PriorityBlockingQueue
PriorityBlockingQueue 能解决什么问题?什么时候使用 PriorityBlockingQueue?
1)PriorityBlockingQueue 是基于优先级堆实现的线程安全的、无界、优先级、阻塞队列。
2)队列的元素按照其自然顺序进行排序,或者根据构造队列时提供的 Comparator 进行排序。
take 操作会移除并返回优先级最高的元素,如果队列为空,则当前线程被阻塞。
如何使用 PriorityBlockingQueue?
1)在并发场景下,需要按照指定的优先级获取元素时。
使用 PriorityBlockingQueue 有什么风险?
1)PriorityBlockingQueue 是无界的阻塞队列,它并不会阻塞生产者插入元素,
当生产速率大于消费速率时,时间一长,可能导致内存溢出。
PriorityBlockingQueue 核心操作的实现原理?
/**
* 默认的数组容量
*/
private static final int DEFAULT_INITIAL_CAPACITY = 11;
/**
* 最大的数组容量
*/
private static final int MAX_ARRAY_SIZE = Integer.MAX_VALUE - 8;
/**
* 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.
*/
private transient Object[] queue;
/**
* 优先级队列中的元素总数
*/
private transient int size;
/**
* 元素比较器,如果按照自然顺序进行排序,则为 null
*/
private transient Comparator<? super E> comparator;
/**
* 控制访问的可重入互斥锁
*/
private final ReentrantLock lock;
/**
* 队列为空时,目标线程将在非空条件阻塞等待
*/
private final Condition notEmpty;
/**
* 扩容时的锁,通过 CAS 写入
*/
private transient volatile int allocationSpinLock;
/**
* 创建一个初始容量为 11,按照自然顺序排序的 PriorityBlockingQueue 实例
*/
public PriorityBlockingQueue() {
this(PriorityBlockingQueue.DEFAULT_INITIAL_CAPACITY, null);
}
/**
* 创建一个初始容量为 initialCapacity,按照自然顺序排序的 PriorityBlockingQueue 实例
*/
public PriorityBlockingQueue(int initialCapacity) {
this(initialCapacity, null);
}
/**
* 创建一个初始容量为 initialCapacity,按照自然顺序排序的 comparator 实例
*/
public PriorityBlockingQueue(int initialCapacity,
Comparator<? super E> comparator) {
if (initialCapacity < 1) {
throw new IllegalArgumentException();
}
this.lock = new ReentrantLock();
this.notEmpty = lock.newCondition();
this.comparator = comparator;
this.queue = new Object[initialCapacity];
}
/**
* 将目标元素插入到队列中,由于是无界的,不会被阻塞
*/
@Override
public void put(E e) {
offer(e); // never need to block
}
@Override
public boolean offer(E e) {
if (e == null) {
throw new NullPointerException();
}
final ReentrantLock lock = this.lock;
lock.lock();
/**
* n:length
* cap:capacity
*/
int n, cap;
Object[] array;
// 元素个数超出队列长度,则进行扩容
while ((n = size) >= (cap = (array = queue).length)) {
tryGrow(array, cap);
}
try {
final Comparator<? super E> cmp = comparator;
if (cmp == null) {
// 自然顺序的插入
PriorityBlockingQueue.siftUpComparable(n, e, array);
} else {
// 使用指定比较器的插入
PriorityBlockingQueue.siftUpUsingComparator(n, e, array, cmp);
}
size = n + 1;
// 唤醒在非空条件上阻塞等待的线程
notEmpty.signal();
} finally {
lock.unlock();
}
return true;
}
private void tryGrow(Object[] array, int oldCap) {
lock.unlock(); // must release and then re-acquire main lock
Object[] newArray = null;
// 当前没有线程在执行扩容 && 原子更新扩容标识为 1
if (allocationSpinLock == 0 &&
PriorityBlockingQueue.ALLOCATIONSPINLOCK.compareAndSet(this, 0, 1)) {
try {
/**
* 1)旧容量小于 64,执行【双倍+2】扩容
* 2)旧容量大于等于 64,执行1.5倍向下取整扩容
*/
int newCap = oldCap + (oldCap < 64 ?
oldCap + 2 : // grow faster if small
oldCap >> 1);
// 新容量超出最大容量
if (newCap - PriorityBlockingQueue.MAX_ARRAY_SIZE > 0) { // possible overflow
final int minCap = oldCap + 1;
// 如果已经溢出,则抛出 OutOfMemoryError 异常
if (minCap < 0 || minCap > PriorityBlockingQueue.MAX_ARRAY_SIZE) {
throw new OutOfMemoryError();
}
// 写入最大容量
newCap = PriorityBlockingQueue.MAX_ARRAY_SIZE;
}
// 创建新的对象数组
if (newCap > oldCap && queue == array) {
newArray = new Object[newCap];
}
} finally {
// 重置扩容标记
allocationSpinLock = 0;
}
}
// 说明已经有线程在执行扩容,则等待其扩容完成
if (newArray == null) {
Thread.yield();
}
lock.lock();
if (newArray != null && queue == array) {
// 扩容成功的线程会将元素从旧数组拷贝到新数组中
queue = newArray;
System.arraycopy(array, 0, newArray, 0, oldCap);
}
}
private static <T> void siftUpComparable(int k, T x, Object[] array) {
final Comparable<? super T> key = (Comparable<? super T>) x;
// 插入元素的目标索引
while (k > 0) {
// 计算父节点索引
final int parent = k - 1 >>> 1;
// 读取父节点值
final Object e = array[parent];
// 新增元素已经 >= 当前节点,则无需上移
if (key.compareTo((T) e) >= 0) {
break;
}
// 父节点元素下移
array[k] = e;
// 递归比较祖父节点
k = parent;
}
// 插入目标元素
array[k] = key;
}
/**
* 实现逻辑和 siftUpComparable 一致
* created by ZXD at 6 Dec 2018 T 21:36:14
* @param k
* @param x
* @param array
* @param cmp
*/
private static <T> void siftUpUsingComparator(int k, T x, Object[] array,
Comparator<? super T> cmp) {
while (k > 0) {
final int parent = k - 1 >>> 1;
final Object e = array[parent];
if (cmp.compare(x, (T) e) >= 0) {
break;
}
array[k] = e;
k = parent;
}
array[k] = x;
}
- 读取元素
- 如果队列为空,则阻塞等待有可用元素后重试,否则移除并返回优先级最高的元素
/**
* 如果队列为空,则阻塞等待有可用元素后重试,否则移除并返回优先级最高的元素
*/
@Override
public E take() throws InterruptedException {
final ReentrantLock lock = this.lock;
lock.lockInterruptibly();
E result;
try {
// 尝试移除并返回优先级最高的元素
while ( (result = dequeue()) == null) {
// 当前线程在非空条件上阻塞等待,被唤醒后重试
notEmpty.await();
}
} finally {
lock.unlock();
}
return result;
}
private E dequeue() {
// 计算尾部元素索引
final int n = size - 1;
// 队列为空,则返回 null
if (n < 0) {
return null;
} else {
final Object[] array = queue;
// 读取优先级最高的元素
final E result = (E) array[0];
// 读取尾部元素
final E x = (E) array[n];
// 清空尾部元素
array[n] = null;
final Comparator<? super E> cmp = comparator;
if (cmp == null) {
PriorityBlockingQueue.siftDownComparable(0, x, array, n);
} else {
PriorityBlockingQueue.siftDownUsingComparator(0, x, array, n, cmp);
}
size = n;
return result;
}
}
/**
* 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 需要填充的目标索引
* @param x 需要插入的目标元素
* @param array 持有对象的数组
* @param n 堆大小
*/
private static <T> void siftDownComparable(int k, T x, Object[] array,
int n) {
if (n > 0) {
final Comparable<? super T> key = (Comparable<? super T>)x;
// 计算二分索引
final int half = n >>> 1; // loop while a non-leaf
while (k < half) {
// 计算左子节点索引
int child = (k << 1) + 1; // assume left child is least
// 读取节点值
Object c = array[child];
// 计算右子节点索引
final int right = child + 1;
/**
* 右子节点索引小于目标堆大小 &&
* 左子节点值 > 右子节点值
*/
if (right < n &&
((Comparable<? super T>) c).compareTo((T) array[right]) > 0) {
// 读取右子节点值,更新查找节点索引
c = array[child = right];
}
// 目标键已经小于查找节点,则可以直接插入
if (key.compareTo((T) c) <= 0) {
break;
}
// 否则,提升子节点为父节点
array[k] = c;
// 迭代处理子节点
k = child;
}
// 插入目标值
array[k] = key;
}
}
private static <T> void siftDownUsingComparator(int k, T x, Object[] array,
int n,
Comparator<? super T> cmp) {
if (n > 0) {
final int half = n >>> 1;
while (k < half) {
int child = (k << 1) + 1;
Object c = array[child];
final int right = child + 1;
if (right < n && cmp.compare((T) c, (T) array[right]) > 0) {
c = array[child = right];
}
if (cmp.compare(x, (T) c) <= 0) {
break;
}
array[k] = c;
k = child;
}
array[k] = x;
}
}
- 如果队列为空,则立即返回 null;否则移除并返回优先级最高的元素
/**
* 如果队列为空,则立即返回 null;否则移除并返回优先级最高的元素。
* created by ZXD at 6 Dec 2018 T 21:38:57
* @return
*/
@Override
public E poll() {
final ReentrantLock lock = this.lock;
lock.lock();
try {
return dequeue();
} finally {
lock.unlock();
}
}
- 在指定的超时时间内尝试移除并返回优先级最高的元素,如果已经超时,则返回 null
/**
* 在指定的超时时间内尝试移除并返回优先级最高的元素,如果已经超时,则返回 null.
* created by ZXD at 6 Dec 2018 T 21:40:03
* @param timeout
* @param unit
* @return
* @throws InterruptedException
*/
@Override
public E poll(long timeout, TimeUnit unit) throws InterruptedException {
long nanos = unit.toNanos(timeout);
final ReentrantLock lock = this.lock;
lock.lockInterruptibly();
E result;
try {
// 尝试移除并返回优先级最高的元素 && 未超时
while ( (result = dequeue()) == null && nanos > 0) {
// 当前线程在非空条件上阻塞等待,被唤醒后重试
nanos = notEmpty.awaitNanos(nanos);
}
} finally {
lock.unlock();
}
return result;
}