在默认大多数情况下,AcitveMQ 是以异步模式发送消息。例外的情况:在没有使用
事务的情况下,生产者以PERSISTENT 传送模式发送消息。在这种情况下,send 方法都
是同步的,并且一直阻塞直到ActiveMQ 发回确认消息:消息已经存储在持久性数据存
储中。这种确认机制保证消息不会丢失,但会造成生产者阻塞从而影响反应时间。
高性能的程序一般都能容忍在故障情况下丢失少量数据。如果编写这样的程序,可
以通过使用异步发送来提高吞吐量(甚至在使用PERSISTENT 传送模式的情况下)。
protected void send(ActiveMQMessageProducer producer, ActiveMQDestination destination, Message message, int deliveryMode, int priority, long timeToLive,
MemoryUsage producerWindow, int sendTimeout, AsyncCallback onComplete) throws JMSException {
checkClosed();
if (destination.isTemporary() && connection.isDeleted(destination)) {
throw new InvalidDestinationException("Cannot publish to a deleted Destination: " + destination);
}
synchronized (sendMutex) {
// tell the Broker we are about to start a new transaction
doStartTransaction();
TransactionId txid = transactionContext.getTransactionId();
long sequenceNumber = producer.getMessageSequence();
//Set the "JMS" header fields on the original message, see 1.1 spec section 3.4.11
message.setJMSDeliveryMode(deliveryMode);
long expiration = 0L;
if (!producer.getDisableMessageTimestamp()) {
long timeStamp = System.currentTimeMillis();
message.setJMSTimestamp(timeStamp);
if (timeToLive > 0) {
expiration = timeToLive + timeStamp;
}
}
message.setJMSExpiration(expiration);
message.setJMSPriority(priority);
message.setJMSRedelivered(false);
// transform to our own message format here
ActiveMQMessage msg = ActiveMQMessageTransformation.transformMessage(message, connection);
msg.setDestination(destination);
msg.setMessageId(new MessageId(producer.getProducerInfo().getProducerId(), sequenceNumber));
// Set the message id.
if (msg != message) {
message.setJMSMessageID(msg.getMessageId().toString());
// Make sure the JMS destination is set on the foreign messages too.
message.setJMSDestination(destination);
}
//clear the brokerPath in case we are re-sending this message
msg.setBrokerPath(null);
msg.setTransactionId(txid);
if (connection.isCopyMessageOnSend()) {
msg = (ActiveMQMessage)msg.copy();
}
msg.setConnection(connection);
msg.onSend();
msg.setProducerId(msg.getMessageId().getProducerId());
if (LOG.isTraceEnabled()) {
LOG.trace(getSessionId() + " sending message: " + msg);
}
// 请看下面这一行就是判断是同步发送还是异步发送的。
if (onComplete==null && sendTimeout <= 0 && !msg.isResponseRequired() && !connection.isAlwaysSyncSend() && (!msg.isPersistent() || connection.isUseAsyncSend() || txid != null)) {
this.connection.asyncSendPacket(msg);
if (producerWindow != null) {
// Since we defer lots of the marshaling till we hit the
// wire, this might not
// provide and accurate size. We may change over to doing
// more aggressive marshaling,
// to get more accurate sizes.. this is more important once
// users start using producer window
// flow control.
int size = msg.getSize();
producerWindow.increaseUsage(size);
}
} else {
if (sendTimeout > 0 && onComplete==null) {
this.connection.syncSendPacket(msg,sendTimeout);
}else {
this.connection.syncSendPacket(msg, onComplete);
}
}
}
}
接下来看看同步发送方法。
public Object request(Object command) throws IOException {
FutureResponse response = asyncRequest(command, null); // 调用发送方法
return response.getResult(); // 从future方法阻塞等待返回
}
看下asyncRequest方法。构建了一个FutureResponse对象。并且将其存到了
requestMap.put(new Integer(command.getCommandId()), future);这个map当中。
等broker有返回的时候,从requestMap里面取出来这个future.
public FutureResponse asyncRequest(Object o, ResponseCallback responseCallback) throws IOException {
Command command = (Command) o;
command.setCommandId(sequenceGenerator.getNextSequenceId());
command.setResponseRequired(true);
FutureResponse future = new FutureResponse(responseCallback, this);
IOException priorError = null;
synchronized (requestMap) {
priorError = this.error;
if (priorError == null) {
requestMap.put(new Integer(command.getCommandId()), future);
}
}
if (priorError != null) {
future.set(new ExceptionResponse(priorError));
throw priorError;
}
next.oneway(command);
return future;
}
看下FutureResponse里面的这个回调方法。
public void set(Response result) {
if (responseSlot.offer(result)) {
if (responseCallback != null) {
responseCallback.onCompletion(this);
}
}
}
其中responseSlot是个阻塞队列 private final ArrayBlockingQueue responseSlot = new ArrayBlockingQueue(1);
。复习下阻塞队列的知识。
使用BlockingQueue的关键技术点如下:
1.BlockingQueue定义的常用方法如下:
1)add(anObject):把anObject加到BlockingQueue里,即如果BlockingQueue可以容纳,则返回true,否则报异常
2)offer(anObject):表示如果可能的话,将anObject加到BlockingQueue里,即如果BlockingQueue可以容纳,则返回true,否则返回false.
3)put(anObject):把anObject加到BlockingQueue里,如果BlockQueue没有空间,则调用此方法的线程被阻断直到BlockingQueue里面有空间再继续.
4)poll(time):取走BlockingQueue里排在首位的对象,若不能立即取出,则可以等time参数规定的时间,取不到时返回null
5)take():取走BlockingQueue里排在首位的对象,若BlockingQueue为空,阻断进入等待状态直到Blocking有新的对象被加入为止
2.BlockingQueue有四个具体的实现类,根据不同需求,选择不同的实现类
1)ArrayBlockingQueue:规定大小的BlockingQueue,其构造函数必须带一个int参数来指明其大小.其所含的对象是以FIFO(先入先出)顺序排序的.
2)LinkedBlockingQueue:大小不定的BlockingQueue,若其构造函数带一个规定大小的参数,生成的BlockingQueue有大小限制,若不带大小参数,所生成的BlockingQueue的大小由Integer.MAX_VALUE来决定.其所含的对象是以FIFO(先入先出)顺序排序的
3)PriorityBlockingQueue:类似于LinkedBlockQueue,但其所含对象的排序不是FIFO,而是依据对象的自然排序顺序或者是构造函数的Comparator决定的顺序.
4)SynchronousQueue:特殊的BlockingQueue,对其的操作必须是放和取交替完成的.
3.LinkedBlockingQueue和ArrayBlockingQueue比较起来,它们背后所用的数据结构不一样,导致LinkedBlockingQueue的数据吞吐量要大于ArrayBlockingQueue,但在线程数量很大时其性能的可预见性低于ArrayBlockingQueue.