PriorityQueue

PriorityQueue是一个基于小顶堆的无界队列，非线程安全，内部元素无序，只有顶部存储着最小的元素；入队是堆的插入元素实现，出队是堆的删除元素实现。

主要属性

public class PriorityQueue<E> extends AbstractQueue<E>
    implements java.io.Serializable {
    private static final long serialVersionUID = -7720805057305804111L;
    //默认容量
    private static final int DEFAULT_INITIAL_CAPACITY = 11;
    /**
     * 存放数据的地方
     * 优先队列由一个平衡二叉堆来实现：queue[n]的两个子节点分别为queue[2*n+1]和queue[2*n+2]
     * 其队列中元素的顺序根据构造器传入的comparator保证或者元素的自然顺序
     */
    transient Object[] queue; // non-private to simplify nested class access
    /**
     * 优先队列中元素个数
     */
    private int size = 0;
    /**
     * 比较器 如果为空 则使用元素的自然顺序
     */
    private final Comparator<? super E> comparator;
    /**
     * 修改次数
     */
    transient int modCount = 0; // non-private to simplify nested class access

入队

public boolean add(E e) {
    return offer(e);
}
public boolean offer(E e) {
    if (e == null)
        throw new NullPointerException();
    modCount++;
    int i = size;
    if (i >= queue.length)//当元素个数到达容量上限 则进行扩容操作
        grow(i + 1);
    size = i + 1;
    if (i == 0)//如果还没有元素
        queue[0] = e;
    else
        siftUp(i, e);
    return true;
}
/**
 * 扩容操作 
 * 如果旧容量<64 则扩容翻倍
 * 如果旧容量>=64 则扩容原来容量的一半
 */
private void grow(int minCapacity) {
    int oldCapacity = queue.length;
    // Double size if small; else grow by 50%
    int newCapacity = oldCapacity + ((oldCapacity < 64) ?
                                     (oldCapacity + 2) :
                                     (oldCapacity >> 1));
    // overflow-conscious code
    if (newCapacity - MAX_ARRAY_SIZE > 0)
        newCapacity = hugeCapacity(minCapacity);
    queue = Arrays.copyOf(queue, newCapacity);
}
 private void siftUp(int k, E x) {
    if (comparator != null)
        siftUpUsingComparator(k, x);
    else
        siftUpComparable(k, x);
}
private void siftUpUsingComparator(int k, E x) {
    while (k > 0) {
        //找到节点k的父节点
        int parent = (k - 1) >>> 1;
        Object e = queue[parent];
        //插入节点比父节点大则跳出循环
        if (comparator.compare(x, (E) e) >= 0)
            break;
        queue[k] = e;//与父节点交互
        k = parent;//继续与父节点比较
    }
    queue[k] = x;//找到最终的位置 放入数据
}

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;
}

出队

public E remove() {
    E x = poll();
    if (x != null)
        return x;
    else
        throw new NoSuchElementException();
}

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);
    return result;
}

private void siftDown(int k, E x) {
    if (comparator != null)
        siftDownUsingComparator(k, x);
    else
        siftDownComparable(k, x);
}
private void siftDownComparable(int k, E x) {
    Comparable<? super E> key = (Comparable<? super E>)x;
    //只需比较一半即可 因为叶子节点占了一半元素
    int half = size >>> 1;        // loop while a non-leaf
    while (k < half) {
        int child = (k << 1) + 1; // assume left child is least
        Object c = queue[child];
        int right = child + 1;
        if (right < size &&
            ((Comparable<? super E>) c).compareTo((E) queue[right]) > 0)
            c = queue[child = right];
            //如果当前元素比左右子节点还小 跳出循环
        if (key.compareTo((E) c) <= 0)
            break;
        queue[k] = c;
        k = child;
    }
    //找到正确的位置 放入元素
    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;
}