【并发编程】【18】【共享模型之工具】JUC Semaphore CountDownLatch CyclicBarrier 线程安全集合类
8. 共享模型之工具
8.2 J.U.C
4. Semaphore
基本使用
[ˈsɛməˌfɔr] 信号量，用来限制能同时访问共享资源的线程上限。
public static void main(String[] args) {
// 1. 创建 semaphore 对象
Semaphore semaphore = new Semaphore(3);
// 2. 10个线程同时运行
for (int i = 0; i < 10; i++) {
new Thread(() -> {
// 3. 获取许可
try {
semaphore.acquire();
} catch (InterruptedException e) {
e.printStackTrace();
}
try {
log.debug("running...");
sleep(1);
log.debug("end...");
} finally {
// 4. 释放许可
semaphore.release();
}
}).start();
}
}
输出
07:35:15.485 c.TestSemaphore [Thread-2] - running...
07:35:15.485 c.TestSemaphore [Thread-1] - running...
07:35:15.485 c.TestSemaphore [Thread-0] - running...
07:35:16.490 c.TestSemaphore [Thread-2] - end...
07:35:16.490 c.TestSemaphore [Thread-0] - end...
07:35:16.490 c.TestSemaphore [Thread-1] - end...
07:35:16.490 c.TestSemaphore [Thread-3] - running...
07:35:16.490 c.TestSemaphore [Thread-5] - running...
07:35:16.490 c.TestSemaphore [Thread-4] - running...
07:35:17.490 c.TestSemaphore [Thread-5] - end...
07:35:17.490 c.TestSemaphore [Thread-4] - end...
07:35:17.490 c.TestSemaphore [Thread-3] - end...
07:35:17.490 c.TestSemaphore [Thread-6] - running...
07:35:17.490 c.TestSemaphore [Thread-7] - running...
07:35:17.490 c.TestSemaphore [Thread-9] - running...
07:35:18.491 c.TestSemaphore [Thread-6] - end...
07:35:18.491 c.TestSemaphore [Thread-7] - end...
07:35:18.491 c.TestSemaphore [Thread-9] - end...
07:35:18.491 c.TestSemaphore [Thread-8] - running...
07:35:19.492 c.TestSemaphore [Thread-8] - end...
*Semaphore 应用
2. 限制对共享资源的使用
semaphore 实现
-
使用 Semaphore 限流，在访问高峰期时，让请求线程阻塞，高峰期过去再释放许可，当然它只适合限制单机线程数量，并且仅是限制线程数，而不是限制资源数（例如连接数，请对比 Tomcat LimitLatch 的实现）
-
用 Semaphore 实现简单连接池，对比『享元模式』下的实现（用wait notify），性能和可读性显然更好，注意下面的实现中线程数和数据库连接数是相等的
@Slf4j(topic = "c.Pool")
class Pool {
// 1. 连接池大小
private final int poolSize;
// 2. 连接对象数组
private Connection[] connections;
// 3. 连接状态数组 0 表示空闲， 1 表示繁忙
private AtomicIntegerArray states;
private Semaphore semaphore;
// 4. 构造方法初始化
public Pool(int poolSize) {
this.poolSize = poolSize;
// 让许可数与资源数一致
this.semaphore = new Semaphore(poolSize);
this.connections = new Connection[poolSize];
this.states = new AtomicIntegerArray(new int[poolSize]);
for (int i = 0; i < poolSize; i++) {
connections[i] = new MockConnection("连接" + (i+1));
}
}
// 5. 借连接
public Connection borrow() {// t1, t2, t3
// 获取许可
try {
semaphore.acquire(); // 没有许可的线程，在此等待
} catch (InterruptedException e) {
e.printStackTrace();
}
for (int i = 0; i < poolSize; i++) {
// 获取空闲连接
if(states.get(i) == 0) {
if (states.compareAndSet(i, 0, 1)) {
log.debug("borrow {}", connections[i]);
return connections[i];
}
}
}
// 不会执行到这里
return null;
}
// 6. 归还连接
public void free(Connection conn) {
for (int i = 0; i < poolSize; i++) {
if (connections[i] == conn) {
states.set(i, 0);
log.debug("free {}", conn);
semaphore.release();
break;
}
}
}
}
* Semaphore 原理
1. 加锁解锁流程
Semaphore 有点像一个停车场，permits 就好像停车位数量，当线程获得了 permits 就像是获得了停车位，然后停车场显示空余车位减一
刚开始，permits（state）为 3，这时 5 个线程来获取资源
假设其中 Thread-1，Thread-2，Thread-4 cas 竞争成功，而 Thread-0 和 Thread-3 竞争失败，进入 AQS 队列park 阻塞
这时 Thread-4 释放了 permits，状态如下
接下来 Thread-0 竞争成功，permits 再次设置为 0，设置自己为 head 节点，断开原来的 head 节点，unpark 接下来的 Thread-3 节点，但由于 permits 是 0，因此 Thread-3 在尝试不成功后再次进入 park 状态
2. 源码分析
static final class NonfairSync extends Sync {
private static final long serialVersionUID = -2694183684443567898L;
NonfairSync(int permits) {
// permits 即 state
super(permits);
}
// Semaphore 方法, 方便阅读, 放在此处
public void acquire() throws InterruptedException {
sync.acquireSharedInterruptibly(1);
}
// AQS 继承过来的方法, 方便阅读, 放在此处
public final void acquireSharedInterruptibly(int arg)
throws InterruptedException {
if (Thread.interrupted())
throw new InterruptedException();
if (tryAcquireShared(arg) < 0)
doAcquireSharedInterruptibly(arg);
}
// 尝试获得共享锁
protected int tryAcquireShared(int acquires) {
return nonfairTryAcquireShared(acquires);
}
// Sync 继承过来的方法, 方便阅读, 放在此处
final int nonfairTryAcquireShared(int acquires) {
for (;;) {
int available = getState();
int remaining = available - acquires;
if (
// 如果许可已经用完, 返回负数, 表示获取失败, 进入 doAcquireSharedInterruptibly
remaining < 0 ||
// 如果 cas 重试成功, 返回正数, 表示获取成功
compareAndSetState(available, remaining)
) {
return remaining;
}
}
}
// AQS 继承过来的方法, 方便阅读, 放在此处
private void doAcquireSharedInterruptibly(int arg) throws InterruptedException {
final Node node = addWaiter(Node.SHARED);
boolean failed = true;
try {
for (;;) {
final Node p = node.predecessor();
if (p == head) {
// 再次尝试获取许可
int r = tryAcquireShared(arg);
if (r >= 0) {
// 成功后本线程出队（AQS）, 所在 Node设置为 head
// 如果 head.waitStatus == Node.SIGNAL ==> 0 成功, 下一个节点 unpark
// 如果 head.waitStatus == 0 ==> Node.PROPAGATE
// r 表示可用资源数, 为 0 则不会继续传播
setHeadAndPropagate(node, r);
p.next = null; // help GC
failed = false;
return;
}
}
// 不成功, 设置上一个节点 waitStatus = Node.SIGNAL, 下轮进入 park 阻塞
if (shouldParkAfterFailedAcquire(p, node) &&
parkAndCheckInterrupt())
throw new InterruptedException();
}
} finally {
if (failed)
cancelAcquire(node);
}
}
// Semaphore 方法, 方便阅读, 放在此处
public void release() {
sync.releaseShared(1);
}
// AQS 继承过来的方法, 方便阅读, 放在此处
public final boolean releaseShared(int arg) {
if (tryReleaseShared(arg)) {
doReleaseShared();
return true;
}
return false;
}
// Sync 继承过来的方法, 方便阅读, 放在此处
protected final boolean tryReleaseShared(int releases) {
for (;;) {
int current = getState();
int next = current + releases;
if (next < current) // overflow
throw new Error("Maximum permit count exceeded");
if (compareAndSetState(current, next))
return true;
}
}
}
5. CountdownLatch（倒计时锁）
用来进行线程同步协作，等待所有线程完成倒计时。
其中构造参数用来初始化等待计数值，await() 用来等待计数归零，countDown() 用来让计数减一
public static void main(String[] args) throws InterruptedException {
CountDownLatch latch = new CountDownLatch(3);
new Thread(() -> {
log.debug("begin...");
sleep(1);
latch.countDown();
log.debug("end...{}", latch.getCount());
}).start();
new Thread(() -> {
log.debug("begin...");
sleep(2);
latch.countDown();
log.debug("end...{}", latch.getCount());
}).start();
new Thread(() -> {
log.debug("begin...");
sleep(1.5);
latch.countDown();
log.debug("end...{}", latch.getCount());
}).start();
log.debug("waiting...");
latch.await();
log.debug("wait end...");
}
输出
18:44:00.778 c.TestCountDownLatch [main] - waiting...
18:44:00.778 c.TestCountDownLatch [Thread-2] - begin...
18:44:00.778 c.TestCountDownLatch [Thread-0] - begin...
18:44:00.778 c.TestCountDownLatch [Thread-1] - begin...
18:44:01.782 c.TestCountDownLatch [Thread-0] - end...2
18:44:02.283 c.TestCountDownLatch [Thread-2] - end...1
18:44:02.782 c.TestCountDownLatch [Thread-1] - end...0
18:44:02.782 c.TestCountDownLatch [main] - wait end...
可以配合线程池使用，改进如下
public static void main(String[] args) throws InterruptedException {
CountDownLatch latch = new CountDownLatch(3);
ExecutorService service = Executors.newFixedThreadPool(4);
service.submit(() -> {
log.debug("begin...");
sleep(1);
latch.countDown();
log.debug("end...{}", latch.getCount());
});
service.submit(() -> {
log.debug("begin...");
sleep(1.5);
latch.countDown();
log.debug("end...{}", latch.getCount());
});
service.submit(() -> {
log.debug("begin...");
sleep(2);
latch.countDown();
log.debug("end...{}", latch.getCount());
});
service.submit(()->{
try {
log.debug("waiting...");
latch.await();
log.debug("wait end...");
} catch (InterruptedException e) {
e.printStackTrace();
}
});
}
输出
18:52:25.831 c.TestCountDownLatch [pool-1-thread-3] - begin...
18:52:25.831 c.TestCountDownLatch [pool-1-thread-1] - begin...
18:52:25.831 c.TestCountDownLatch [pool-1-thread-2] - begin...
18:52:25.831 c.TestCountDownLatch [pool-1-thread-4] - waiting...
18:52:26.835 c.TestCountDownLatch [pool-1-thread-1] - end...2
18:52:27.335 c.TestCountDownLatch [pool-1-thread-2] - end...1
18:52:27.835 c.TestCountDownLatch [pool-1-thread-3] - end...0
18:52:27.835 c.TestCountDownLatch [pool-1-thread-4] - wait end...
* 应用之同步等待多线程准备完毕
AtomicInteger num = new AtomicInteger(0);
ExecutorService service = Executors.newFixedThreadPool(10, (r) -> {
return new Thread(r, "t" + num.getAndIncrement());
});
CountDownLatch latch = new CountDownLatch(10);
String[] all = new String[10];
Random r = new Random();
for (int j = 0; j < 10; j++) {
int x = j;
service.submit(() -> {
for (int i = 0; i <= 100; i++) {
try {
Thread.sleep(r.nextInt(100));
} catch (InterruptedException e) {
}
all[x] = Thread.currentThread().getName() + "(" + (i + "%") + ")";
System.out.print("\r" + Arrays.toString(all));
}
latch.countDown();
});
}
latch.await();
System.out.println("\n游戏开始...");
service.shutdown();
中间输出
[t0(52%), t1(47%), t2(51%), t3(40%), t4(49%), t5(44%), t6(49%), t7(52%), t8(46%), t9(46%)]
最后输出
[t0(100%), t1(100%), t2(100%), t3(100%), t4(100%), t5(100%), t6(100%), t7(100%), t8(100%),
t9(100%)]
游戏开始...
* 应用之同步等待多个远程调用结束
@RestController
public class TestCountDownlatchController {
@GetMapping("/order/{id}")
public Map<String, Object> order(@PathVariable int id) {
HashMap<String, Object> map = new HashMap<>();
map.put("id", id);
map.put("total", "2300.00");
sleep(2000);
return map;
}
@GetMapping("/product/{id}")
public Map<String, Object> product(@PathVariable int id) {
HashMap<String, Object> map = new HashMap<>();
if (id == 1) {
map.put("name", "小爱音箱");
map.put("price", 300);
} else if (id == 2) {
map.put("name", "小米手机");
map.put("price", 2000);
}
map.put("id", id);
sleep(1000);
return map;
}
@GetMapping("/logistics/{id}")
public Map<String, Object> logistics(@PathVariable int id) {
HashMap<String, Object> map = new HashMap<>();
map.put("id", id);
map.put("name", "中通快递");
sleep(2500);
return map;
}
private void sleep(int millis) {
try {
Thread.sleep(millis);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
rest 远程调用
RestTemplate restTemplate = new RestTemplate();
log.debug("begin");
ExecutorService service = Executors.newCachedThreadPool();
CountDownLatch latch = new CountDownLatch(4);
Future<Map<String,Object>> f1 = service.submit(() -> {
Map<String, Object> r =
restTemplate.getForObject("http://localhost:8080/order/{1}", Map.class, 1);
return r;
});
Future<Map<String, Object>> f2 = service.submit(() -> {
Map<String, Object> r =
restTemplate.getForObject("http://localhost:8080/product/{1}", Map.class, 1);
return r;
});
Future<Map<String, Object>> f3 = service.submit(() -> {
Map<String, Object> r =
restTemplate.getForObject("http://localhost:8080/product/{1}", Map.class, 2);
return r;
});
Future<Map<String, Object>> f4 = service.submit(() -> {
Map<String, Object> r =
restTemplate.getForObject("http://localhost:8080/logistics/{1}", Map.class, 1);
return r;
});
System.out.println(f1.get());
System.out.println(f2.get());
System.out.println(f3.get());
System.out.println(f4.get());
log.debug("执行完毕");
service.shutdown();
执行结果（有返回值的多线程用Future更方便，CountDownLatch更适合无返回值的多线程同步）
19:51:39.711 c.TestCountDownLatch [main] - begin
{total=2300.00, id=1}
{price=300, name=小爱音箱, id=1}
{price=2000, name=小米手机, id=2}
{name=中通快递, id=1}
19:51:42.407 c.TestCountDownLatch [main] - 执行完毕
6. CyclicBarrier
[ˈsaɪklɪk ˈbæriɚ] 循环栅栏，用来进行线程协作，等待线程满足某个计数。构造时设置『计数个数』，每个线程执行到某个需要“同步”的时刻调用 await() 方法进行等待，当等待的线程数满足『计数个数』时，继续执行
CyclicBarrier cb = new CyclicBarrier(2, () -> {
log.debug("task1, task2 finish...")
}); // 个数为2时才会继续执行
new Thread(()->{
System.out.println("线程1开始.."+new Date());
try {
cb.await(); // 当个数不足时，等待
} catch (InterruptedException | BrokenBarrierException e) {
e.printStackTrace();
}
System.out.println("线程1继续向下运行..."+new Date());
}).start();
new Thread(()->{
System.out.println("线程2开始.."+new Date());
try { Thread.sleep(2000); } catch (InterruptedException e) { }
try {
cb.await(); // 2 秒后，线程个数够2，继续运行
} catch (InterruptedException | BrokenBarrierException e) {
e.printStackTrace();
}
System.out.println("线程2继续向下运行..."+new Date());
}).start();
注意 CyclicBarrier 与 CountDownLatch 的主要区别在于 CyclicBarrier 是可以重用的 CyclicBarrier 可以被比喻为『人满发车』
线程池数与CyclicBarrier参数1一致，不然得不到我们想要的效果
public static void main(String[] args) {
ExecutorService service = Executors.newFixedThreadPool(2);
CyclicBarrier barrier = new CyclicBarrier(2, ()-> {
log.debug("task1, task2 finish...");
});
for (int i = 0; i < 3; i++) { // task1 task2 task1
service.submit(() -> {
log.debug("task1 begin...");
sleep(1);
try {
barrier.await(); // 2-1=1
} catch (InterruptedException | BrokenBarrierException e) {
e.printStackTrace();
}
});
service.submit(() -> {
log.debug("task2 begin...");
sleep(2);
try {
barrier.await(); // 1-1=0
} catch (InterruptedException | BrokenBarrierException e) {
e.printStackTrace();
}
});
}
service.shutdown();
}
7. 线程安全集合类概述
线程安全集合类可以分为三大类：
-
遗留的线程安全集合如 Hashtable ， Vector
-
使用 Collections 装饰的线程安全集合，如：（装饰器模式）
- Collections.synchronizedCollection
- Collections.synchronizedList
- Collections.synchronizedMap
- Collections.synchronizedSet
- Collections.synchronizedNavigableMap
- Collections.synchronizedNavigableSet
- Collections.synchronizedSortedMap
- Collections.synchronizedSortedSet
-
java.util.concurrent.*
重点介绍 java.util.concurrent.* 下的线程安全集合类，可以发现它们有规律，里面包含三类关键词：Blocking、CopyOnWrite、Concurrent
-
Blocking 大部分实现基于锁，并提供用来阻塞的方法（不满足条件阻塞，一般使用ReentrantLock实现）
-
CopyOnWrite 之类容器修改开销相对较重（修改时拷贝，适用于读多写少的场景）
-
Concurrent 类型的容器**（建议使用）**
- 内部很多操作使用 cas 优化，一般可以提供较高吞吐量
- 弱一致性
- 遍历时弱一致性，例如，当利用迭代器遍历时，如果容器发生修改，迭代器仍然可以继续进行遍历，这时内容是旧的
- 求大小弱一致性，size 操作未必是 100% 准确
- 读取弱一致性
遍历时如果发生了修改，对于非安全容器（集合）来讲，使用 fail-fast（相反概念 fail-safe ） 机制也就是让遍历立刻失败，抛出ConcurrentModifificationException，不再继续遍历