上篇文章讲述了什么是线程,以及在Linux系统下线程的相关操作
线程(Linux系统实现)_小梁今天敲代码了吗的博客-CSDN博客
本文将继续讲述线程的相关知识——线程同步
目录
1.线程同步的概念
2.线程不同步可能会发生什么
3.线程同步方式
4.互斥锁
申请一个互斥锁
尝试获取互斥锁
互斥锁解锁
互斥锁示例
线程同步是指在多线程编程中,为了保证多个线程按照某种特定的方式正确、有序地执行,需要进行线程间的协作与同步。在多线程编程中,当多个线程共享同一份资源时,由于线程的执行顺序是不确定的,因此会存在一些并发问题,如死锁、竞态条件、资源争用等问题。为了避免这些问题,需要对线程进行同步。线程同步实际上就是通过线程之间的协作,使得线程能够按照一定的顺序来访问共享资源,从而避免并发问题的发生。常用的线程同步机制有互斥锁、信号量、条件变量等。
线程不同步可能会导致以下问题:
1. 竞态条件(Race Condition):多个线程同时访问、修改一份共享资源,可能会导致资源的状态不确定,进而导致程序出现逻辑错误,甚至崩溃。
2. 死锁(Deadlock):多个线程在等待对方释放锁,导致所有线程都无法继续执行,程序陷入死循环,最终可能会崩溃。
3. 饥饿(Starvation):某些线程可能因为无法获取资源而一直等待,导致无法正常执行,进而影响整个程序的性能。
4. 资源争用(Resource Contention):多个线程同时竞争同一份资源,导致资源的使用效率下降,总体性能降低。
示例:两个线程交替数数(每个线程数 50 个数,交替数到 100)
#include
#include
#include
#include
#include
#include
#include
#define MAX 50
// 全局变量
int number;
// 线程处理函数
void* funcA_num(void* arg)
{
for(int i=0; i
在linux系统中编译,运行结果:
[itliang@localhost ~]$ ./xctb
Thread B, id = 140388304152320, number = 1
Thread A, id = 140388312545024, number = 1
Thread B, id = 140388304152320, number = 2
Thread A, id = 140388312545024, number = 2
Thread B, id = 140388304152320, number = 3
Thread A, id = 140388312545024, number = 3
Thread B, id = 140388304152320, number = 4
Thread A, id = 140388312545024, number = 4
Thread B, id = 140388304152320, number = 5
Thread A, id = 140388312545024, number = 5
Thread B, id = 140388304152320, number = 6
Thread B, id = 140388304152320, number = 7
Thread A, id = 140388312545024, number = 6
Thread B, id = 140388304152320, number = 7
Thread A, id = 140388312545024, number = 7
Thread A, id = 140388312545024, number = 8
Thread B, id = 140388304152320, number = 9
Thread B, id = 140388304152320, number = 10
Thread A, id = 140388312545024, number = 9
Thread A, id = 140388312545024, number = 10
Thread B, id = 140388304152320, number = 11
Thread B, id = 140388304152320, number = 12
Thread A, id = 140388312545024, number = 11
Thread A, id = 140388312545024, number = 12
Thread B, id = 140388304152320, number = 13
Thread A, id = 140388312545024, number = 13
Thread B, id = 140388304152320, number = 14
Thread B, id = 140388304152320, number = 15
Thread A, id = 140388312545024, number = 14
Thread B, id = 140388304152320, number = 15
Thread A, id = 140388312545024, number = 15
Thread A, id = 140388312545024, number = 16
Thread B, id = 140388304152320, number = 17
Thread B, id = 140388304152320, number = 18
Thread A, id = 140388312545024, number = 17
Thread A, id = 140388312545024, number = 18
Thread B, id = 140388304152320, number = 19
Thread A, id = 140388312545024, number = 19
Thread B, id = 140388304152320, number = 20
Thread B, id = 140388304152320, number = 21
Thread A, id = 140388312545024, number = 20
Thread A, id = 140388312545024, number = 21
Thread B, id = 140388304152320, number = 22
Thread B, id = 140388304152320, number = 23
Thread A, id = 140388312545024, number = 22
Thread A, id = 140388312545024, number = 23
Thread B, id = 140388304152320, number = 24
Thread B, id = 140388304152320, number = 25
Thread A, id = 140388312545024, number = 24
Thread B, id = 140388304152320, number = 25
Thread A, id = 140388312545024, number = 25
Thread A, id = 140388312545024, number = 26
Thread B, id = 140388304152320, number = 27
Thread B, id = 140388304152320, number = 28
Thread A, id = 140388312545024, number = 27
Thread A, id = 140388312545024, number = 28
Thread B, id = 140388304152320, number = 29
Thread A, id = 140388312545024, number = 29
Thread B, id = 140388304152320, number = 30
Thread B, id = 140388304152320, number = 31
Thread A, id = 140388312545024, number = 30
Thread A, id = 140388312545024, number = 31
Thread B, id = 140388304152320, number = 32
Thread B, id = 140388304152320, number = 33
Thread A, id = 140388312545024, number = 32
Thread A, id = 140388312545024, number = 33
Thread B, id = 140388304152320, number = 34
Thread B, id = 140388304152320, number = 35
Thread A, id = 140388312545024, number = 34
Thread A, id = 140388312545024, number = 35
Thread B, id = 140388304152320, number = 36
Thread B, id = 140388304152320, number = 37
Thread A, id = 140388312545024, number = 36
Thread A, id = 140388312545024, number = 37
Thread B, id = 140388304152320, number = 38
Thread B, id = 140388304152320, number = 39
Thread A, id = 140388312545024, number = 38
Thread A, id = 140388312545024, number = 39
Thread B, id = 140388304152320, number = 40
Thread B, id = 140388304152320, number = 41
Thread A, id = 140388312545024, number = 40
Thread A, id = 140388312545024, number = 41
Thread B, id = 140388304152320, number = 42
Thread B, id = 140388304152320, number = 43
Thread A, id = 140388312545024, number = 42
Thread A, id = 140388312545024, number = 43
Thread B, id = 140388304152320, number = 44
Thread B, id = 140388304152320, number = 45
Thread A, id = 140388312545024, number = 44
Thread A, id = 140388312545024, number = 45
Thread B, id = 140388304152320, number = 46
Thread B, id = 140388304152320, number = 47
Thread A, id = 140388312545024, number = 46
Thread A, id = 140388312545024, number = 47
Thread B, id = 140388304152320, number = 48
Thread A, id = 140388312545024, number = 48
Thread B, id = 140388304152320, number = 49
Thread B, id = 140388304152320, number = 50
Thread A, id = 140388312545024, number = 49
Thread A, id = 140388312545024, number = 50
通过对上面例子的测试,可以看出虽然每个线程内部循环了 50 次每次数一个数,但是最终没有数到 100,通过输出的结果可以看到,有些数字被重复数了多次,其原因就是没有对线程进行同步处理,造成了数据的混乱。
线程同步方式有以下几种:
1. 互斥锁(Mutex):使用互斥锁来控制多个线程对共享资源的访问。只有获得锁的线程才能进入临界区进行操作,其他线程必须等待锁释放后才能进入。
2. 读写锁(Read-Write Lock):允许多个线程同时读取共享资源,但只允许一个线程写入共享资源。读写锁可以提高程序的并发性能,减少资源争用问题。
3. 条件变量(Condition Variable):用于等待特定条件的发生。当某个线程等待某个条件变量时,它会被阻塞,直到其他线程发出信号,通知条件变量已经满足。
4. 信号量(Semaphore):使用信号量来控制多个线程对有限数量资源的访问。信号量表示资源的数量,每个线程在使用完资源后必须释放信号量,以便其他线程可以使用资源。
以上是常见的几种线程同步方式,每种方式都有其适用的场景和优缺点,根据具体的应用场景选择适合的同步方式是非常重要的,这里先介绍互斥锁。
互斥锁是线程同步最常用的一种方式,通过互斥锁可以锁定一个代码块,被锁定的这个代码块,所有的线程只能顺序执行 (不能并行处理),这样多线程访问共享资源数据混乱的问题就可以被解决了,需要付出的代价就是执行效率的降低,因为默认临界区多个线程是可以并行处理的,现在只能串行处理。
在 Linux 中互斥锁的类型为 pthread_mutex_t,创建一个这种类型的变量就得到了一把互斥锁:
pthread_mutex_t mutex;
在创建的锁对象中保存了当前这把锁的状态信息:锁定还是打开,如果是锁定状态还记录了给这把锁加锁的线程信息(线程 ID)。一个互斥锁变量只能被一个线程锁定,被锁定之后其他线程再对互斥锁变量加锁就会被阻塞,直到这把互斥锁被解锁,被阻塞的线程才能被解除阻塞。一般情况下,每一个共享资源对应一个把互斥锁,锁的个数和线程的个数无关。
Linux 提供的互斥锁操作函数如下,如果函数调用成功会返回 0,调用失败会返回相应的错误号:
// 初始化互斥锁
// restrict: 是一个关键字, 用来修饰指针, 只有这个关键字修饰的指针可以访问指向的内存地址, 其他指针是不行的
int pthread_mutex_init(pthread_mutex_t *restrict mutex,
const pthread_mutexattr_t *restrict attr);
// 释放互斥锁资源
int pthread_mutex_destroy(pthread_mutex_t *mutex);
//mutex: 互斥锁变量的地址
//attr: 互斥锁的属性,一般使用默认属性即可,这个参数指定为 NULL
修改互斥锁的状态, 将其设定为锁定状态, 这个状态被写入到参数 mutex 中
int pthread_mutex_lock(pthread_mutex_t *mutex);
这个函数被调用,首先会判断参数 mutex 互斥锁中的状态是不是锁定状态:
没有被锁定,是打开的,这个线程可以加锁成功,这个这个锁中会记录是哪个线程加锁成功
如果被锁定了,其他线程加锁就失败了,这些线程都会阻塞在这把锁上
当这把锁被解开之后,这些阻塞在锁上的线程就解除阻塞了,并且这些线程是通过竞争的方式对这把锁加锁,没抢到锁的线程继续阻塞
下面这个函数是尝试获取一个互斥锁。如果当前的锁没有被其他线程占用,则该函数会立即返回,线程成功获取锁,并返回0。否则,该函数会立即返回,线程不会阻塞,直接返回EBUSY错误码。
// 尝试加锁
int pthread_mutex_trylock(pthread_mutex_t *mutex);
使用pthread_mutex_trylock
函数获取锁的好处是,在获取锁的过程中不会引起线程阻塞,避免了由于长时间阻塞而导致的程序性能下降或死锁问题。但是,需要注意的是,在使用pthread_mutex_trylock
函数时,如果获取锁失败,则需要有相应的处理措施来处理获取锁失败的情况。
通过调用pthread_mutex_unlock()函数将占用的互斥锁释放,以便其他线程可以竞争和访问共享资源。如果未正确解锁互斥锁,则可能会导致死锁或其他线程无法访问共享资源。因此,正确使用互斥锁是确保多线程代码正确运行的关键之一。
// 对互斥锁解锁
int pthread_mutex_unlock(pthread_mutex_t *mutex);
我们可以将上面多线程交替数数的例子修改一下,使用互斥锁进行线程同步。两个线程一共操作了同一个全局变量,因此需要添加一互斥锁,来控制这两个线程。
#include
#include
#include
#include
#include
#include
#include
#define MAX 100
// 全局变量
int number;
// 创建一把互斥锁
// 全局变量, 多个线程共享
pthread_mutex_t mutex;
// 线程处理函数
void* funcA_num(void* arg)
{
for(int i=0; i
linux系统运行结果:
[itliang@localhost ~]$ ./xctb
Thread A, id = 139912715360000, number = 1
Thread A, id = 139912715360000, number = 2
Thread A, id = 139912715360000, number = 3
Thread A, id = 139912715360000, number = 4
Thread A, id = 139912715360000, number = 5
Thread A, id = 139912715360000, number = 6
Thread A, id = 139912715360000, number = 7
Thread A, id = 139912715360000, number = 8
Thread A, id = 139912715360000, number = 9
Thread A, id = 139912715360000, number = 10
Thread A, id = 139912715360000, number = 11
Thread A, id = 139912715360000, number = 12
Thread A, id = 139912715360000, number = 13
Thread A, id = 139912715360000, number = 14
Thread A, id = 139912715360000, number = 15
Thread A, id = 139912715360000, number = 16
Thread A, id = 139912715360000, number = 17
Thread A, id = 139912715360000, number = 18
Thread A, id = 139912715360000, number = 19
Thread A, id = 139912715360000, number = 20
Thread A, id = 139912715360000, number = 21
Thread A, id = 139912715360000, number = 22
Thread A, id = 139912715360000, number = 23
Thread A, id = 139912715360000, number = 24
Thread A, id = 139912715360000, number = 25
Thread A, id = 139912715360000, number = 26
Thread A, id = 139912715360000, number = 27
Thread A, id = 139912715360000, number = 28
Thread A, id = 139912715360000, number = 29
Thread A, id = 139912715360000, number = 30
Thread A, id = 139912715360000, number = 31
Thread A, id = 139912715360000, number = 32
Thread A, id = 139912715360000, number = 33
Thread A, id = 139912715360000, number = 34
Thread A, id = 139912715360000, number = 35
Thread A, id = 139912715360000, number = 36
Thread A, id = 139912715360000, number = 37
Thread A, id = 139912715360000, number = 38
Thread A, id = 139912715360000, number = 39
Thread A, id = 139912715360000, number = 40
Thread A, id = 139912715360000, number = 41
Thread A, id = 139912715360000, number = 42
Thread A, id = 139912715360000, number = 43
Thread A, id = 139912715360000, number = 44
Thread A, id = 139912715360000, number = 45
Thread A, id = 139912715360000, number = 46
Thread A, id = 139912715360000, number = 47
Thread A, id = 139912715360000, number = 48
Thread A, id = 139912715360000, number = 49
Thread A, id = 139912715360000, number = 50
Thread B, id = 139912706967296, number = 51
Thread B, id = 139912706967296, number = 52
Thread B, id = 139912706967296, number = 53
Thread B, id = 139912706967296, number = 54
Thread B, id = 139912706967296, number = 55
Thread B, id = 139912706967296, number = 56
Thread B, id = 139912706967296, number = 57
Thread B, id = 139912706967296, number = 58
Thread B, id = 139912706967296, number = 59
Thread B, id = 139912706967296, number = 60
Thread B, id = 139912706967296, number = 61
Thread B, id = 139912706967296, number = 62
Thread B, id = 139912706967296, number = 63
Thread B, id = 139912706967296, number = 64
Thread B, id = 139912706967296, number = 65
Thread B, id = 139912706967296, number = 66
Thread B, id = 139912706967296, number = 67
Thread B, id = 139912706967296, number = 68
Thread B, id = 139912706967296, number = 69
Thread B, id = 139912706967296, number = 70
Thread B, id = 139912706967296, number = 71
Thread B, id = 139912706967296, number = 72
Thread B, id = 139912706967296, number = 73
Thread B, id = 139912706967296, number = 74
Thread B, id = 139912706967296, number = 75
Thread B, id = 139912706967296, number = 76
Thread B, id = 139912706967296, number = 77
Thread B, id = 139912706967296, number = 78
Thread B, id = 139912706967296, number = 79
Thread B, id = 139912706967296, number = 80
Thread B, id = 139912706967296, number = 81
Thread B, id = 139912706967296, number = 82
Thread B, id = 139912706967296, number = 83
Thread B, id = 139912706967296, number = 84
Thread B, id = 139912706967296, number = 85
Thread B, id = 139912706967296, number = 86
Thread B, id = 139912706967296, number = 87
Thread B, id = 139912706967296, number = 88
Thread B, id = 139912706967296, number = 89
Thread B, id = 139912706967296, number = 90
Thread B, id = 139912706967296, number = 91
Thread B, id = 139912706967296, number = 92
Thread B, id = 139912706967296, number = 93
Thread B, id = 139912706967296, number = 94
Thread B, id = 139912706967296, number = 95
Thread B, id = 139912706967296, number = 96
Thread B, id = 139912706967296, number = 97
Thread B, id = 139912706967296, number = 98
Thread B, id = 139912706967296, number = 99
Thread B, id = 139912706967296, number = 100