线程池是较为底层的组件,平时我们在开发的过程中,可能更多的是调用这些组件的接口。对于服务器而言,这些底层的组件代码是很通用的。线程池主要用在写日志、计算结果、增删改查中。
线程池主要是由任务队列、执行队列和池管理组件构成,这里直接给出代码。
#define LL_ADD(item, list) do
{
item->prev = NULL;
item->next = list;
list = item;
} while(0)
#define LL_REMOVE(item, list) do
{
if (item->prev != NULL) item->prev->next = item->next;
if (item->next != NULL) item->next->prev = item->prev;
if (list == item) list = item->next;
item->prev = item->next = NULL;
} while(0)
typedef struct NWORKER
{
pthread_t thread;
int terminate;
struct NWORKQUEUE *workqueue;
struct NWORKER *prev;
struct NWORKER *next;
} nWorker;
typedef struct NJOB
{
void (*job_function)(struct NJOB *job);
void *user_data;
struct NJOB *prev;
struct NJOB *next;
} nJob;
typedef struct NWORKQUEUE
{
struct NWORKER *workers;
struct NJOB *waiting_jobs;
pthread_mutex_t jobs_mtx;
pthread_cond_t jobs_cond;
} nWorkQueue;
typedef nWorkQueue nThreadPool;
static void *ntyWorkerThread(void *ptr)
{
nWorker *worker = (nWorker*)ptr;
while (1)
{
pthread_mutex_lock(&worker->workqueue->jobs_mtx);
while (worker->workqueue->waiting_jobs == NULL)
{
if (worker->terminate) break;
pthread_cond_wait(&worker->workqueue->jobs_cond, &worker->workqueue->jobs_mtx);
}
if (worker->terminate)
{
pthread_mutex_unlock(&worker->workqueue->jobs_mtx);
break;
}
nJob *job = worker->workqueue->waiting_jobs;
if (job != NULL)
{
LL_REMOVE(job, worker->workqueue->waiting_jobs);
}
pthread_mutex_unlock(&worker->workqueue->jobs_mtx);
if (job == NULL) continue;
job->job_function(job);
}
free(worker);
pthread_exit(NULL);
}
int ntyThreadPoolCreate(nThreadPool *workqueue, int numWorkers)
{
if (numWorkers < 1) numWorkers = 1;
memset(workqueue, 0, sizeof(nThreadPool));
pthread_cond_t blank_cond = PTHREAD_COND_INITIALIZER;
memcpy(&workqueue->jobs_cond, &blank_cond, sizeof(workqueue->jobs_cond));
pthread_mutex_t blank_mutex = PTHREAD_MUTEX_INITIALIZER;
memcpy(&workqueue->jobs_mtx, &blank_mutex, sizeof(workqueue->jobs_mtx));
int i = 0;
for (i = 0;i < numWorkers;i ++)
{
nWorker *worker = (nWorker*)malloc(sizeof(nWorker));
if (worker == NULL)
{
perror("malloc");
return 1;
}
memset(worker, 0, sizeof(nWorker));
worker->workqueue = workqueue;
int ret = pthread_create(&worker->thread, NULL, ntyWorkerThread, (void *)worker);
if (ret)
{
perror("pthread_create");
free(worker);
return 1;
}
LL_ADD(worker, worker->workqueue->workers);
}
return 0;
}
void ntyThreadPoolShutdown(nThreadPool *workqueue)
{
nWorker *worker = NULL;
for (worker = workqueue->workers;worker != NULL;worker = worker->next)
{
worker->terminate = 1;
}
pthread_mutex_lock(&workqueue->jobs_mtx);
workqueue->workers = NULL;
workqueue->waiting_jobs = NULL;
pthread_cond_broadcast(&workqueue->jobs_cond);
pthread_mutex_unlock(&workqueue->jobs_mtx);
}
void ntyThreadPoolQueue(nThreadPool *workqueue, nJob *job)
{
pthread_mutex_lock(&workqueue->jobs_mtx);
LL_ADD(job, workqueue->waiting_jobs);
pthread_cond_signal(&workqueue->jobs_cond);
pthread_mutex_unlock(&workqueue->jobs_mtx);
}
代码中有几点需要解释,一是对链表的操作使用了宏函数,因为这样可以避免因为数据类型不同而需要定义多个函数的问题,二是互斥锁和条件变量的初始化方法,这里用的静态初始化方法,却避免了变量在定义好后不能用静态初始化赋值的问题。
这里再啰嗦一点,服务器的处理流程,一是检测IO事件是否就绪,二是对IO进行读写操作,三是对数据进行解析和操作。这三步分别对应epoll、recv()/send()、parse。因此,服务器有三种做法,一是单线程做法,一个线程处理以上三步,二是把IO读写和解析都放在线程池中处理,三是只把解析过程放在线程池中,读写IO还是由单线程处理。以上三种做法中,第二种方法服务器响应最快,但是有个问题,就是多个线程会共用一个fd。想象这样一个情况,线程池中有两个任务,操作的都是同一fd,而这两个任务分配给了两个线程,那么这两个线程如果同时发数据,就会出现脏数据的现象,或者是,一个线程正在收发数据,另一个线程却调用了close(),导致崩溃。第二个方法适用于针对fd操作时间较长的情景,而第三种方法适用于针对业务处理时间较长的情形。



