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实现数据结构是堆,堆底层实现结构是数组,堆是完全二叉树。
主要的成员变量

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/**
* Priority queue represented as a balanced binary heap: the two
* children of queue[n] are queue[2*n+1] and queue[2*(n+1)]. The
* priority queue is ordered by comparator, or by the elements'
* natural ordering, if comparator is null: For each node n in the
* heap and each descendant d of n, n <= d. The element with the
* lowest value is in queue[0], assuming the queue is nonempty.
*/
transient Object[] queue; // non-private to simplify nested class access

/**
* The number of elements in the priority queue.
*/
private int size = 0;

/**
* The comparator, or null if priority queue uses elements'
* natural ordering.
*/
private final Comparator<? super E> comparator;

/**
* The number of times this priority queue has been
* <i>structurally modified</i>. See AbstractList for gory details.
*/
transient int modCount = 0; // non-private to simplify nested class access

queue是堆的底层实现,size是记录堆的大小的,comparator是自己实现比较方法的,可以实现大顶堆和小顶堆,mouCount用于控制并发

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/**
* Creates a {@code PriorityQueue} with the specified initial capacity
* that orders its elements according to the specified comparator.
*
* @param initialCapacity the initial capacity for this priority queue
* @param comparator the comparator that will be used to order this
* priority queue. If {@code null}, the {@linkplain Comparable
* natural ordering} of the elements will be used.
* @throws IllegalArgumentException if {@code initialCapacity} is
* less than 1
*/
public PriorityQueue(int initialCapacity,
Comparator<? super E> comparator) {
// Note: This restriction of at least one is not actually needed,
// but continues for 1.5 compatibility
if (initialCapacity < 1)
throw new IllegalArgumentException();
this.queue = new Object[initialCapacity];
this.comparator = comparator;
}

初始化的时候,可以自定义比较器和容器大小,默认是11
主要方法
添加数据

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/**
* Inserts the specified element into this priority queue.
*
* @return {@code true} (as specified by {@link Queue#offer})
* @throws ClassCastException if the specified element cannot be
* compared with elements currently in this priority queue
* according to the priority queue's ordering
* @throws NullPointerException if the specified element is null
*/
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;
}

如果队列大小与容量上限一直,就去扩容,从最后一位去向上堆化

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/**
* Increases the capacity of the array.
*
* @param minCapacity the desired minimum capacity
*/
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);
}

扩容方法,如果容量小于64 ,则一次扩容 2n+2,大于则 扩容1.5n,最后复制原来数组到新数组

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* 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
*/
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;
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;
}

向上堆化,如果自定义了比较器 就用siftUpUsingComparator,其他就用默认的比较器,按字母顺序排序,两个方法实现基本相同
K是新插入的节点的索引,它的父是( k-1)/2,这个地方跟一般的堆有些区别,是从0开始算的,父是n,左子树是2n+1,右子树是2(n+1)
优先级小的在上面,如果遇到子比父优先级大,结束,将x赋值给k位。如果父优先级更大,将父的值赋给子节点,继续比较父的父级,知道k=0.

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@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;
}

弹出堆顶值,queue[0]是优先级最小的,要弹出的值,sfitDown是从堆顶向堆底堆化,从最后一位取一个值,放到堆顶,然后从顶开始堆化。

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/**
* 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
*/
private void siftDown(int k, E x) {
if (comparator != null)
siftDownUsingComparator(k, x);
else
siftDownComparable(k, x);
}

@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
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];
if (key.compareTo((E) c) <= 0)
break;
queue[k] = c;
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;
}

跟从下到上结构相似,看是否有自实现的比较器。
size/2 是差不多最后一个非叶子节点,最后到这个节点去堆化,从k=0 开始,其次与左右子树比,谁优先级更小,不断循环,直到x的优先级,小于某个的节点,然后放置到k处

总结
优先级队列,底层数据结构是堆,堆的底层数据结构是数组,每次插入和删除,都要堆化,有2种堆化方式,一种是从上到下,一种是从下到上。从数组角度去理解还是有点难度的,需要想象成树的结构,然后根据序号存储在数组内。

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