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# Java多线程的阻塞队列实现
## 一、阻塞队列概述
### 1.1 什么是阻塞队列
阻塞队列(BlockingQueue)是Java并发包(java.util.concurrent)中提供的一种线程安全的队列实现。它在普通队列的基础上增加了两个附加操作:
1. 当队列为空时,获取元素的线程会等待队列变为非空
2. 当队列满时,存储元素的线程会等待队列可用
这种特性使得阻塞队列成为生产者-消费者模式的理想实现方式,无需开发者手动实现线程间的等待/通知机制。
### 1.2 阻塞队列的核心特性
- **线程安全**:所有操作都是原子性的
- **阻塞机制**:提供put/take等阻塞方法
- **容量限制**:可以是有界队列或无界队列
- **公平性选项**:部分实现支持公平访问策略
### 1.3 Java中的阻塞队列实现类
Java并发包提供了多种阻塞队列实现:
1. ArrayBlockingQueue:基于数组的有界阻塞队列
2. LinkedBlockingQueue:基于链表的可选有界阻塞队列
3. PriorityBlockingQueue:支持优先级排序的无界阻塞队列
4. DelayQueue:使用优先级队列实现的无界阻塞队列
5. SynchronousQueue:不存储元素的阻塞队列
6. LinkedTransferQueue:基于链表的无界阻塞队列
7. LinkedBlockingDeque:基于链表的双向阻塞队列
## 二、阻塞队列的核心方法
### 2.1 插入操作
| 方法 | 说明 | 特殊行为 |
|------|------|----------|
| add(E e) | 添加元素到队列 | 队列满时抛出IllegalStateException |
| offer(E e) | 添加元素到队列 | 队列满时返回false |
| put(E e) | 添加元素到队列 | 队列满时阻塞等待 |
| offer(E e, long timeout, TimeUnit unit) | 添加元素到队列 | 队列满时等待指定时间 |
### 2.2 移除操作
| 方法 | 说明 | 特殊行为 |
|------|------|----------|
| remove() | 移除并返回队列头元素 | 队列空时抛出NoSuchElementException |
| poll() | 移除并返回队列头元素 | 队列空时返回null |
| take() | 移除并返回队列头元素 | 队列空时阻塞等待 |
| poll(long timeout, TimeUnit unit) | 移除并返回队列头元素 | 队列空时等待指定时间 |
### 2.3 检查操作
| 方法 | 说明 | 特殊行为 |
|------|------|----------|
| element() | 返回队列头元素 | 队列空时抛出NoSuchElementException |
| peek() | 返回队列头元素 | 队列空时返回null |
## 三、阻塞队列的实现原理
### 3.1 锁与条件变量
阻塞队列的核心实现依赖于ReentrantLock和Condition:
```java
// 以ArrayBlockingQueue为例
final ReentrantLock lock;
private final Condition notEmpty;
private final Condition notFull;
public ArrayBlockingQueue(int capacity, boolean fair) {
// 省略其他初始化代码
lock = new ReentrantLock(fair);
notEmpty = lock.newCondition();
notFull = lock.newCondition();
}
以put()方法为例:
public void put(E e) throws InterruptedException {
Objects.requireNonNull(e);
final ReentrantLock lock = this.lock;
lock.lockInterruptibly();
try {
while (count == items.length)
notFull.await(); // 队列满时等待
enqueue(e); // 实际入队操作
} finally {
lock.unlock();
}
}
以enqueue()方法为例:
private void enqueue(E e) {
final Object[] items = this.items;
items[putIndex] = e;
if (++putIndex == items.length) putIndex = 0;
count++;
notEmpty.signal(); // 唤醒等待的消费者线程
}
public class ArrayBlockingQueue<E> extends AbstractQueue<E>
implements BlockingQueue<E>, java.io.Serializable {
final Object[] items; // 存储元素的数组
int takeIndex; // 下一个要取出的元素索引
int putIndex; // 下一个要放入的元素索引
int count; // 当前元素数量
// 锁和条件变量
final ReentrantLock lock;
private final Condition notEmpty;
private final Condition notFull;
// 迭代器
transient Itrs itrs;
}
入队操作:
public boolean offer(E e) {
Objects.requireNonNull(e);
final ReentrantLock lock = this.lock;
lock.lock();
try {
if (count == items.length)
return false;
else {
enqueue(e);
return true;
}
} finally {
lock.unlock();
}
}
出队操作:
public E poll() {
final ReentrantLock lock = this.lock;
lock.lock();
try {
return (count == 0) ? null : dequeue();
} finally {
lock.unlock();
}
}
public class LinkedBlockingQueue<E> extends AbstractQueue<E>
implements BlockingQueue<E>, java.io.Serializable {
// 节点类
static class Node<E> {
E item;
Node<E> next;
Node(E x) { item = x; }
}
private final int capacity; // 容量限制
private final AtomicInteger count = new AtomicInteger(); // 当前元素数量
// 头节点和尾节点
transient Node<E> head;
private transient Node<E> last;
// 分离的锁
private final ReentrantLock takeLock = new ReentrantLock();
private final Condition notEmpty = takeLock.newCondition();
private final ReentrantLock putLock = new ReentrantLock();
private final Condition notFull = putLock.newCondition();
}
入队操作:
public void put(E e) throws InterruptedException {
if (e == null) throw new NullPointerException();
int c = -1;
Node<E> node = new Node<E>(e);
final ReentrantLock putLock = this.putLock;
final AtomicInteger count = this.count;
putLock.lockInterruptibly();
try {
while (count.get() == capacity) {
notFull.await();
}
enqueue(node);
c = count.getAndIncrement();
if (c + 1 < capacity)
notFull.signal();
} finally {
putLock.unlock();
}
if (c == 0)
signalNotEmpty();
}
出队操作:
public E take() throws InterruptedException {
E x;
int c = -1;
final AtomicInteger count = this.count;
final ReentrantLock takeLock = this.takeLock;
takeLock.lockInterruptibly();
try {
while (count.get() == 0) {
notEmpty.await();
}
x = dequeue();
c = count.getAndDecrement();
if (c > 1)
notEmpty.signal();
} finally {
takeLock.unlock();
}
if (c == capacity)
signalNotFull();
return x;
}
基于堆结构的优先级阻塞队列:
public class PriorityBlockingQueue<E> extends AbstractQueue<E>
implements BlockingQueue<E>, java.io.Serializable {
private transient Object[] queue;
private transient int size;
private transient Comparator<? super E> comparator;
private final ReentrantLock lock;
private final Condition notEmpty;
// 扩容时使用的自旋锁
private transient volatile int allocationSpinLock;
}
特点: - 无界队列(自动扩容) - 元素必须实现Comparable或提供Comparator - 出队顺序由优先级决定
用于实现延迟任务的队列:
public class DelayQueue<E extends Delayed> extends AbstractQueue<E>
implements BlockingQueue<E> {
private final transient ReentrantLock lock = new ReentrantLock();
private final PriorityQueue<E> q = new PriorityQueue<E>();
private final Condition available = lock.newCondition();
private Thread leader;
}
特点: - 元素必须实现Delayed接口 - 只有到期元素才能被取出 - 应用场景:缓存过期、定时任务调度
不存储元素的阻塞队列:
public class SynchronousQueue<E> extends AbstractQueue<E>
implements BlockingQueue<E>, java.io.Serializable {
abstract static class Transferer<E> {
abstract E transfer(E e, boolean timed, long nanos);
}
// 两种不同的传输策略
static final class TransferStack<E> extends Transferer<E> { /*...*/ }
static final class TransferQueue<E> extends Transferer<E> { /*...*/ }
}
特点: - 每个插入操作必须等待一个移除操作 - 吞吐量高于LinkedBlockingQueue和ArrayBlockingQueue - 适合传递性场景
经典实现方式:
// 生产者
class Producer implements Runnable {
private final BlockingQueue<String> queue;
public Producer(BlockingQueue<String> queue) {
this.queue = queue;
}
public void run() {
try {
while (true) {
String item = produceItem();
queue.put(item);
Thread.sleep(100);
}
} catch (InterruptedException ex) {
// 处理中断
}
}
private String produceItem() {
// 生产逻辑
}
}
// 消费者
class Consumer implements Runnable {
private final BlockingQueue<String> queue;
public Consumer(BlockingQueue<String> queue) {
this.queue = queue;
}
public void run() {
try {
while (true) {
String item = queue.take();
consumeItem(item);
}
} catch (InterruptedException ex) {
// 处理中断
}
}
private void consumeItem(String item) {
// 消费逻辑
}
}
Java线程池使用阻塞队列作为工作队列:
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue<Runnable> workQueue) {
// 实现代码
}
实现简单的消息队列:
public class SimpleMessageQueue {
private final BlockingQueue<Message> queue;
public SimpleMessageQueue(int capacity) {
this.queue = new LinkedBlockingQueue<>(capacity);
}
public void send(Message msg) throws InterruptedException {
queue.put(msg);
}
public Message receive() throws InterruptedException {
return queue.take();
}
}
场景: 生产者等待队列空间,消费者等待生产者释放锁
解决方案: - 使用双锁设计的LinkedBlockingQueue - 设置合理的超时时间 - 避免在持有锁时调用外部方法
场景: 无界队列持续增长导致OOM
解决方案: - 使用有界队列 - 实现自定义的拒绝策略 - 监控队列大小
场景: 单一锁成为系统瓶颈
解决方案: - 使用分离锁的实现(如LinkedBlockingQueue) - 考虑无锁队列(如ConcurrentLinkedQueue) - 分区处理(多个队列)
public class SimpleBlockingQueue<E> {
private final E[] items;
private int putIndex, takeIndex, count;
private final ReentrantLock lock = new ReentrantLock();
private final Condition notFull = lock.newCondition();
private final Condition notEmpty = lock.newCondition();
public SimpleBlockingQueue(int capacity) {
this.items = (E[]) new Object[capacity];
}
public void put(E e) throws InterruptedException {
Objects.requireNonNull(e);
lock.lockInterruptibly();
try {
while (count == items.length)
notFull.await();
items[putIndex] = e;
if (++putIndex == items.length) putIndex = 0;
count++;
notEmpty.signal();
} finally {
lock.unlock();
}
}
public E take() throws InterruptedException {
lock.lockInterruptibly();
try {
while (count == 0)
notEmpty.await();
E e = items[takeIndex];
items[takeIndex] = null;
if (++takeIndex == items.length) takeIndex = 0;
count--;
notFull.signal();
return e;
} finally {
lock.unlock();
}
}
}
public class CASBlockingQueue<E> {
private static class Node<E> {
volatile E item;
volatile Node<E> next;
Node(E item) {
this.item = item;
}
}
private volatile Node<E> head;
private volatile Node<E> tail;
private final AtomicInteger count = new AtomicInteger(0);
private final int capacity;
public CASBlockingQueue(int capacity) {
if (capacity <= 0) throw new IllegalArgumentException();
this.capacity = capacity;
head = tail = new Node<>(null);
}
public boolean offer(E e) {
Objects.requireNonNull(e);
Node<E> newNode = new Node<>(e);
for (;;) {
Node<E> currentTail = tail;
Node<E> tailNext = currentTail.next;
if (currentTail == tail) {
if (tailNext != null) {
// 帮助推进尾节点
compareAndSetTail(tail, tailNext);
} else {
if (count.get() < capacity) {
if (compareAndSetNext(currentTail, null, newNode)) {
compareAndSetTail(tail, newNode);
count.incrementAndGet();
return true;
}
} else {
return false;
}
}
}
}
}
// 省略其他方法和CAS操作实现
}
场景 | 推荐队列 | 理由 |
---|---|---|
固定大小线程池 | ArrayBlockingQueue | 简单高效 |
高并发生产者消费者 | LinkedBlockingQueue | 吞吐量高 |
任务优先级处理 | PriorityBlockingQueue | 支持优先级 |
延迟任务调度 | DelayQueue | 内置延迟支持 |
直接传递任务 | SynchronousQueue | 零容量设计 |
本文共约9350字,详细介绍了Java多线程中阻塞队列的实现原理、各种实现类的特点、应用场景以及性能优化建议。 “`
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