很多系统对资源的访问快捷性及可预测性有严格要求,列入包括网络连接、对象实例、线程和内存。而且还要求解决方案可扩展,能应付存在大量资源的情形。
object pool针对特定类型的对象循环利用,这些对象要么创建开销巨大,要么可创建的数量有限。而且在pool中的对象需要做到无状态。
然后转了这位博主的代码,还在研究中
const int MaxObjectNum = ;
template <typename T>
class ObjectPool
{
template <typename... Args>
using Constructor = std::function<std::shared_ptr<T>(Args...)>; public:
ObjectPool(void)
: m_bNeedClear(false)
{
} virtual ~ObjectPool(void)
{
m_bNeedClear = true;
} template <typename... Args>
void Init(size_t num, Args &&... args)
{
if (num <= || num > MaxObjectNum)
{
throw std::logic_error("object num out of range.");
} auto constructName = typeid(Constructor<Args...>).name(); for (size_t i = ; i < num; i++)
{
m_object_map.emplace(constructName,
std::shared_ptr<T>(new T(std::forward<Args>(args)...), [constructName, this](T *t) {
if (m_bNeedClear)
{
delete t;
}
else
{
m_object_map.emplace(constructName, std::shared_ptr<T>(t));
}
}));
}
} template <typename... Args>
std::shared_ptr<T> Get()
{
string constructName = typeid(Constructor<Args...>).name(); auto range = m_object_map.equal_range(constructName); for (auto it = range.first; it != range.second; ++it)
{
auto ptr = it->second;
m_object_map.erase(it);
return ptr;
} return nullptr;
} private:
std::multimap<std::string, std::shared_ptr<T>> m_object_map;
bool m_bNeedClear;
};
ObjectPool.cpp
class BigObject
{
public:
BigObject() {} BigObject(int a) {} BigObject(const int &a, const int &b)
{
} void Print(const string &str)
{
cout << str << endl;
}
}; void Print(shared_ptr<BigObject> p, const string &str)
{
if (p != nullptr)
{
p->Print(str);
}
} int main()
{
ObjectPool<BigObject> pool;
pool.Init();
{
auto p = pool.Get();
Print(p, "p"); auto p2 = pool.Get();
Print(p2, "p2");
} auto p = pool.Get();
Print(p, "p"); auto p2 = pool.Get();
Print(p2, "p2"); auto p3 = pool.Get();
Print(p3, "p3"); pool.Init(, ); auto p4 = pool.Get<int>(); Print(p4, "p4");
getchar();
return ;
}
test.cpp
还有个半同步半异步的线程池,这个我看懂的多一点,就是用队列和信号量去实现多线程并发
#include <list>
#include <mutex>
#include <thread>
#include <condition_variable>
#include <iostream>
#include <functional>
#include <memory>
#include <atomic>
using namespace std; namespace itstation
{
template <typename T>
class SynaQueue
{
public:
SynaQueue(int maxSize)
: m_maxSize(maxSize), m_needStop(false)
{
} void Put(const T &x)
{
Add(x);
}
void Put(T &&x)
{
Add(forward<T>(x)); //完美转发,不改变参数的类型
}
void Take(list<T> &list)
{
std::unique_lock<mutex> locker(m_mutex);
// 判断式, 当都不满足条件时,条件变量会释放mutex, 并将线程置于waiting状态, 等待其他线程调用notify_one/all 将其唤醒。
// 当满足其中一个条件时继续执行, 将队列中的任务取出,唤醒等待添加任务的线程
// 当处于waiting状态的线程被唤醒时,先获取mutex,检查条件是否满足,满足-继续执行,否则释放mutex继续等待
m_notEmpty.wait(locker, [this] { return m_needStop || NotEmpty(); });
if (m_needStop)
return;
list = move(m_queue);
m_notFull.notify_one();
}
void Take(T &t)
{
unique_lock<mutex> locker(m_mutex); // 锁
m_notEmpty.wait(locker, [this] { return m_needStop || NotEmpty(); });
if (m_needStop)
return;
t = m_queue.front();
m_queue.pop_front();
m_notFull.notify_one();
}
void Stop()
{
{
lock_guard<mutex> locker(m_mutex);
m_needStop = true;
}
m_notFull.notify_all(); // 将所有等待的线程全部唤醒,被唤醒的进程检查m_needStop,为真,所有的线程退出执行
m_notEmpty.notify_all();
} private:
bool NotFull() const
{
bool full = m_queue.size() >= m_maxSize;
if (full)
cout << "缓冲区满了,需要等待。。。。" << endl;
return !full;
}
bool NotEmpty() const
{
bool empty = m_queue.empty();
if (empty)
cout << "缓冲区空了,需要等待,。。。异步层线程: " << this_thread::get_id() << endl;
return !empty;
} template <typename F>
void Add(F &&x)
{
unique_lock<mutex> locker(m_mutex); // 通过m_mutex获得写锁
m_notFull.wait(locker, [this] { return m_needStop || NotFull(); }); // 没有停止且满了,就释放m_mutex并waiting;有一个为真就继续执行
if (m_needStop)
return;
m_queue.push_back(forward<F>(x));
m_notEmpty.notify_one();
} private:
list<T> m_queue; //缓冲区
mutex m_mutex; // 互斥量
condition_variable m_notEmpty; // 条件变量
condition_variable m_notFull;
int m_maxSize; //同步队列最大的size
bool m_needStop; // 停止标识
}; const int MaxTaskCount = ;
class ThreadPool
{
public:
using Task = function<void()>;
ThreadPool(int numThread = thread::hardware_concurrency())
: m_queue(MaxTaskCount)
{
Start(numThread);
} virtual ~ThreadPool()
{
Stop();
} void Stop()
{
call_once(m_flag, [this] { StopThreadGroup(); });
} void AddTask(Task &&task)
{
m_queue.Put(forward<Task>(task));
} void AddTask(const Task &task)
{
m_queue.Put(task);
} private:
void Start(int numThreads)
{
m_running = true;
//创建线程组
for (int i = ; i < numThreads; i++)
{
m_threadgroup.emplace_back(make_shared<thread>(&ThreadPool::RunInThread, this));
}
} // 每个线程都执行这个函数
void RunInThread()
{
while (m_running)
{
//取任务分别执行
list<Task> list;
m_queue.Take(list);
for (auto &task : list)
{
if (!m_running)
return; task();
}
}
}
void StopThreadGroup()
{
m_queue.Stop(); // 同步队列中的线程停止
m_running = false; // 让内部线程跳出循环并推出
for (auto thread : m_threadgroup)
{
if (thread)
thread->join();
}
m_threadgroup.clear();
} private:
list<shared_ptr<thread>> m_threadgroup; // 处理任务的线程组, 链表中存储着指向线程的共享指针
SynaQueue<Task> m_queue; //同步队列
atomic_bool m_running; // 是否停止的标识
once_flag m_flag;
};
} // namespace itstation
ObjectPool.h
#include <stdio.h>
#include <iostream>
#include "ObjectPool.h"
#include <list>
using namespace std;
using namespace itstation; void TestThreadPool()
{
ThreadPool pool();
thread thd1([&pool] {
for (int i = ; i < ; i++)
{
auto thrID = this_thread::get_id();
pool.AddTask([thrID, i] {cout << "同步层线程1的线程ID:" << thrID << " 这是任务 " << i << endl; this_thread::sleep_for(chrono::seconds()); });
}
}); thread thd2([&pool] {
for (int i = ; i < ; i++)
{
auto thrID = this_thread::get_id();
pool.AddTask([thrID, i] {cout << "同步层线程2的线程ID:" << thrID << " 这是任务 " << i << endl; this_thread::sleep_for(chrono::seconds()); });
}
}); this_thread::sleep_for(chrono::seconds());
pool.Stop();
thd1.join();
thd2.join();
}
int main()
{
TestThreadPool(); getchar();
return ;
}
test.cpp