java.util.concurrent.BlockingQueue
在Queue的基础增加额外的功能：遍历队列时，若无元素则阻塞等待；插入元素时，无额外的空间则等待空间释放。
其方法可分为四种形式：根据对相同操作(对操作不能立即满足)的不同处理结果来分为以下四种
- 抛出异常
- 返回特定值，不同的方法返回的值不同
- 阻塞，直到条件满足
- 阻塞一段时间，而后再放弃
| Throws exception | Special value | Blocks | Times out | |
| Insert | {@link #add add(e)} | {@link #offer offer(e)} | {@link #put put(e)} | {@link #offer(Object, long, TimeUnit) offer(e, time, unit)} |
| Remove | {@link #remove remove()} | {@link #poll poll()} | {@link #take take()} | {@link #poll(long, TimeUnit) poll(time, unit)} |
| Examine | {@link #element element()} | {@link #peek peek()} | not applicable | not applicable |
- 不允许插入Null， add \offer \ put 均应抛出异常
- 设计之初是为了方便：生产者-消费者队列
- 线程安全；但对于批量操作，比如addAll containsAll retainAll removeAll等，是未做要求的，除非实现类做了特殊说明。
- 内存可见性：Happen-before原则，
Memory consistency effects: As with other concurrent
collections, actions in a thread prior to placing an object into a
{@code BlockingQueue}
happen-before
actions subsequent to the access or removal of that element from
the {@code BlockingQueue} in another thread.
java.util.concurrent.PriorityBlockingQueue
阻塞优先级队列
- 功能同java.util.PriorityQueue
- 无容量限制，除非是资源耗尽，抛出OutOfMemory
- 不允许插入Null
- 若队列依赖元素自身的排序规则，则不允许插入非Comparable的元素
- iterator遍历时，不保证顺序。若要一致的顺序，需自行toArray后排序，再进行遍历
- priority相同的元素，顺序不固定。
- 每个public的方法均使用内部的lock来实现并发控制
- 所有的公共方法均是使用lock锁实现并发控制
- take和带有超时时间的poll，均使用了lock和notEmpty(condition)实现。
- 在构造器中，会对lock和notEmpty初始化，condition在等待时会释放锁，被唤醒时会重新获取锁！
this.lock = new ReentrantLock();
this.notEmpty = lock.newCondition();
- 在获取lock后，若支持阻塞，则应使用lockInterruptibly来获取锁！
- 四个疑问
- 使用SortedSet初始化时，为何不需要重新堆化呢？
- 初始的堆化时，为何指定了从half = (n >>> 1) - 1;开始呢？
- siftDown时，while的停止条件是 k < (n >>> 1)
- removeAt方法中，最后为何要判断array[i] == moved???
从Collection初始化一个PriorityBlockingQueue
public PriorityBlockingQueue(Collection<? extends E> c) {
this.lock = new ReentrantLock();
this.notEmpty = lock.newCondition();
boolean heapify = true; // true if not known to be in heap order
boolean screen = true; // true if must screen for nulls
if (c instanceof SortedSet<?>) {
SortedSet<? extends E> ss = (SortedSet<? extends E>) c;
this.comparator = (Comparator<? super E>) ss.comparator();
// sorted set 已经是堆化的？？？？ 尤其是toArray()方法返回的数组
heapify = false;
}
else if (c instanceof PriorityBlockingQueue<?>) {
PriorityBlockingQueue<? extends E> pq =
(PriorityBlockingQueue<? extends E>) c;
this.comparator = (Comparator<? super E>) pq.comparator();
screen = false;
if (pq.getClass() == PriorityBlockingQueue.class) // exact match
// 只相信 PriorityBlockingQueue 返回的数组是 堆化的。
heapify = false;
}
Object[] a = c.toArray();
int n = a.length;
// If c.toArray incorrectly doesn't return Object[], copy it.
if (a.getClass() != Object[].class)
a = Arrays.copyOf(a, n, Object[].class);
// this.comparator != null： comparator不允许null
// n == 1 ？？？？ 兼容历史？
// PriorityQueue也是如此的判断条件
if (screen && (n == 1 || this.comparator != null)) {
for (int i = 0; i < n; ++i)
if (a[i] == null)
//不允许存储Null
throw new NullPointerException();
}
this.queue = a;
this.size = n;
if (heapify)
heapify();
}
从Collection初始化一个PriorityQueue
public PriorityQueue(Collection<? extends E> c) {
if (c instanceof SortedSet<?>) {
SortedSet<? extends E> ss = (SortedSet<? extends E>) c;
this.comparator = (Comparator<? super E>) ss.comparator();
initElementsFromCollection(ss);
}
else if (c instanceof PriorityQueue<?>) {
PriorityQueue<? extends E> pq = (PriorityQueue<? extends E>) c;
this.comparator = (Comparator<? super E>) pq.comparator();
initFromPriorityQueue(pq);
}
else {
this.comparator = null;
initFromCollection(c);
}
}
//复制底层数组和size，并重新进行堆化
private void initFromCollection(Collection<? extends E> c) {
initElementsFromCollection(c);
heapify();
}
//不需要重新 堆化
private void initElementsFromCollection(Collection<? extends E> c) {
Object[] a = c.toArray();
// If c.toArray incorrectly doesn't return Object[], copy it.
if (a.getClass() != Object[].class)
a = Arrays.copyOf(a, a.length, Object[].class);
int len = a.length;
// 此处未能理解。。。。为何是在这种条件下进行校验空元素
if (len == 1 || this.comparator != null)
for (int i = 0; i < len; i++)
if (a[i] == null)
throw new NullPointerException();
this.queue = a;
this.size = a.length;
}
// 只有是从另外一个PriorityQueue初始化时，才不需要重新堆化
private void initFromPriorityQueue(PriorityQueue<? extends E> c) {
if (c.getClass() == PriorityQueue.class) {
this.queue = c.toArray();
this.size = c.size();
} else {
initFromCollection(c);
}
}
- 对于集合作为参数的构造器，其中有一个疑问：当集合类型为SortedSet时，是不需要重新堆化的。难道SortedSet底层的存储结构的存储顺序是和PriorityQueue是一样的逻辑？ toArray返回的数组顺序满足PriortyQueue的要求，意即：权重最小的在最前面，父节点和子节点的位置关系满足如下要求：
Priority queue represented as a balanced binary heap: the two
children of queue[n] are queue[2n+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.
- 添加元素时的扩容过程
在扩容的分配空间阶段会释放锁，分配完成后再重新获取锁。在分配空间时也需要对并发做控制，为了不影响其他的操作，此处使用了UNSAFE来实现并发控制。
/*
* The implementation uses an array-based binary heap, with public
* operations protected with a single lock. However, allocation
* during resizing uses a simple spinlock (used only while not
* holding main lock) in order to allow takes to operate
* concurrently with allocation. This avoids repeated
* postponement of waiting consumers and consequent element
* build-up. The need to back away from lock during allocation
* makes it impossible to simply wrap delegated
* java.util.PriorityQueue operations within a lock, as was done
* in a previous version of this class. To maintain
* interoperability, a plain PriorityQueue is still used during
* serialization, which maintains compatibility at the expense of
* transiently doubling overhead.
* 此队列实现使用了基于数组的二元堆，并用单一的锁来实现公共并发操作的保护！但是，在扩容过程中
* 用了一个简单的自旋锁（仅在没有获取主锁时使用），从而实现了在扩容的过程中也能允许take并发操作。
* 这样避免了重复的推迟等待的消费者以及后续元素的建立。在扩容期间，退出锁的动作，不能再简单的在获取锁的情况下包装委托至
* java.util.PriorityQueue操作，这也是上个版本的实现。为了兼容，在序列化时，仍然使用了一个简单的PriorityQueue, 在保持
* 兼容性的同时，暂时增加了一倍的开销！
*/
private void tryGrow(Object[] array, int oldCap) {
lock.unlock(); // must release and then re-acquire main lock
Object[] newArray = null;
/**
* // 该方法用户比较及替换值
// 第一个参数为要替换的对象本身，第二个参数为值的内存地址
// 第三个参数为变量的预期值，第四个参数为变量要换的值
// 如果变量目前的值等于预期值(第三个参数)，则会将变量的值换成新值(第四个参数)，返回 true
// 如果不等于预期，则不会改变，并返回 false
*
*/
if (allocationSpinLock == 0 &&
UNSAFE.compareAndSwapInt(this, allocationSpinLockOffset,
0, 1)) {
try {
int newCap = oldCap + ((oldCap < 64) ?
(oldCap + 2) : // grow faster if small
(oldCap >> 1));
if (newCap - MAX_ARRAY_SIZE > 0) { // possible overflow
int minCap = oldCap + 1;
if (minCap < 0 || minCap > MAX_ARRAY_SIZE)
throw new OutOfMemoryError();
newCap = MAX_ARRAY_SIZE;
}
//queue 可能已变更
if (newCap > oldCap && queue == array)
newArray = new Object[newCap];
} finally {
allocationSpinLock = 0;
}
}
// 释放资源；重新获取CPU资源
if (newArray == null) // back off if another thread is allocating
Thread.yield();
lock.lock();
//再次检查queue == array， 必须保证queue是最新的
if (newArray != null && queue == array) {
queue = newArray;
System.arraycopy(array, 0, newArray, 0, oldCap);
}
}
public boolean offer(E e) {
if (e == null)
throw new NullPointerException();
final ReentrantLock lock = this.lock;
lock.lock();
int n, cap;
Object[] array;
// 扩容
while ((n = size) >= (cap = (array = queue).length))
tryGrow(array, cap);
try {
Comparator<? super E> cmp = comparator;
if (cmp == null)
siftUpComparable(n, e, array);
else
siftUpUsingComparator(n, e, array, cmp);
size = n + 1;
notEmpty.signal();
} finally {
lock.unlock();
}
return true;
}
- 两种方式来平衡堆，用于不同的场景！
出队时，头部节点移除，根节点空缺，此时将最后一个元素，放置于根节点，不停的下沉，直至比其子节点小或者相等或者变为叶
子节点；
入队时，将元素直接插至最后一个元素的后面，不停的与父节点进行对比，冒泡；直至比其父节点大或者相等或者变为根节点。
在其上两种方法中，都需要根据当前节点获取父节点或者子节点的位置；
当前节点n的子节点：2n+1,2n+2
当前节点n的父节点：（n-1)/2
- 初始化建立二元堆的过程
//初始化堆
private void heapify() {
Object[] array = queue;
int n = size;
// 为何从此处开始呢？代表什么意义？
int half = (n >>> 1) - 1;
Comparator<? super E> cmp = comparator;
if (cmp == null) {
for (int i = half; i >= 0; i--)
siftDownComparable(i, (E) array[i], array, n);
}
else {
for (int i = half; i >= 0; i--)
siftDownUsingComparator(i, (E) array[i], array, n, cmp);
}
}
//将元素x插入数组array的位置k，数组大小为n
private static <T> void siftDownComparable(int k, T x, Object[] array,
int n) {
if (n > 0) {
Comparable<? super T> key = (Comparable<? super T>)x;
//保证为非叶子节点，如果是叶子节点，则停止循环
int half = n >>> 1; // loop while a non-leaf
while (k < half) {
int child = (k << 1) + 1; // assume left child is least
Object c = array[child];
int right = child + 1;
if (right < n &&
((Comparable<? super T>) c).compareTo((T) array[right]) > 0)
c = array[child = right];
if (key.compareTo((T) c) <= 0)
break;
array[k] = c;
k = child;
}
array[k] = key;
}
}
- take方法，没有元素时会被阻塞；使用了lock和lock.condition来实现阻塞！
public E take() throws InterruptedException {
final ReentrantLock lock = this.lock;
//可被打断，要么获取锁，要么被打断；否则将一直处于休眠状态，等待获取锁
lock.lockInterruptibly();
E result;
try {
while ( (result = dequeue()) == null)
// 释放锁资源，被唤醒时需重新获取锁。 被打断或者接到信号，否则将一直等待
//signal, signAll, interupte, spurious wakeup
notEmpty.await();
} finally {
lock.unlock();
}
return result;
}
- poll有两种方法，区别在于是否会返回null。 空参数的poll，在队列为空时会立即返回null；支持超时时间的poll，允许等待超时时间。
public E poll(long timeout, TimeUnit unit) throws InterruptedException {
long nanos = unit.toNanos(timeout);
final ReentrantLock lock = this.lock;
lock.lockInterruptibly();
E result;
try {
while ( (result = dequeue()) == null && nanos > 0)
nanos = notEmpty.awaitNanos(nanos);
} finally {
lock.unlock();
}
return result;
}
- 移除i位置的元素
/**
* Removes the ith element from queue.
*/
private void removeAt(int i) {
Object[] array = queue;
int n = size - 1;
if (n == i) // removed last element
array[i] = null;
else {
E moved = (E) array[n];
array[n] = null;
Comparator<? super E> cmp = comparator;
if (cmp == null)
siftDownComparable(i, moved, array, n);
else
siftDownUsingComparator(i, moved, array, n, cmp);
//节点指针相同 ???
if (array[i] == moved) {
if (cmp == null)
siftUpComparable(i, moved, array);
else
siftUpUsingComparator(i, moved, array, cmp);
}
}
size = n;
}
- iterator方法，遍历时是遍历的一份array备份；但在移除元素时，会移除真正的array里的元素。iterator本身拷贝的数组不会删除元素。
来源：oschina
链接：https://my.oschina.net/838900801/blog/4263584