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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。

java
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();
            //对于非打断式获取，如果此过程中被打断，线程依旧会等到获取了信号量之后才进入catch块。
            //catch块中的线程依旧持有信号量，捕获该异常后catch块可以不做任何处理。
            } 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

sh
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...

说明：

  • Semaphore有两个构造器：Semaphore(int permits)和Semaphore(int permits,boolean fair)
  • permits表示允许同时访问共享资源的线程数。
  • fair表示公平与否，与之前的ReentrantLock一样。

​

semaphore 限制对共享资源的使用

  • 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【分布式不适用】，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
java
@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;
            }
        }
    }
}

​

CountdownLatch ​

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

java
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

sh
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...

相比于join，CountDownLatch能配合线程池使用。

java
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();
        }
    });
}

​

应用之同步等待多线程准备完毕

java
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 {
                //随机休眠，模拟网络延迟
                Thread.sleep(r.nextInt(100));
            } catch (InterruptedException e) {
            }
            all[x] = Thread.currentThread().getName() + "(" + (i + "%") + ")";
            //\r可以让当前输出覆盖上一次的输出。
            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

sh
[t0(52%), t1(47%), t2(51%), t3(40%), t4(49%), t5(44%), t6(49%), t7(52%), t8(46%), t9(46%)]

最后输出

sh
[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

java
@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

java
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

sh
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

说明：

  • 这种等待多个带有返回值的任务的场景，还是用future比较合适，CountdownLatch适合任务没有返回值的场景。

CyclicBarrier ​

CountdownLatch的缺点在于不能重用，见下：

java
private static void test1() {
    ExecutorService service = Executors.newFixedThreadPool(5);
    for (int i = 0; i < 3; i++) {
        CountDownLatch latch = new CountDownLatch(2);
        service.submit(() -> {
            log.debug("task1 start...");
            sleep(1);
            latch.countDown();
        });
        service.submit(() -> {
            log.debug("task2 start...");
            sleep(2);
            latch.countDown();
        });
        try {
            latch.await();
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
        log.debug("task1 task2 finish...");
    }
    service.shutdown();
}

想要重复使用CountdownLatch进行同步，必须创建多个CountDownLatch对象。

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

java
CyclicBarrier cb = new CyclicBarrier(2); // 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』
  • CountDownLatch的计数和阻塞方法是分开的两个方法，而CyclicBarrier是一个方法。
  • CyclicBarrier的构造器还有一个Runnable类型的参数，在计数为0时会执行其中的run方法。

StampedLock ​

该类自 JDK 8 加入，是为了进一步优化读性能，它的特点是在使用读锁、写锁时都必须配合【戳】使用加解读锁

java
long stamp = lock.readLock();
lock.unlockRead(stamp);

加解写锁

java
long stamp = lock.writeLock();
lock.unlockWrite(stamp);

乐观读，StampedLock 支持 tryOptimisticRead() 方法（乐观读），读取完毕后需要做一次 戳校验 如果校验通过，表示这期间确实没有写操作，数据可以安全使用，如果校验没通过，需要重新获取读锁，保证数据安全。

java
long stamp = lock.tryOptimisticRead();
// 验戳
if(!lock.validate(stamp)){
    // 锁升级
}

提供一个数据容器类内部分别使用读锁保护数据的read()方法，写锁保护数据的write()方法

JAVA
class DataContainerStamped {
    private int data;
    private final StampedLock lock = new StampedLock();
    public DataContainerStamped(int data) {
        this.data = data;
    }
    public int read(int readTime) {
        //获取戳
        long stamp = lock.tryOptimisticRead();
        log.debug("optimistic read locking...{}", stamp);
        //读取数据
        sleep(readTime);
        //读取数据之后再验戳
        if (lock.validate(stamp)) {
            log.debug("read finish...{}, data:{}", stamp, data);
            return data;
        }
        //如果验戳失败，说明已经数据已经被修改，需要升级锁重新读。
        // 锁升级 - 读锁
        log.debug("updating to read lock... {}", stamp);
        try {
            stamp = lock.readLock();
            log.debug("read lock {}", stamp);
            sleep(readTime);
            log.debug("read finish...{}, data:{}", stamp, data);
            return data;
        } finally {
            log.debug("read unlock {}", stamp);
            lock.unlockRead(stamp);
        }
    }
    public void write(int newData) {
        long stamp = lock.writeLock();
        log.debug("write lock {}", stamp);
        try {
            sleep(2);
            this.data = newData;
        } finally {
            log.debug("write unlock {}", stamp);
            lock.unlockWrite(stamp);
        }
    }
}

测试读-读可以优化

JAVA
public static void main(String[] args) {
    DataContainerStamped dataContainer = new DataContainerStamped(1);
    new Thread(() -> {
        dataContainer.read(1);
    }, "t1").start();
    sleep(0.5);
    new Thread(() -> {
        dataContainer.read(0);
    }, "t2").start();
}

输出结果，可以看到实际没有加读锁

SH
15:58:50.217 c.DataContainerStamped [t1] - optimistic read locking...256 
15:58:50.717 c.DataContainerStamped [t2] - optimistic read locking...256 
15:58:50.717 c.DataContainerStamped [t2] - read finish...256, data:1 
15:58:51.220 c.DataContainerStamped [t1] - read finish...256, data:1

测试读-写时优化读补加读锁

JAVA
public static void main(String[] args) {
    DataContainerStamped dataContainer = new DataContainerStamped(1);
    new Thread(() -> {
        dataContainer.read(1);
    }, "t1").start();
    sleep(0.5);
    new Thread(() -> {
        dataContainer.write(100);
    }, "t2").start();
}

输出结果

SH
15:57:00.219 c.DataContainerStamped [t1] - optimistic read locking...256 
15:57:00.717 c.DataContainerStamped [t2] - write lock 384 
15:57:01.225 c.DataContainerStamped [t1] - updating to read lock... 256 
15:57:02.719 c.DataContainerStamped [t2] - write unlock 384 
15:57:02.719 c.DataContainerStamped [t1] - read lock 513 
15:57:03.719 c.DataContainerStamped [t1] - read finish...513, data:1000 
15:57:03.719 c.DataContainerStamped [t1] - read unlock 513

注意

  • StampedLock 不支持条件变量
  • StampedLock 不支持可重入