PriorityQueue 源码解析

PriorityQueue是Java util包里的具有“优先级”特征的队列，其接受类需要实现Compara接口。PriorityQueue可以当作小顶堆使用（不实现任何Comparable接口，将会按照自然排序（nature odering排序）。

public class PriorityQueue<E> extends AbstractQueue<E>
    implements java.io.Serializable {
    //序列化识别id
    private static final long serialVersionUID = -7720805057305804111L;
    //默认的容量是11
    private static final int DEFAULT_INITIAL_CAPACITY = 11;
    //数组实现
    transient Object[] queue;
    //大小
    private int size = 0;
    //比较器（默认为自然比较）
    private final Comparator<? super E> comparator;
    //
    transient int modCount = 0;
    //常用方法
    PriorityQueue();
    PriorityQueue(int initialCapacity);
    PriorityQueue(Comparator<? super E> comparator);
    PriorityQueue(int initialCapacity,Comparator<? super E> comparator);
    PriorityQueue(Collection<? extends E> c);
    grow(int minCapacity);
    //添加
    public boolean add(E e) {
        return offer(e);
    }
    //取堆顶
    public E peek() {
        return (size == 0) ? null : (E) queue[0];
    }
    //删除
    public boolean remove(Object o) {
        int i = indexOf(o);
        if (i == -1)
            return false;
        else {
            removeAt(i);
            return true;
        }
    }
    //contains,顺序查找
    public boolean contains(Object o) {
        return indexOf(o) != -1;
    }
    //poll
    poll()；
}
解析：
1. grow函数用于增加容量（如果容量小于64就双倍容量，大于64就增加50%）

1. add(E e)

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)
            grow(i + 1);
        size = i + 1;
        if (i == 0)
            queue[0] = e;
        else
            siftUp(i, e);
        return true;
    }

解析：
1. add函数调用了offer
2. offer函数首先检查了是否超过容量，如果超过容量就调用grow函数增加容量
3. 然后调用siftUp函数插入元素
4. 插入的主要逻辑就是 把整个Object数组当作是小顶堆（完全二叉树），具体逻辑看代码注释

2. remove(Object o)

删除元素同时为了保持整个小顶堆，需要做调整

public boolean remove(Object o) {
    int i = indexOf(o); //顺序查找o的位置
    if (i == -1)
        return false;
    else {
        removeAt(i);//调用具体函数
        return true;
    }
}

private E removeAt(int i) {
        // assert i >= 0 && i < size;
        modCount++;
        int s = --size;
        if (s == i) // removed last element
            queue[i] = null;
        else {
            E moved = (E) queue[s];//取出最后一个元素
            queue[s] = null;
            siftDown(i, moved);
            if (queue[i] == moved) {
                siftUp(i, moved);
                if (queue[i] != moved)
                    return moved;
            }
        }
        return null;
    }

1.删除元素时，首先查找元素的位置，调用removeAt删除元素
2.将最后一个元素取出，然后置空，调整小顶堆

    /**
     * Inserts item x at position k, maintaining heap invariant by
     * promoting x up the tree until it is greater than or equal to
     * its parent, or is the root.
     *
     * To simplify and speed up coercions and comparisons. the
     * Comparable and Comparator versions are separated into different
     * methods that are otherwise identical. (Similarly for siftDown.)
     *
     * @param k the position to fill
     * @param x the item to insert
    //在k处插入元素，并向上调整堆至小顶堆
    private void siftUp(int k, E x) {
            if (comparator != null)
                siftUpUsingComparator(k, x);
            else
                siftUpComparable(k, x);
        }

    @SuppressWarnings("unchecked")

    private void siftUpComparable(int k, E x) {
       Comparable<? super E> key = (Comparable<? super E>) x;
       while (k > 0) {
           int parent = (k - 1) >>> 1;//查看当前节点的父亲节点
           Object e = queue[parent];
           if (key.compareTo((E) e) >= 0) //如果大于等于当前节点，break
               break;
           queue[k] = e; //如果小于，将父亲节点移到当前位置
           k = parent;//继续查看父亲节点
       }
       queue[k] = key;
    }

    @SuppressWarnings("unchecked")
    //同上，区别是使用了用户自定义
    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;
    }


    /**
     * Inserts item x at position k, maintaining heap invariant by
     * demoting x down the tree repeatedly until it is less than or
     * equal to its children or is a leaf.
     *
     * @param k the position to fill
     * @param x the item to insert
     */
     //在k处插入x，向下调整小顶堆
    private void siftDown(int k, E x) {
        if (comparator != null)
            siftDownUsingComparator(k, x);  //使用用户定义比较器
        else
            siftDownComparable(k, x);  //使用默认比较器
    }

    @SuppressWarnings("unchecked")
    private void siftDownComparable(int k, E x) {
        Comparable<? super E> key = (Comparable<? super E>)x;
        int half = size >>> 1;        // loop while a non-leaf   从非叶子节点开始，叶子节点只用向上调整就行
        while (k < half) {
            int child = (k << 1) + 1; // assume left child is least 
            Object c = queue[child]; //位置k的左孩子
            int right = child + 1;   
            if (right < size && ((Comparable<? super E>) c).compareTo((E) queue[right]) > 0)   //左孩子比右孩子大
                c = queue[child = right];  //位置k的右孩子
            if (key.compareTo((E) c) <= 0)
                break;//如果key小于孩子中比较小的那个
            queue[k] = c;  //交换到k较小的孩子中继续比较，一直到叶子节点
            k = child; 
        }
        queue[k] = key;
    }

    @SuppressWarnings("unchecked")
    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;
    }

3. poll()

取出最小值，并向下调整小顶堆

 @SuppressWarnings("unchecked")
    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;
    }