Java高并发编程案例

文章目录

  • synchronized关键字
    • 对象加锁
    • 修饰方法
    • 锁定静态方法
    • 同步和非同步方法同时调用
    • 脏读
    • 可重入锁
    • 异常释放锁
    • 同步监视器变化
  • volatile
    • 线程之间的可见性
    • 对比synchronized
    • AtomXXX
    • 淘宝面试题
  • Reentrantlock
  • 生产者--消费者
    • 使用wait+notify
    • 使用Lock+Condition
  • ThreadLocal
  • 同步容器
    • ConcurrentMap
    • CopyOnWriteArrayList
    • ConcurrentLinkedQueue
    • BlockingQueue
      • LinkedBlockingQueue
      • ArrayBlockingQueue
    • DelayQueue
  • 线程池
    • Executor
    • Callable
    • Executors
    • ThreadPool
    • Future
    • 并行计算
    • CachedPool
    • SingleThreadPool
    • ScheduledPool
    • WorkStealingPool
    • ForkJoinPool
  • ParallelStream

synchronized关键字

对象加锁

对某个对象加锁,互斥锁(一个线程拿到其它就拿不到)

public class T {
    private int count = 10;
    private Object o = new Object();

    public void m() {
        synchronized(o) { //任何线程要执行下面的代码,必须先拿到o的锁
            count--;
            System.out.println(Thread.currentThread().getName() + " count = " + count);
        }
    }
}

若每次都要建一个Object来当锁太麻烦,直接拿自身对象当锁即可

public class T {

    private int count = 10;

    public void m() {
        synchronized(this) { //任何线程要执行下面的代码,必须先拿到this的锁
            count--;
            System.out.println(Thread.currentThread().getName() + " count = " + count);
        }
    }
}

修饰方法

直接用synchronized修饰方法等同于锁定自身对象

public class T {

    private int count = 10;

    public synchronized void m() { //等同于在方法的代码执行时要synchronized(this)
        count--;
        System.out.println(Thread.currentThread().getName() + " count = " + count);
    }
}

锁定静态方法

public class T {

    private static int count = 10;

    public synchronized static void m() { //这里等同于synchronized(top.tjtulong.T.class)
        count--;
        System.out.println(Thread.currentThread().getName() + " count = " + count);
    }

    public static void mm() {
        synchronized(T.class) { //考虑一下这里写synchronized(this)是否可以?
            count --;
        }
    }
}

一个synchronized代码块的代码是一个原子操作

同步和非同步方法同时调用

public class T {

    public synchronized void m1() {
        System.out.println(Thread.currentThread().getName() + " m1 start...");
        try {
            Thread.sleep(10000);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
        System.out.println(Thread.currentThread().getName() + " m1 end");
    }

    public void m2() {
        try {
            Thread.sleep(5000);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
        System.out.println(Thread.currentThread().getName() + " m2 ");
    }

    public static void main(String[] args) {
        T t = new T();

		/*new Thread(()->t.m1(), "t1").start();
		new Thread(()->t.m2(), "t2").start();*/

        new Thread(t::m1, "t1").start();
        new Thread(t::m2, "t2").start();

		/*
		new Thread(new Runnable() {

			@Override
			public void run() {
				t.m1();
			}

		});
		*/
    }
}

输出结果:

t1 m1 start...
t2 m2 
t1 m1 end

可见同步和非同步方法可以同时调用

脏读

只对写加锁而不对读加锁会造成脏读!

public class Account {
    String name;
    double balance;

    public synchronized void set(String name, double balance) {
        this.name = name;

        try {
            Thread.sleep(2000);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }


        this.balance = balance;
    }

    public /*synchronized*/ double getBalance(String name) {
        return this.balance;
    }

    public void setBalance(double balance) {
        this.balance = balance;
    }


    public static void main(String[] args) {
        Account a = new Account();
        new Thread(() -> a.set("zhangsan", 100.0)).start();

        try {
            TimeUnit.SECONDS.sleep(1);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        a.setBalance(50.0);
        System.out.println(a.getBalance("zhangsan"));

        try {
            TimeUnit.SECONDS.sleep(2);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        System.out.println(a.getBalance("zhangsan"));
    }
}

可重入锁

public class T {
    synchronized void m1() {
        System.out.println("m1 start");
        try {
            TimeUnit.SECONDS.sleep(1);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
        m2();
    }

    synchronized void m2() {
        try {
            TimeUnit.SECONDS.sleep(2);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
        System.out.println("m2");
    }
}

m2()方法可以执行

一个同步方法可以调用另外一个同步方法,一个线程已经拥有某个对象的锁,再次申请的时候仍然会得到该对象的锁,也就是说synchronized获得的锁是可重入的

异常释放锁

public class T {
    int count = 0;

    synchronized void m() {
        System.out.println(Thread.currentThread().getName() + " start");
        while (true) {
            count++;
            System.out.println(Thread.currentThread().getName() + " count = " + count);
            try {
                TimeUnit.SECONDS.sleep(1);

            } catch (InterruptedException e) {
                e.printStackTrace();
            }

            if (count == 5) {
                int i = 1 / 0; //此处抛出异常,锁将被释放,要想不被释放,可以在这里进行catch,然后让循环继续
                System.out.println(i);
            }
        }
    }

    public static void main(String[] args) {
        T t = new T();
        Runnable r = new Runnable() {

            @Override
            public void run() {
                t.m();
            }
        };
        new Thread(r, "t1").start();

        try {
            TimeUnit.SECONDS.sleep(3);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        new Thread(r, "t2").start();
    }
}

输出结果:

t1 start
t1 count = 1
t1 count = 2
t1 count = 3
t1 count = 4
t1 count = 5
t2 start
Exception in thread "t1" java.lang.ArithmeticException: / by zero
t2 count = 6
	at top.tjtulong.demo8.T.m(T.java:21)
	at top.tjtulong.demo8.T$1.run(T.java:33)
	at java.lang.Thread.run(Thread.java:748)
t2 count = 7
t2 count = 8
t2 count = 9
t2 count = 10
t2 count = 11

程序在执行过程中,如果出现异常,默认情况锁会被释放,所以在并发处理的过程中,有异常要多加小心,不然可能会发生不一致的情况。比如,在一个web app处理过程中,多个servlet线程共同访问同一个资源,这时如果异常处理不合适,在第一个线程中抛出异常,其他线程就会进入同步代码区,有可能会访问到异常产生时的数据,因此要非常小心的处理同步业务逻辑中的异常。

同步监视器变化

锁定某对象o,如果o的属性发生改变,不影响锁的使用;但是如果o变成另外一个对象,则锁定的对象发生改变,应该避免将锁定对象的引用变成另外的对象。

public class T {

    Object o = new Object();

    void m() {
        synchronized(o) {
            while(true) {
                try {
                    TimeUnit.SECONDS.sleep(1);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
                System.out.println(Thread.currentThread().getName());
            }
        }
    }

    public static void main(String[] args) {
        T t = new T();
        //启动第一个线程
        new Thread(t::m, "t1").start();

        try {
            TimeUnit.SECONDS.sleep(3);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
        //创建第二个线程
        Thread t2 = new Thread(t::m, "t2");

        t.o = new Object(); //锁对象发生改变,所以t2线程得以执行,如果注释掉这句话,线程2将永远得不到执行机会

        t2.start();
    }
}


注:不要用字符串常量作为锁定对象,因为这样其实锁定的是同一个对象。这种情况还会发生比较诡异的现象,比如你用到了一个类库,在该类库中代码锁定了字符串“Hello”,但是你读不到源码,所以你在自己的代码中也锁定了"Hello",这时候就有可能发生非常诡异的死锁阻塞,因为你的程序和你用到的类库不经意间使用了同一把锁。

volatile

线程之间的可见性

public class T {
    //对比一下有无volatile的情况下,整个程序运行结果的区别
    /*volatile*/ boolean running = true; 

    void m() {
        System.out.println("m start");
        while (running) {

        }
        System.out.println("m end!");
    }

    public static void main(String[] args) {
        T t = new T();

        new Thread(t::m, "t1").start();

        try {
            TimeUnit.SECONDS.sleep(1);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        t.running = false;
    }
}

如果running变量不用volatile修饰的话,程序将不会停止。

volatile 关键字,使一个变量在多个线程间可见。A、B线程都用到一个变量,java默认是A线程中保留一份copy,这样如果B线程修改了该变量,则A线程未必知道。但使用volatile关键字,会让所有线程都会读到变量的修改值。

在上面的代码中,running是存在于堆内存的t对象中,当线程t1开始运行的时候,会把running值从内存中读到t1线程的工作区,在运行过程中直接使用这个copy,并不会每次都去读取堆内存,这样当主线程修改running的值之后,t1线程感知不到,所以不会停止运行;而使用volatile,将会强制所有线程都去堆内存中读取running的值。

volatile并不能保证多个线程共同修改running变量时所带来的不一致问题,也就是说volatile不能替代synchronized

对比synchronized

public class T {
    volatile int count = 0;
    void m() {
        for(int i=0; i<10000; i++) count++;
    }

    public static void main(String[] args) {
        T t = new T();

        List<Thread> threads = new ArrayList<Thread>();

        for(int i=0; i<10; i++) {
            threads.add(new Thread(t::m, "thread-"+i));
        }

        threads.forEach((o)->o.start());

        threads.forEach((o)->{
            try {
                o.join();
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
        });

        System.out.println(t.count);
    }
}

输出结果必定小于100000.

这是由于volatile并不能保证多个线程共同修改running变量时所带来的不一致问题(++不是原子性操作),也就是说volatile不能替代synchronized。

Java高并发编程案例_第1张图片

synchronized void m() { 
    for (int i = 0; i < 10000; i++)
        count++;
}

对比上一个程序,可以用synchronized解决,synchronized可以保证可见性和原子性,volatile只能保证可见性。

AtomXXX

解决同样的问题的更高效的方法,使用AtomXXX类:

AtomicInteger count = new AtomicInteger(0); 

void m() { 
    for (int i = 0; i < 10000; i++)
        //if count.get() < 1000
        count.incrementAndGet(); //等同于count++,但是是原子的
}

AtomXXX类本身方法都是原子性的,但不能保证多个方法连续调用是原子性的。

淘宝面试题

实现一个容器,提供两个方法,add,size,写两个线程,线程1添加10个元素到容器中,线程2实现监控元素的个数,当个数到5个时,线程2给出提示并结束。

方法一:使用wait和notify

public class MyContainer4 {

    //添加volatile,使t2能够得到通知
    volatile List lists = new ArrayList();

    public void add(Object o) {
        lists.add(o);
    }

    public int size() {
        return lists.size();
    }

    public static void main(String[] args) {
        MyContainer4 c = new MyContainer4();

        final Object lock = new Object();

        new Thread(() -> {
            synchronized(lock) {
                System.out.println("t2启动");
                if(c.size() != 5) {
                    try {
                        lock.wait();
                    } catch (InterruptedException e) {
                        e.printStackTrace();
                    }
                }
                System.out.println("t2 结束");
                //通知t1继续执行
                lock.notify();
            }

        }, "t2").start();

        try {
            TimeUnit.SECONDS.sleep(1);
        } catch (InterruptedException e1) {
            e1.printStackTrace();
        }

        new Thread(() -> {
            System.out.println("t1启动");
            synchronized(lock) {
                for(int i=0; i<10; i++) {
                    c.add(new Object());
                    System.out.println("add " + i);

                    if(c.size() == 5) {
                        lock.notify();
                        //释放锁,让t2得以执行
                        try {
                            lock.wait();
                        } catch (InterruptedException e) {
                            e.printStackTrace();
                        }
                    }

                    try {
                        TimeUnit.SECONDS.sleep(1);
                    } catch (InterruptedException e) {
                        e.printStackTrace();
                    }
                }
            }
        }, "t1").start();
    }
}

sleep() 不释放锁
wait() 释放锁
notify() 不释放锁

方法二:使用Latch(门闩) 替代wait和notify来进行通知。好处是通信方式简单,同时也可以指定等待时间。使用await和countdown方法替代wait和notify,CountDownLatch不涉及锁定,当count的值为零时当前线程继续运行。

当不涉及同步,只是涉及线程通信的时候,用synchronized + wait/notify就显得太重了,这时应该考虑countdownlatch/cyclicbarrier/semaphore。

public class MyContainer5 {

    // 添加volatile,使t2能够得到通知
    volatile List lists = new ArrayList();

    public void add(Object o) {
        lists.add(o);
    }

    public int size() {
        return lists.size();
    }

    public static void main(String[] args) {
        MyContainer5 c = new MyContainer5();

        CountDownLatch latch = new CountDownLatch(1);

        new Thread(() -> {
            System.out.println("t2启动");
            if (c.size() != 5) {
                try {
                    latch.await();

                    TimeUnit.SECONDS.sleep(5);
                    //也可以指定等待时间
                    //latch.await(5000, TimeUnit.MILLISECONDS);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            }
            System.out.println("t2 结束");

        }, "t2").start();

        try {
            TimeUnit.SECONDS.sleep(1);
        } catch (InterruptedException e1) {
            e1.printStackTrace();
        }

        new Thread(() -> {
            System.out.println("t1启动");
            for (int i = 0; i < 10; i++) {
                c.add(new Object());
                System.out.println("add " + i);

                if (c.size() == 5) {
                    // 打开门闩,让t2得以执行
                    latch.countDown();
                }

                try {
                    TimeUnit.SECONDS.sleep(1);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            }

        }, "t1").start();
    }
}

Reentrantlock

使用Reentrantlock可以替代synchronize完成同样的功能。需要注意的是,必须要必须要必须要手动释放锁。使用syn锁定的话如果遇到异常,jvm会自动释放锁,但是lock必须手动释放锁,因此经常在finally中进行锁的释放。

class X{
    //定义锁对象
    private final ReentrantLock lock=new ReentrantLock();
    //定义需要保证线程安全的方法
    public void m(){
        //加锁
        lock.lock();
        try{
            //...method body
        }
        //使用finally块来保证释放锁
        finally{
            lock.unlock();
        }
    }
}

使用Reentrantlock可以进行尝试锁定tryLock,这样无法锁定,或者在指定时间内无法锁定,线程可以决定是否继续等待。

public class ReentrantLock3 {
    Lock lock = new ReentrantLock();

    void m1() {
        try {
            lock.lock();
            for (int i = 0; i < 10; i++) {
                TimeUnit.SECONDS.sleep(1);

                System.out.println(i);
            }
        } catch (InterruptedException e) {
            e.printStackTrace();
        } finally {
            lock.unlock();
        }
    }

    /**
     * 使用tryLock进行尝试锁定,不管锁定与否,方法都将继续执行
     * 可以根据tryLock的返回值来判定是否锁定
     * 也可以指定tryLock的时间,由于tryLock(time)抛出异常,所以要注意unclock的处理,必须放到finally中
     */
    void m2() {
		/*
		boolean locked = lock.tryLock();
		System.out.println("m2 ..." + locked);
		if(locked) lock.unlock();
		*/

        boolean locked = false;

        try {
            locked = lock.tryLock(5, TimeUnit.SECONDS);
            System.out.println("m2 ..." + locked);
        } catch (InterruptedException e) {
            e.printStackTrace();
        } finally {
            if(locked) lock.unlock();
        }
    }

    public static void main(String[] args) {
        ReentrantLock3 rl = new ReentrantLock3();
        new Thread(rl::m1).start();
        try {
            TimeUnit.SECONDS.sleep(1);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
        new Thread(rl::m2).start();
    }
}

使用ReentrantLock还可以调用lockInterruptibly方法,可以对线程interrupt方法做出响应,在一个线程等待锁的过程中,可以被打断。

ReentrantLock还可以指定为公平锁,即谁等的时间长,谁得到锁,synchronized为非公平锁,不在乎一个线程已经等待多长时间。

public class ReentrantLock5 extends Thread {

    private static ReentrantLock lock=new ReentrantLock(true); //参数为true表示为公平锁,请对比输出结果
    public void run() {
        for(int i=0; i<100; i++) {
            lock.lock();
            try{
                System.out.println(Thread.currentThread().getName()+"获得锁");
            }finally{
                lock.unlock();
            }
        }
    }
    public static void main(String[] args) {
        ReentrantLock5 rl=new ReentrantLock5();
        Thread th1=new Thread(rl);
        Thread th2=new Thread(rl);
        th1.start();
        th2.start();
    }
}

输出结果为:

Thread-1获得锁
Thread-2获得锁
Thread-1获得锁
Thread-2获得锁
Thread-1获得锁
Thread-2获得锁
Thread-1获得锁
Thread-2获得锁

生产者–消费者

写一个固定容量同步容器,拥有put和get方法,以及getCount方法,能够支持2个生产者线程以及10个消费者线程的阻塞调用。

使用wait+notify

public class MyContainer1<T> {
    final private LinkedList<T> lists = new LinkedList<>();
    final private int MAX = 10; //最多10个元素
    private int count = 0;


    public synchronized void put(T t) {
        while (lists.size() == MAX) { //想想为什么用while而不是用if?
            try {
                this.wait(); //effective java
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
        }

        lists.add(t);
        ++count;
        this.notifyAll(); //通知消费者线程进行消费
    }

    public synchronized T get() {
        T t = null;
        while (lists.size() == 0) {
            try {
                this.wait();
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
        }
        t = lists.removeFirst();
        count--;
        this.notifyAll(); //通知生产者进行生产
        return t;
    }

    public static void main(String[] args) {
        MyContainer1<String> c = new MyContainer1<>();
        //启动消费者线程
        for (int i = 0; i < 10; i++) {
            new Thread(() -> {
                for (int j = 0; j < 5; j++) System.out.println(c.get());
            }, "c" + i).start();
        }

        try {
            TimeUnit.SECONDS.sleep(2);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        //启动生产者线程
        for (int i = 0; i < 2; i++) {
            new Thread(() -> {
                for (int j = 0; j < 25; j++) c.put(Thread.currentThread().getName() + " " + j);
            }, "p" + i).start();
        }
    }
}

关键点:

  1. 用while而不是用if;
  2. notifyAll而不是notify。

使用Lock+Condition

Condition的方式可以更加精确的指定哪些线程被唤醒

public class MyContainer2<T> {
    final private LinkedList<T> lists = new LinkedList<>();
    final private int MAX = 10; //最多10个元素
    private int count = 0;

    private Lock lock = new ReentrantLock();
    private Condition producer = lock.newCondition();
    private Condition consumer = lock.newCondition();

    public void put(T t) {
        try {
            lock.lock();
            while(lists.size() == MAX) { //想想为什么用while而不是用if?
                producer.await();
            }

            lists.add(t);
            ++count;
            consumer.signalAll(); //通知消费者线程进行消费
        } catch (InterruptedException e) {
            e.printStackTrace();
        } finally {
            lock.unlock();
        }
    }

    public T get() {
        T t = null;
        try {
            lock.lock();
            while(lists.size() == 0) {
                consumer.await();
            }
            t = lists.removeFirst();
            count --;
            producer.signalAll(); //通知生产者进行生产
        } catch (InterruptedException e) {
            e.printStackTrace();
        } finally {
            lock.unlock();
        }
        return t;
    }

    public static void main(String[] args) {
        MyContainer2<String> c = new MyContainer2<>();
        //启动消费者线程
        for(int i=0; i<10; i++) {
            new Thread(()->{
                for(int j=0; j<5; j++) System.out.println(c.get());
            }, "c" + i).start();
        }

        try {
            TimeUnit.SECONDS.sleep(2);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        //启动生产者线程
        for(int i=0; i<2; i++) {
            new Thread(()->{
                for(int j=0; j<25; j++) c.put(Thread.currentThread().getName() + " " + j);
            }, "p" + i).start();
        }
    }
}

ThreadLocal

ThreadLocal是线程局部变量

ThreadLocal是使用空间换时间,synchronized是使用时间换空间

public class ThreadLocal2 {
    //volatile static Person p = new Person();
    static ThreadLocal<Person> tl = new ThreadLocal<>();

    public static void main(String[] args) {

        new Thread(()->{
            try {
                TimeUnit.SECONDS.sleep(2);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }

            System.out.println(tl.get());
        }).start();

        new Thread(()->{
            try {
                TimeUnit.SECONDS.sleep(1);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            tl.set(new Person());
        }).start();
    }

    static class Person {
        String name = "zhangsan";
    }
}

同步容器

ConcurrentMap

多线程情况下用ConcurrentHashMap代替HashMap;
ConcurrentHashMap效率要比Hashtable高;
ConcurrentSkipListMap支持高并发且排序;
Collections.sychronizedXXX可以将非线程安全的容器变为线程安全的容器。

public class T01_ConcurrentMap {
    public static void main(String[] args) {
        //Map map = new ConcurrentHashMap<>();
        //Map map = new ConcurrentSkipListMap<>(); //高并发并且排序

        //Map map = new Hashtable<>();
        Map<String, String> map = new HashMap<>(); //Collections.synchronizedXXX
        //TreeMap
        Random r = new Random();
        Thread[] ths = new Thread[100];
        CountDownLatch latch = new CountDownLatch(ths.length);
        long start = System.currentTimeMillis();
        for(int i=0; i<ths.length; i++) {
            ths[i] = new Thread(()->{
                for(int j=0; j<10000; j++) map.put("a" + r.nextInt(100000), "a" + r.nextInt(100000));
                latch.countDown();
            });
        }

        Arrays.asList(ths).forEach(t->t.start());
        try {
            latch.await();
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        long end = System.currentTimeMillis();
        System.out.println(end - start);
    }
}

CopyOnWriteArrayList

写的速度很慢但读的速度很快。

ConcurrentLinkedQueue

内部加锁的队列

public class T04_ConcurrentQueue {
    public static void main(String[] args) {
        Queue<String> strs = new ConcurrentLinkedQueue<>();

        for (int i = 0; i < 10; i++) {
            strs.offer("a" + i);  //add
        }

        System.out.println(strs);

        System.out.println(strs.size());

        System.out.println(strs.poll());//取出并删除
        System.out.println(strs.size());

        System.out.println(strs.peek());//仅取出不删除
        System.out.println(strs.size());

        //双端队列Deque
    }
}

BlockingQueue

阻塞式队列:LinkedBlockingQueue(无界)和ArrayBlockingQueue(有界)

LinkedBlockingQueue

LinkedBlockingQueue自动实现了阻塞式队列

public class T05_LinkedBlockingQueue {

    static BlockingQueue<String> strs = new LinkedBlockingQueue<>();

    static Random r = new Random();

    public static void main(String[] args) {
        new Thread(() -> {
            for (int i = 0; i < 100; i++) {
                try {
                    strs.put("a" + i); //如果满了,就会等待
                    TimeUnit.MILLISECONDS.sleep(r.nextInt(1000));
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            }
        }, "p1").start();

        for (int i = 0; i < 5; i++) {
            new Thread(() -> {
                for (;;) {
                    try {
                        System.out.println(Thread.currentThread().getName() + " take -" + strs.take()); //如果空了,就会等待
                    } catch (InterruptedException e) {
                        e.printStackTrace();
                    }
                }
            }, "c" + i).start();

        }
    }
}

ArrayBlockingQueue

public class T06_ArrayBlockingQueue {

    static BlockingQueue<String> strs = new ArrayBlockingQueue<>(10);

    static Random r = new Random();

    public static void main(String[] args) throws InterruptedException {
        for (int i = 0; i < 10; i++) {
            strs.put("a" + i);
        }

        strs.put("aaa"); //满了就会等待,程序阻塞
        strs.add("aaa");//添加不进去报错
        strs.offer("aaa");//添加不进去返回false
        strs.offer("aaa", 1, TimeUnit.SECONDS);//1s添加不进去返回false

        System.out.println(strs);
    }
}

DelayQueue

数组中每个元素记录着自己还有多长时间可以被消费者拿走,可用作定时执行任务,放入DelayQueue中的元素必须实现Delayed接口。

public class T07_DelayQueue {

    static BlockingQueue<MyTask> tasks = new DelayQueue<>();

    static Random r = new Random();

    static class MyTask implements Delayed {
        long runningTime;

        MyTask(long rt) {
            this.runningTime = rt;
        }

        @Override
        public int compareTo(Delayed o) {
            if(this.getDelay(TimeUnit.MILLISECONDS) < o.getDelay(TimeUnit.MILLISECONDS))
                return -1;
            else if(this.getDelay(TimeUnit.MILLISECONDS) > o.getDelay(TimeUnit.MILLISECONDS))
                return 1;
            else
                return 0;
        }

        @Override
        public long getDelay(TimeUnit unit) {

            return unit.convert(runningTime - System.currentTimeMillis(), TimeUnit.MILLISECONDS);
        }


        @Override
        public String toString() {
            return "" + runningTime;
        }
    }

    public static void main(String[] args) throws InterruptedException {
        long now = System.currentTimeMillis();
        MyTask t1 = new MyTask(now + 1000);
        MyTask t2 = new MyTask(now + 2000);
        MyTask t3 = new MyTask(now + 1500);
        MyTask t4 = new MyTask(now + 2500);
        MyTask t5 = new MyTask(now + 500);

        tasks.put(t1);
        tasks.put(t2);
        tasks.put(t3);
        tasks.put(t4);
        tasks.put(t5);

        System.out.println(tasks);

        for(int i=0; i<5; i++) {
            System.out.println(tasks.take());
        }
    }
}

线程池

Executor

最顶层接口

public class T01_MyExecutor implements Executor{

    public static void main(String[] args) {
        new T01_MyExecutor().execute(()->System.out.println("hello executor"));
    }

    @Override
    public void execute(Runnable command) {
        //new Thread(command).run();
        command.run();
    }
}

Callable

Callable接口提供了一个call()方法可以作为线程执行体,但call()方法比run()方法功能更强大:call()方法可以有返回值且call()方法可以声明抛出异常。

Executors

操作Exector的工具类。

ThreadPool

线程池,维护着一个任务队列和一个完成队列。

public class T05_ThreadPool {
    public static void main(String[] args) throws InterruptedException {
        ExecutorService service = Executors.newFixedThreadPool(5); //execute submit
        for (int i = 0; i < 6; i++) {
            service.execute(() -> {
                try {
                    TimeUnit.MILLISECONDS.sleep(500);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
                System.out.println(Thread.currentThread().getName());
                //java.util.concurrent.ThreadPoolExecutor@3b9a45b3[Running, pool size = 5, active threads = 5, queued tasks = 1, completed tasks = 0]
            });
        }
        System.out.println(service);

        service.shutdown();
        System.out.println(service.isTerminated());//是否执行完false
        System.out.println(service.isShutdown());//是否关闭true
        System.out.println(service);
        //java.util.concurrent.ThreadPoolExecutor@3b9a45b3[Shutting down, pool size = 5, active threads = 5, queued tasks = 1, completed tasks = 0]

        TimeUnit.SECONDS.sleep(5);
        System.out.println(service.isTerminated());//true
        System.out.println(service.isShutdown());//true
        System.out.println(service);
        //java.util.concurrent.ThreadPoolExecutor@3b9a45b3[Terminated, pool size = 0, active threads = 0, queued tasks = 0, completed tasks = 6]
    }
}

Future

相当于Callable方法未来要返回的值

public class T06_Future {
    public static void main(String[] args) throws InterruptedException, ExecutionException {

        FutureTask<Integer> task = new FutureTask<>(()->{
            TimeUnit.MILLISECONDS.sleep(500);
            return 1000;
        }); //new Callable () { Integer call();}

        new Thread(task).start();

        System.out.println(task.get()); //阻塞返回1000

        //*******************************
        ExecutorService service = Executors.newFixedThreadPool(5);
        Future<Integer> f = service.submit(()->{
            TimeUnit.MILLISECONDS.sleep(500);
            return 1;
        });
        System.out.println(f.get());//1
        System.out.println(f.isDone());//true
    }
}

并行计算

计算1-200000之间有多少个质数。

一般起线程数 > CPU核数

public class T07_ParallelComputing {
    public static void main(String[] args) throws InterruptedException, ExecutionException {
        long start = System.currentTimeMillis();
        getPrime(1, 200000);
        long end = System.currentTimeMillis();
        System.out.println(end - start);

        final int cpuCoreNum = 4;

        ExecutorService service = Executors.newFixedThreadPool(cpuCoreNum);

        MyTask t1 = new MyTask(1, 80000); //1-5 5-10 10-15 15-20
        MyTask t2 = new MyTask(80001, 130000);
        MyTask t3 = new MyTask(130001, 170000);
        MyTask t4 = new MyTask(170001, 200000);

        Future<List<Integer>> f1 = service.submit(t1);
        Future<List<Integer>> f2 = service.submit(t2);
        Future<List<Integer>> f3 = service.submit(t3);
        Future<List<Integer>> f4 = service.submit(t4);

        start = System.currentTimeMillis();
        f1.get();
        f2.get();
        f3.get();
        f4.get();
        end = System.currentTimeMillis();
        System.out.println(end - start);
    }

    static class MyTask implements Callable<List<Integer>> {
        int startPos, endPos;

        MyTask(int s, int e) {
            this.startPos = s;
            this.endPos = e;
        }

        @Override
        public List<Integer> call() throws Exception {
            List<Integer> r = getPrime(startPos, endPos);
            return r;
        }

    }

    static boolean isPrime(int num) {
        for(int i=2; i<=num/2; i++) {
            if(num % i == 0) return false;
        }
        return true;
    }

    static List<Integer> getPrime(int start, int end) {
        List<Integer> results = new ArrayList<>();
        for(int i=start; i<=end; i++) {
            if(isPrime(i)) results.add(i);
        }

        return results;
    }
}

从计算结果可以看出,利用线程池并行计算明显比单线程计算快。

CachedPool

开始没有线程,需要起线程时便启动线程,当线程空闲60s(可以自己设置)时自动关闭。

public class T08_CachedPool {
    public static void main(String[] args) throws InterruptedException {
        ExecutorService service = Executors.newCachedThreadPool();
        System.out.println(service);
        //java.util.concurrent.ThreadPoolExecutor@677327b6[Running, pool size = 0, active threads = 0, queued tasks = 0, completed tasks = 0]
        for (int i = 0; i < 2; i++) {
            service.execute(() -> {
                try {
                    TimeUnit.MILLISECONDS.sleep(500);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
                System.out.println(Thread.currentThread().getName());
            });
        }
        System.out.println(service);
        //java.util.concurrent.ThreadPoolExecutor@677327b6[Running, pool size = 2, active threads = 2, queued tasks = 0, completed tasks = 0]

        TimeUnit.SECONDS.sleep(80);

        System.out.println(service);
        //java.util.concurrent.ThreadPoolExecutor@677327b6[Running, pool size = 0, active threads = 0, queued tasks = 0, completed tasks = 2]
    }
}

SingleThreadPool

线程池中只有一个线程,保证任务顺序执行。

public class T09_SingleThreadPool {
    public static void main(String[] args) {
        ExecutorService service = Executors.newSingleThreadExecutor();
        for(int i=0; i<5; i++) {
            final int j = i;
            service.execute(()->{

                System.out.println(j + " " + Thread.currentThread().getName());
            });
        }
    }
}

ScheduledPool

以固定的频率执行任务

public class T10_ScheduledPool {
    public static void main(String[] args) {
        ScheduledExecutorService service = Executors.newScheduledThreadPool(4);
        service.scheduleAtFixedRate(()->{
            try {
                TimeUnit.MILLISECONDS.sleep(new Random().nextInt(1000));
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            System.out.println(Thread.currentThread().getName());
        }, 0, 500, TimeUnit.MILLISECONDS);
        // 500 表示每隔0.5秒执行一次
    }
}

WorkStealingPool

线程池中每隔线程都维护一个任务列表,当自身的任务列表执行完成后,会执行别的线程的任务列表。本质是ForkJoinPool线程池,所有的线程都是精灵线程。

public class T11_WorkStealingPool {
    public static void main(String[] args) throws IOException {
        ExecutorService service = Executors.newWorkStealingPool();
        System.out.println(Runtime.getRuntime().availableProcessors());

        service.execute(new R(1000));
        service.execute(new R(2000));
        service.execute(new R(2000));
        service.execute(new R(2000)); //daemon
        service.execute(new R(2000));

        //由于产生的是精灵线程(守护线程、后台线程),主线程不阻塞的话,看不到输出
        System.in.read();
    }

    static class R implements Runnable {
        int time;

        R(int t) {
            this.time = t;
        }

        @Override
        public void run() {
            try {
                TimeUnit.MILLISECONDS.sleep(time);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            System.out.println(time  + " " + Thread.currentThread().getName());
        }
    }
}

ForkJoinPool

Fork/Join框架就是在必要的情况下,将一个大任务进行拆分(fork)成若干个小任务(拆到不可再拆时),再将一个个的小任务运算的结果进行join汇总
Java高并发编程案例_第2张图片

import java.io.IOException;
import java.util.Arrays;
import java.util.Random;
import java.util.concurrent.ForkJoinPool;
import java.util.concurrent.RecursiveTask;

public class T12_ForkJoinPool {
    static int[] nums = new int[1000000];
    static final int MAX_NUM = 50000;
    static Random r = new Random();

    static {
        for(int i=0; i<nums.length; i++) {
            nums[i] = r.nextInt(100);
        }

        System.out.println(Arrays.stream(nums).sum()); //stream api
    }

	/*
	static class AddTask extends RecursiveAction {

		int start, end;

		AddTask(int s, int e) {
			start = s;
			end = e;
		}

		@Override
		protected void compute() {

			if(end-start <= MAX_NUM) {
				long sum = 0L;
				for(int i=start; istatic class AddTask extends RecursiveTask<Long> {

        private static final long serialVersionUID = 1L;
        int start, end;

        AddTask(int s, int e) {
            start = s;
            end = e;
        }

        @Override
        protected Long compute() {

            if(end-start <= MAX_NUM) {
                long sum = 0L;
                for(int i=start; i<end; i++) sum += nums[i];
                return sum;
            }

            int middle = start + (end-start)/2;

            AddTask subTask1 = new AddTask(start, middle);
            AddTask subTask2 = new AddTask(middle, end);
            subTask1.fork();
            subTask2.fork();

            return subTask1.join() + subTask2.join();
        }

    }

    public static void main(String[] args) throws IOException {
        ForkJoinPool fjp = new ForkJoinPool();
        AddTask task = new AddTask(0, nums.length);
        fjp.execute(task);
        long result = task.join();
        System.out.println(result);

        //System.in.read();
    }
}

ps:多线程归并排序

各种线程池归根到底都是ThreadPoolExecutor类,指定起始线程、最大线程、存活时间及使用的队列。

ParallelStream

利用多线程访问数据流

public class T14_ParallelStreamAPI {
    public static void main(String[] args) {
        List<Integer> nums = new ArrayList<>();
        Random r = new Random();
        for(int i=0; i<10000; i++) nums.add(1000000 + r.nextInt(1000000));

        //System.out.println(nums);

        long start = System.currentTimeMillis();
        nums.forEach(v->isPrime(v));
        long end = System.currentTimeMillis();
        System.out.println(end - start);

        //使用parallel stream api

        start = System.currentTimeMillis();
        nums.parallelStream().forEach(T14_ParallelStreamAPI::isPrime);
        end = System.currentTimeMillis();

        System.out.println(end - start);
    }

    static boolean isPrime(int num) {
        for(int i=2; i<=num/2; i++) {
            if(num % i == 0) return false;
        }
        return true;
    }
}

你可能感兴趣的:(高并发)