBenchmark] [13328-test_threadPool] test_threadPoolBenchmark.cpp:48 main | 每秒执行任务数:948445
2024-01-03 15:36:24.969 I [test_threadPoolBenchmark] [13328-test_threadPool] test_threadPoolBenchmark.cpp:48 main | 每秒执行任务数:0
2024-01-03 15:36:24.969 I [test_threadPoolBenchmark] [13328-test_threadPool] logger.cpp:86 ~Logger |

进程已结束,退出代码0
============================
 windows下的运行结果：
 2024-01-03 15:37:43.140 D [test_threadPoolBenchmark.exe] [18316-stamp thread] util.cpp:366 operator () | Stamp thread started
2024-01-03 15:37:56.332 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:39 main | 1000万任务入队耗时:13183ms
2024-01-03 15:37:57.336 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:574157
2024-01-03 15:37:58.340 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:550270
2024-01-03 15:37:59.344 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:578763
2024-01-03 15:38:00.348 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:574638
2024-01-03 15:38:01.354 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:581882
2024-01-03 15:38:02.357 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:580594
2024-01-03 15:38:03.361 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:581774
2024-01-03 15:38:04.365 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:584657
2024-01-03 15:38:05.370 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:586089
2024-01-03 15:38:06.374 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:585166
2024-01-03 15:38:07.379 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:584371
2024-01-03 15:38:08.384 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:582507
2024-01-03 15:38:09.390 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:587002
2024-01-03 15:38:10.391 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:588688
2024-01-03 15:38:11.393 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:577069
2024-01-03 15:38:12.396 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:579160
2024-01-03 15:38:13.399 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:576091
2024-01-03 15:38:13.650 I [test_threadPoolBenchmark.exe] [18316-thread pool 0] test_threadPoolBenchmark.cpp:35 operator () | 执行1000万任务总共耗时:17315ms
2024-01-03 15:38:14.403 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:147122
2024-01-03 15:38:15.406 I [test_threadPoolBenchmark.exe] [18316-2144] test_threadPoolBenchmark.cpp:47 main | 每秒执行任务数:0
2024-01-03 15:38:15.409 I [test_threadPoolBenchmark.exe] [18316-2144] logger.cpp:86 ~Logger |

E:\26_zlmediakit\11_ZLToolKit\__202311141609-vs\__202311141609\ZLToolKit\bin\Debug\test_threadPoolBenchmark.exe (进程 18316)已退出，代码为 0。
按任意键关闭此窗口. . .



 */

4.参考onceToken解析

https://github.com/ZLMediaKit/ZLMediaKit/wiki/%E4%BB%A3%E7%A0%81%E7%AF%87%E4%B9%8BonceToken

这里是作者的解析，原地址如上