Java集合源码学习(15)_Queue接口的实现PriorityQueue和PriorityBlockingQueue

一：PriorityQueue

继承自AbstractQueue类，队列里面的数据根据指定的Comparator或者自然排序(元素的compareTo())排序；

1：无界的队列(可以动态扩展)

2：内部实现基于堆

3：队列的头元素，是按照排序规则最小的元素；

一：类变量：

private static final int DEFAULT_INITIAL_CAPACITY = 11;//默认的初始化容量//实际的存放元素的数组，其实实现的是一个最小堆。private transient Object[] queue;//queue里面的元素的实际数量private int size = 0;//指定的比较器private final Comparator<? super E> comparator;

二：几个方法

1：容量扩展

private void grow(int minCapacity) {if (minCapacity < 0) // overflowthrow new OutOfMemoryError();int oldCapacity = queue.length;// Double size if small; else grow by 50%int newCapacity = ((oldCapacity < 64) ? ((oldCapacity + 1) * 2) : ((oldCapacity / 2) * 3));if (newCapacity < 0) // overflownewCapacity = Integer.MAX_VALUE;if (newCapacity < minCapacity)newCapacity = minCapacity;queue = Arrays.copyOf(queue, newCapacity);}

2:元素入队列

public boolean offer(E e) {if (e == null)throw new NullPointerException();modCount++;int i = size;if (i >= queue.length)grow(i + 1);//如果空间不足，扩容size = i + 1;if (i == 0)queue[0] = e;elsesiftUp(i, e);//将数据放置到堆的最后位置，自下而上的调整堆return true;}

自下而上调整的算法如下:

private void siftUp(int k, E x) {if (comparator != null)siftUpUsingComparator(k, x);elsesiftUpComparable(k, x);}private void siftUpComparable(int k, E x) {Comparable<? super E> key = (Comparable<? super E>) x;while (k > 0) {int parent = (k - 1) >>> 1;Object e = queue[parent];if (key.compareTo((E) e) >= 0)break;queue[k] = e;k = parent;}queue[k] = key;}private void siftUpUsingComparator(int k, E x) {while (k > 0) {int parent = (k - 1) >>> 1;Object e = queue[parent];if (comparator.compare(x, (E) e) >= 0)break;queue[k] = e;k = parent;}queue[k] = x;}

3:元素出队列

public E poll() {if (size == 0)return null;int s = --size;modCount++;E result = (E) queue[0];E x = (E) queue[s];queue[s] = null;if (s != 0)siftDown(0, x);//移除堆最上面的元素，然后自上而下调整堆return result;}

自上而下调整的算法如下：

private void siftDown(int k, E x) {if (comparator != null)siftDownUsingComparator(k, x);elsesiftDownComparable(k, x);}private void siftDownComparable(int k, E x) {Comparable<? super E> key = (Comparable<? super E>) x;int half = size >>> 1; // loop while a non-leafwhile (k < half) {int child = (k << 1) + 1; // assume left child is leastObject c = queue[child];int right = child + 1;if (right < size && ((Comparable<? super E>) c).compareTo((E) queue[right]) > 0)c = queue[child = right];if (key.compareTo((E) c) <= 0)break;queue[k] = c;k = child;}queue[k] = key;}private void siftDownUsingComparator(int k, E x) {int half = size >>> 1;while (k < half) {int child = (k << 1) + 1;Object c = queue[child];int right = child + 1;if (right < size && comparator.compare((E) c, (E) queue[right]) > 0)c = queue[child = right];if (comparator.compare(x, (E) c) <= 0)break;queue[k] = c;k = child;}queue[k] = x;}

学习过数据结构的话，如果对堆的算法有了解，理解上面这几个方法应该比较容易

二：PriorityBlockingQueue

继承自AbstractQueue，实现了BlockingQueue接口；

其实是，包装了PriorityQueue，对相应的方法进行了加锁的控制；

当然，也是一个无界队列；

一：类的变量

private final PriorityQueue<E> q;//实际存储数据的队列private final ReentrantLock lock = new ReentrantLock(true);//公平的锁private final Condition notEmpty = lock.newCondition();//因为是无解的队列，所以不需要notFull的条件变量

二：关键方法

1：offer方法（立即返回，成功true）

public boolean offer(E e) {final ReentrantLock lock = this.lock;lock.lock();try {boolean ok = q.offer(e);assert ok;notEmpty.signal();//唤醒一个等待线程return true;} finally {lock.unlock();}}

2:add()(抛异常)方法和put()方法(阻塞)和offer(time)(阻塞)

入队列都不会阻塞，直接调用offer方法的

public boolean add(E e) {return offer(e);}

public void put(E e) {offer(e); // never need to block}

public boolean offer(E e, long timeout, TimeUnit unit) {return offer(e); // never need to block}

3：poll()方法,不阻塞

public E poll() {final ReentrantLock lock = this.lock;lock.lock();try {return q.poll();//如果不存在返回null} finally {lock.unlock();}}

4:take()阻塞式获取

public E take() throws InterruptedException {final ReentrantLock lock = this.lock;lock.lockInterruptibly();try {try {while (q.size() == 0)notEmpty.await();} catch (InterruptedException ie) {//不太理解为何有signal了一次？notEmpty.signal(); // propagate to non-interrupted threadthrow ie;}E x = q.poll();assert x != null;return x;} finally {lock.unlock();}}

public E poll(long timeout, TimeUnit unit) throws InterruptedException {long nanos = unit.toNanos(timeout);final ReentrantLock lock = this.lock;lock.lockInterruptibly();try {for (;;) {E x = q.poll();if (x != null)return x;if (nanos <= 0)return null;try {nanos = notEmpty.awaitNanos(nanos);} catch (InterruptedException ie) {notEmpty.signal(); // propagate to non-interrupted threadthrow ie;}}} finally {lock.unlock();}}