可重入锁（ReentrantLock）是 synchronized 关键字的扩展，更加灵活。还有一种ReentrantLock应用场景是和Condition搭配使用，实现多线程环境下等待状态条件的功能。Object.wait 和 Object.notify 是和 synchronized 配合使用的，条件变量Condition是和ReentrantLock相关联的。
接下来先通过一个Demo看看Condition的用法，然后列举两个应用的地方，最后分析其源码实现。
先通过一个Demo看看怎么使用Condition，主线程通知条件满足，通过另一个线程继续运行，可以看到的是Condition.wait/signal方法需要和一个ReentrantLock绑定。
public class ReenterLockCondition implements Runnable {
public static ReentrantLock lock = new ReentrantLock();
public static Condition condition = lock.newCondition();
@Override
public void run() {
try {
lock.lock();
condition.await();
System.out.println(String.format("条件满足，线程%s运行！", Thread.currentThread().getName()));
} catch (InterruptedException e) {
e.printStackTrace();
} finally {
lock.unlock();
}
}
public static void main(String args[]) throws InterruptedException {
ReenterLockCondition reenterLockCondition = new ReenterLockCondition();
Thread thread1 = new Thread(reenterLockCondition);
thread1.setName("T1");
thread1.start();
Thread.sleep(2000);
System.out.println("通知T1条件满足");
lock.lock();
condition.signal();
lock.unlock();
}
}
JDK并发包中的 ArrayBlockingQueue 就使用了Condition来同步队列的空/满状态。先看条件变量的定义：
/** Main lock guarding all access */
final ReentrantLock lock;
/** Condition for waiting takes */
private final Condition notEmpty;
/** Condition for waiting puts */
private final Condition notFull;
public ArrayBlockingQueue(int capacity, boolean fair) {
if (capacity <= 0)
throw new IllegalArgumentException();
this.items = new Object[capacity];
lock = new ReentrantLock(fair);
notEmpty = lock.newCondition();
notFull = lock.newCondition();
}ArrayBlockingQueue 构造的时候初始化了2个条件变量：非空，非满，他们都是和同一个重入锁关联的。
元素入队的时候，如果队列一直满的话就一直阻塞等待非满条件为真，否则的话就插入对应的元素，并且通知非空条件为真。
public void put(E e) throws InterruptedException {
checkNotNull(e);
final ReentrantLock lock = this.lock;
lock.lockInterruptibly();
try {
while (count == items.length)
notFull.await();
enqueue(e);
} finally {
lock.unlock();
}
}
private void enqueue(E x) {
// assert lock.getHoldCount() == 1;
// assert items[putIndex] == null;
final Object[] items = this.items;
items[putIndex] = x;
if (++putIndex == items.length)
putIndex = 0;
count++;
notEmpty.signal();
}同样的，出队的时候，如果队列没有元素就等待非空的条件为真，否则出队，并通知非满条件为真。
public E take() throws InterruptedException {
final ReentrantLock lock = this.lock;
lock.lockInterruptibly();
try {
while (count == 0)
notEmpty.await();
return dequeue();
} finally {
lock.unlock();
}
}
private E dequeue() {
// assert lock.getHoldCount() == 1;
// assert items[takeIndex] != null;
final Object[] items = this.items;
@SuppressWarnings("unchecked")
E x = (E) items[takeIndex];
items[takeIndex] = null;
if (++takeIndex == items.length)
takeIndex = 0;
count--;
if (itrs != null)
itrs.elementDequeued();
notFull.signal();
return x;
}
KafkaProducer里面有一个buffer pool的概念，BufferPool里面内存分配，回收过程也有用到条件变量。
public ByteBuffer allocate(int size, long maxTimeToBlockMs) throws InterruptedException {
this.lock.lock();
try {
// check if we have a free buffer of the right size pooled
if (size == poolableSize && !this.free.isEmpty())
return this.free.pollFirst();
// now check if the request is immediately satisfiable with the
// memory on hand or if we need to block
int freeListSize = this.free.size() * this.poolableSize;
if (this.availableMemory + freeListSize >= size) {
// 不断释放free队列中的buffer，直到可用内存>size
// we have enough unallocated or pooled memory to immediately
// satisfy the request
freeUp(size);
this.availableMemory -= size;
lock.unlock();
// 使用的不是free队列中的buffer，而是直接分配HeapByteBuffer
return ByteBuffer.allocate(size);
} else {
// 没有足够空间，阻塞
// we are out of memory and will have to block
int accumulated = 0;
ByteBuffer buffer = null;
Condition moreMemory = this.lock.newCondition();
long remainingTimeToBlockNs = TimeUnit.MILLISECONDS.toNanos(maxTimeToBlockMs);
this.waiters.addLast(moreMemory);
// loop over and over until we have a buffer or have reserved
// enough memory to allocate one
while (accumulated < size) {
long startWaitNs = time.nanoseconds();
long timeNs;
boolean waitingTimeElapsed;
try {
waitingTimeElapsed = !moreMemory.await(remainingTimeToBlockNs, TimeUnit.NANOSECONDS);
} catch (InterruptedException e) {
this.waiters.remove(moreMemory);
throw e;
} finally {
long endWaitNs = time.nanoseconds();
timeNs = Math.max(0L, endWaitNs - startWaitNs);
this.waitTime.record(timeNs, time.milliseconds());
}
if (waitingTimeElapsed) {
this.waiters.remove(moreMemory);
throw new TimeoutException("Failed to allocate memory within the configured max blocking time " + maxTimeToBlockMs + " ms.");
}
remainingTimeToBlockNs -= timeNs;
// check if we can satisfy this request from the free list,
// otherwise allocate memory
if (accumulated == 0 && size == this.poolableSize && !this.free.isEmpty()) {
// just grab a buffer from the free list
buffer = this.free.pollFirst();
accumulated = size;
} else {
// 先分配一部分空间
// we'll need to allocate memory, but we may only get
// part of what we need on this iteration
freeUp(size - accumulated);
int got = (int) Math.min(size - accumulated, this.availableMemory);
this.availableMemory -= got;
accumulated += got;
}
}
// 成功分配空间后，移除条件变量
// remove the condition for this thread to let the next thread
// in line start getting memory
Condition removed = this.waiters.removeFirst();
if (removed != moreMemory)
throw new IllegalStateException("Wrong condition: this shouldn't happen.");
// 如果还有剩余空间，还有等待线程，则唤醒
// signal any additional waiters if there is more memory left
// over for them
if (this.availableMemory > 0 || !this.free.isEmpty()) {
if (!this.waiters.isEmpty())
this.waiters.peekFirst().signal();
}
// unlock and return the buffer
lock.unlock();
if (buffer == null)
return ByteBuffer.allocate(size);
else
return buffer;
}
} finally {
if (lock.isHeldByCurrentThread())
lock.unlock();
}
}
public void deallocate(ByteBuffer buffer, int size) {
lock.lock();
try {
// 如果是poolableSize大小的buffer，则入free队列管理
if (size == this.poolableSize && size == buffer.capacity()) {
buffer.clear();
this.free.add(buffer);
} else {
// 否则直接增加大小，分配的buffer由GC回收
this.availableMemory += size;
}
// 唤醒一个因内存分配得不到满足而阻塞的线程
Condition moreMem = this.waiters.peekFirst();
if (moreMem != null)
moreMem.signal();
} finally {
lock.unlock();
}
} 接下来看看条件变量是怎么实现的？可重入锁关联的条件变量实现类是AQS内部类ConditionObject，接下来通过其中的await和signal方法的源码看看Condition的实现。
调用 Condition.await 方法前需要拥有锁，await 会释放锁fullyRelease。
public final void await() throws InterruptedException {
if (Thread.interrupted())
throw new InterruptedException();
Node node = addConditionWaiter();
// 释放关联的锁
int savedState = fullyRelease(node);
int interruptMode = 0;
// 如果该节点没有放入同步队列(sync queue)，则阻塞等待
while (!isOnSyncQueue(node)) {
LockSupport.park(this);
if ((interruptMode = checkInterruptWhileWaiting(node)) != 0)
break;
}
// 节点进入了同步队列，则争用锁，锁获取成功后，await就退出了
if (acquireQueued(node, savedState) && interruptMode != THROW_IE)
interruptMode = REINTERRUPT;
if (node.nextWaiter != null) // clean up if cancelled
unlinkCancelledWaiters();
if (interruptMode != 0)
reportInterruptAfterWait(interruptMode);
}将当前线程加入到条件等待队列。
// 新增一个条件节点
private Node addConditionWaiter() {
Node t = lastWaiter;
// If lastWaiter is cancelled, clean out.
if (t != null && t.waitStatus != Node.CONDITION) {
unlinkCancelledWaiters();
t = lastWaiter;
}
Node node = new Node(Thread.currentThread(), Node.CONDITION);
if (t == null)
firstWaiter = node;
else
t.nextWaiter = node;
lastWaiter = node;
return node;
}AQS的方法。getState()方法获取的就是AQS里面的state变量，在ReentrantLock中，其实state保存的是重入的次数（参考ReentrantLock）。
final int fullyRelease(Node node) {
boolean failed = true;
try {
int savedState = getState();
if (release(savedState)) {
failed = false;
return savedState;
} else {
throw new IllegalMonitorStateException();
}
} finally {
if (failed)
node.waitStatus = Node.CANCELLED;
}
}ReentrantLock.Sync.tryRelease的实现如下，可以看到不管重入了多少次都会一次性释放。
protected final boolean tryRelease(int releases) {
int c = getState() - releases;
if (Thread.currentThread() != getExclusiveOwnerThread())
throw new IllegalMonitorStateException();
boolean free = false;
if (c == 0) {
free = true;
setExclusiveOwnerThread(null);
}
setState(c);
return free;
}fullyRelease返回之前的重入次数，后续会用到。
await 释放锁后进入阻塞等待状态，阻塞的条件是该节点没有在SyncQueue上：
final boolean isOnSyncQueue(Node node) {
if (node.waitStatus == Node.CONDITION || node.prev == null)
return false;
if (node.next != null) // If has successor, it must be on queue
return true;
/*
* node.prev can be non-null, but not yet on queue because
* the CAS to place it on queue can fail. So we have to
* traverse from tail to make sure it actually made it. It
* will always be near the tail in calls to this method, and
* unless the CAS failed (which is unlikely), it will be
* there, so we hardly ever traverse much.
*/
return findNodeFromTail(node);
}
``
signal的时候该方法会返回true。
### 重获锁
条件满足后，需要重新获取锁，acquireQueued会调到ReentrantLock.tryAcquire，此处可以看到保存前面`savedState`的作用。
### signal
唤醒就是把等待队列中的第一个节点转移到同步队列。
```java
public final void signal() {
// 先判断当前线程是否获取了锁，否则异常
if (!isHeldExclusively())
throw new IllegalMonitorStateException();
Node first = firstWaiter;
if (first != null)
doSignal(first);
}
// 摘除头节点，把头节点移到同步队列
private void doSignal(Node first) {
do {
if ( (firstWaiter = first.nextWaiter) == null)
lastWaiter = null;
first.nextWaiter = null;
} while (!transferForSignal(first) &&
(first = firstWaiter) != null);
}
final boolean transferForSignal(Node node) {
// CAS 将状态设置为0,0是一个无效的状态
if (!compareAndSetWaitStatus(node, Node.CONDITION, 0))
return false;
/*
* Splice onto queue and try to set waitStatus of predecessor to
* indicate that thread is (probably) waiting. If cancelled or
* attempt to set waitStatus fails, wake up to resync (in which
* case the waitStatus can be transiently and harmlessly wrong).
*/
Node p = enq(node);
int ws = p.waitStatus;
// 唤醒线程
if (ws > 0 || !compareAndSetWaitStatus(p, ws, Node.SIGNAL))
LockSupport.unpark(node.thread);
return true;
}
// 这个方法是AQS中的，node进入同步队列
private Node enq(final Node node) {
for (;;) {
Node t = tail;
if (t == null) { // Must initialize
if (compareAndSetHead(new Node()))
tail = head;
} else {
node.prev = t;
if (compareAndSetTail(t, node)) {
t.next = node;
return t;
}
}
}
}转移所有的等待节点。
private void doSignalAll(Node first) {
lastWaiter = firstWaiter = null;
do {
Node next = first.nextWaiter;
first.nextWaiter = null;
transferForSignal(first);
first = next;
} while (first != null);
}了解Linux环境编程的会想到其中也有条件变量的机制来实现线程之间的同步，和Java中的基本上语义是相同的，在等待条件的时候都会原子的释放锁。
