并发编程网 - ifeve.com

作者：一粟

介绍

Java 6的并发编程包中的SynchronousQueue是一个没有数据缓冲的BlockingQueue，生产者线程对其的插入操作put必须等待消费者的移除操作take，反过来也一样。

不像ArrayBlockingQueue或LinkedListBlockingQueue，SynchronousQueue内部并没有数据缓存空间，你不能调用peek()方法来看队列中是否有数据元素，因为数据元素只有当你试着取走的时候才可能存在，不取走而只想偷窥一下是不行的，当然遍历这个队列的操作也是不允许的。队列头元素是第一个排队要插入数据的线程，而不是要交换的数据。数据是在配对的生产者和消费者线程之间直接传递的，并不会将数据缓冲数据到队列中。可以这样来理解：生产者和消费者互相等待对方，握手，然后一起离开。

SynchronousQueue的一个使用场景是在线程池里。Executors.newCachedThreadPool()就使用了SynchronousQueue，这个线程池根据需要（新任务到来时）创建新的线程，如果有空闲线程则会重复使用，线程空闲了60秒后会被回收。

实现原理

阻塞队列的实现方法有许多：

阻塞算法实现

阻塞算法实现通常在内部采用一个锁来保证多个线程中的put()和take()方法是串行执行的。采用锁的开销是比较大的，还会存在一种情况是线程A持有线程B需要的锁，B必须一直等待A释放锁，即使A可能一段时间内因为B的优先级比较高而得不到时间片运行。所以在高性能的应用中我们常常希望规避锁的使用。

[code]public class NativeSynchronousQueue<E> {
boolean putting = false;
E item = null;

public synchronized E take() throws InterruptedException {
while (item == null)
wait();
E e = item;
item = null;
notifyAll();
return e;
}

public synchronized void put(E e) throws InterruptedException {
if (e==null) return;
while (putting)
wait();
putting = true;
item = e;
notifyAll();
while (item!=null)
wait();
putting = false;
notifyAll();
}
}
[/code]

信号量实现

经典同步队列实现采用了三个信号量，代码很简单，比较容易理解：

[code lang=”java”]
public class SemaphoreSynchronousQueue<E> {
E item = null;
Semaphore sync = new Semaphore(0);
Semaphore send = new Semaphore(1);
Semaphore recv = new Semaphore(0);

public E take() throws InterruptedException {
recv.acquire();
E x = item;
sync.release();
send.release();
return x;
}

public void put (E x) throws InterruptedException{
send.acquire();
item = x;
recv.release();
sync.acquire();
}
}
[/code]

在多核机器上，上面方法的同步代价仍然较高，操作系统调度器需要上千个时间片来阻塞或唤醒线程，而上面的实现即使在生产者put()时已经有一个消费者在等待的情况下，阻塞和唤醒的调用仍然需要。

Java 5实现

[code lang=”java”]
public class Java5SynchronousQueue<E> {
ReentrantLock qlock = new ReentrantLock();
Queue waitingProducers = new Queue();
Queue waitingConsumers = new Queue();

static class Node extends AbstractQueuedSynchronizer {
E item;
Node next;

Node(Object x) { item = x; }
void waitForTake() { /* (uses AQS) */ }
E waitForPut() { /* (uses AQS) */ }
}

public E take() {
Node node;
boolean mustWait;
qlock.lock();
node = waitingProducers.pop();
if(mustWait = (node == null))
node = waitingConsumers.push(null);
qlock.unlock();

if (mustWait)
return node.waitForPut();
else
return node.item;
}

public void put(E e) {
Node node;
boolean mustWait;
qlock.lock();
node = waitingConsumers.pop();
if (mustWait = (node == null))
node = waitingProducers.push(e);
qlock.unlock();

if (mustWait)
node.waitForTake();
else
node.item = e;
}
}
[/code]

Java 5的实现相对来说做了一些优化，只使用了一个锁，使用队列代替信号量也可以允许发布者直接发布数据，而不是要首先从阻塞在信号量处被唤醒。

Java6实现

Java 6的SynchronousQueue的实现采用了一种性能更好的无锁算法 — 扩展的“Dual stack and Dual queue”算法。性能比Java5的实现有较大提升。竞争机制支持公平和非公平两种：非公平竞争模式使用的数据结构是后进先出栈(Lifo Stack)；公平竞争模式则使用先进先出队列（Fifo Queue），性能上两者是相当的，一般情况下，Fifo通常可以支持更大的吞吐量，但Lifo可以更大程度的保持线程的本地化。

代码实现里的Dual Queue或Stack内部是用链表(LinkedList)来实现的，其节点状态为以下三种情况：

1. 持有数据 – put()方法的元素
2. 持有请求 – take()方法
3. 空

这个算法的特点就是任何操作都可以根据节点的状态判断执行，而不需要用到锁。

其核心接口是Transfer，生产者的put或消费者的take都使用这个接口，根据第一个参数来区别是入列（栈）还是出列（栈）。

[code lang=”java”]
/**
* Shared internal API for dual stacks and queues.
*/
static abstract class Transferer {
/**
* Performs a put or take.
*
* @param e if non-null, the item to be handed to a consumer;
* if null, requests that transfer return an item
* offered by producer.
* @param timed if this operation should timeout
* @param nanos the timeout, in nanoseconds
* @return if non-null, the item provided or received; if null,
* the operation failed due to timeout or interrupt —
* the caller can distinguish which of these occurred
* by checking Thread.interrupted.
*/
abstract Object transfer(Object e, boolean timed, long nanos);
}
[/code]
TransferQueue实现如下(摘自Java 6源代码)，入列和出列都基于Spin和CAS方法：

[code lang=”java”]
/**
* Puts or takes an item.
*/
Object transfer(Object e, boolean timed, long nanos) {
/* Basic algorithm is to loop trying to take either of
* two actions:
*
* 1. If queue apparently empty or holding same-mode nodes,
* try to add node to queue of waiters, wait to be
* fulfilled (or cancelled) and return matching item.
*
* 2. If queue apparently contains waiting items, and this
* call is of complementary mode, try to fulfill by CAS’ing
* item field of waiting node and dequeuing it, and then
* returning matching item.
*
* In each case, along the way, check for and try to help
* advance head and tail on behalf of other stalled/slow
* threads.
*
* The loop starts off with a null check guarding against
* seeing uninitialized head or tail values. This never
* happens in current SynchronousQueue, but could if
* callers held non-volatile/final ref to the
* transferer. The check is here anyway because it places
* null checks at top of loop, which is usually faster
* than having them implicitly interspersed.
*/

QNode s = null; // constructed/reused as needed
boolean isData = (e != null);

for (;;) {
QNode t = tail;
QNode h = head;
if (t == null || h == null) // saw uninitialized value
continue; // spin

if (h == t || t.isData == isData) { // empty or same-mode
QNode tn = t.next;
if (t != tail) // inconsistent read
continue;
if (tn != null) { // lagging tail
advanceTail(t, tn);
continue;
}
if (timed &amp;&amp; nanos &lt;= 0) // can’t wait
return null;
if (s == null)
s = new QNode(e, isData);
if (!t.casNext(null, s)) // failed to link in
continue;

advanceTail(t, s); // swing tail and wait
Object x = awaitFulfill(s, e, timed, nanos);
if (x == s) { // wait was cancelled
clean(t, s);
return null;
}

if (!s.isOffList()) { // not already unlinked
advanceHead(t, s); // unlink if head
if (x != null) // and forget fields
s.item = s;
s.waiter = null;
}
return (x != null)? x : e;

} else { // complementary-mode
QNode m = h.next; // node to fulfill
if (t != tail || m == null || h != head)
continue; // inconsistent read

Object x = m.item;
if (isData == (x != null) || // m already fulfilled
x == m || // m cancelled
!m.casItem(x, e)) { // lost CAS
advanceHead(h, m); // dequeue and retry
continue;
}

advanceHead(h, m); // successfully fulfilled
LockSupport.unpark(m.waiter);
return (x != null)? x : e;
}
}
}
[/code]

参考文章

1. Javadoc of SynchronousQueue
2. Scalable Synchronous Queues
3. Nonblocking Concurrent Data Structures with Condition Synchronization