消息队列通常在消费端都会提供push和pull两种模式,RocketMQ一样实现了这两种模式,分别提供了两个实现类:DefaultMQPushConsumer和DefaultMQPullConsumer;两种方式各有优点:
push模式:推送模式,即服务端有数据以后立马推送消息给客户端,须要客户端和服务器创建长链接,实时性很高,对客户端来讲也简单,接收处理消息便可;缺点就是服务端不知道客户端处理消息的能力,可能会致使数据积压,同时也增长了服务端的工做量,影响服务端的性能;
pull模式:拉取模式,即客户端主动去服务端拉取数据,主动权在客户端,拉取数据,而后处理数据,再拉取数据,一直循环下去,具体拉取数据的时间间隔很差设定,过短可能会致使大量的链接拉取不到数据,太长致使数据接收不及时;
RocketMQ使用了长轮询的方式,兼顾了push和pull两种模式的优势,下面首先对长轮询作简单介绍,进而分析RocketMQ内置的长轮询模式。git
长轮询经过客户端和服务端的配合,达到主动权在客户端,同时也能保证数据的实时性;长轮询本质上也是轮询,只不过对普通的轮询作了优化处理,服务端在没有数据的时候并非立刻返回数据,会hold住请求,等待服务端有数据,或者一直没有数据超时处理,而后一直循环下去;下面看一下如何简单实现一个长轮询;github
客户端应该存在一个一直循环的程序,不停的向服务端发送获取消息请求;express
服务器接收到客户端请求以后,首先查看是否有数据,若是有数据则直接返回,若是没有则保持链接,等待获取数据,服务端获取数据以后,会通知以前的请求链接来获取数据,而后返回给客户端;服务器
正常状况下,客户端会立刻接收到服务端的数据,或者等待一段时间获取到数据;若是一直获取不到数据,会有超时处理;在获取数据或者超时处理以后会关闭链接,而后再次发起长轮询请求;app
如下使用netty模拟一个http服务器,使用HttpURLConnection模拟客户端发送请求,使用BlockingQueue存放数据;dom
服务端代码ide
public class Server { public static void start(final int port) throws Exception { EventLoopGroup boss = new NioEventLoopGroup(); EventLoopGroup woker = new NioEventLoopGroup(); ServerBootstrap serverBootstrap = new ServerBootstrap(); try { serverBootstrap.channel(NioServerSocketChannel.class).group(boss, woker) .childOption(ChannelOption.SO_KEEPALIVE, true).option(ChannelOption.SO_BACKLOG, 1024) .childHandler(new ChannelInitializer<SocketChannel>() { @Override protected void initChannel(SocketChannel ch) throws Exception { ch.pipeline().addLast("http-decoder", new HttpServerCodec()); ch.pipeline().addLast(new HttpServerHandler()); } }); ChannelFuture future = serverBootstrap.bind(port).sync(); System.out.println("server start ok port is " + port); DataCenter.start(); future.channel().closeFuture().sync(); } finally { boss.shutdownGracefully(); woker.shutdownGracefully(); } } public static void main(String[] args) throws Exception { start(8080); } }
netty默认支持http协议,直接使用便可,启动端口为8080;同时启动数据中心服务,相关代码以下:oop
public class DataCenter { private static Random random = new Random(); private static BlockingQueue<String> queue = new LinkedBlockingQueue<>(); private static AtomicInteger num = new AtomicInteger(); public static void start() { while (true) { try { Thread.sleep(random.nextInt(5) * 1000); String data = "hello world" + num.incrementAndGet(); queue.put(data); System.out.println("store data:" + data); } catch (InterruptedException e) { e.printStackTrace(); } } } public static String getData() throws InterruptedException { return queue.take(); } }
为了模拟服务端没有数据,须要等待的状况,这里使用BlockingQueue来模拟,不按期的往队列里面插入数据,同时对外提供获取数据的方法,使用的是take方法,没有数据会阻塞知道有数据为止;getData在类HttpServerHandler中使用,此类也很简单,以下:性能
public class HttpServerHandler extends ChannelInboundHandlerAdapter { public void channelRead(ChannelHandlerContext ctx, Object msg) throws Exception { if (msg instanceof HttpRequest) { FullHttpResponse httpResponse = new DefaultFullHttpResponse(HttpVersion.HTTP_1_1, HttpResponseStatus.OK); httpResponse.content().writeBytes(DataCenter.getData().getBytes()); httpResponse.headers().set(HttpHeaders.Names.CONTENT_TYPE, "text/plain; charset=UTF-8"); httpResponse.headers().set(HttpHeaders.Names.CONTENT_LENGTH, httpResponse.content().readableBytes()); ctx.writeAndFlush(httpResponse); } } }
获取到客户端的请求以后,从数据中心获取一条消息,若是没有数据,会进行等待,直到有数据为止;而后使用FullHttpResponse返回给客户端;客户端使用HttpURLConnection来和服务端创建链接,不停的拉取数据,代码以下:优化
public class Client { public static void main(String[] args) { while (true) { HttpURLConnection connection = null; try { URL url = new URL("http://localhost:8080"); connection = (HttpURLConnection) url.openConnection(); connection.setReadTimeout(10000); connection.setConnectTimeout(3000); connection.setRequestMethod("GET"); connection.connect(); if (200 == connection.getResponseCode()) { BufferedReader reader = null; try { reader = new BufferedReader(new InputStreamReader(connection.getInputStream(), "UTF-8")); StringBuffer result = new StringBuffer(); String line = null; while ((line = reader.readLine()) != null) { result.append(line); } System.out.println("时间:" + new Date().toString() + "result = " + result); } finally { if (reader != null) { reader.close(); } } } } catch (IOException e) { e.printStackTrace(); } finally { if (connection != null) { connection.disconnect(); } } } } }
以上只是简单的模拟了长轮询的方式,下面重点来看看RocketMQ是如何实现长轮询的;
RocketMQ的消费端提供了两种消费模式分别是:DefaultMQPushConsumer和DefaultMQPullConsumer,其中DefaultMQPushConsumer就是使用的长轮询,因此下面重点分析此类;
从名字能够看出来就是客户端从服务端拉取数据的服务,看里面的一个核心方法:
@Override public void run() { log.info(this.getServiceName() + " service started"); while (!this.isStopped()) { try { PullRequest pullRequest = this.pullRequestQueue.take(); this.pullMessage(pullRequest); } catch (InterruptedException ignored) { } catch (Exception e) { log.error("Pull Message Service Run Method exception", e); } } log.info(this.getServiceName() + " service end"); }
服务启动以后,会一直不停的循环调用拉取数据,PullRequest能够看做是拉取数据须要的参数,部分代码以下:
public class PullRequest { private String consumerGroup; private MessageQueue messageQueue; private ProcessQueue processQueue; private long nextOffset; private boolean lockedFirst = false; ...省略... }
每一个MessageQueue 对应了封装成了一个PullRequest,由于拉取数据是以每一个Broker下面的Queue为单位,同时里面还一个ProcessQueue,每一个MessageQueue也一样对应一个ProcessQueue,保存了这个MessageQueue消息处理状态的快照;还有nextOffset用来标识读取的位置;继续看一段pullMessage中的内容,给服务端发送请求的头内容:
PullMessageRequestHeader requestHeader = new PullMessageRequestHeader(); requestHeader.setConsumerGroup(this.consumerGroup); requestHeader.setTopic(mq.getTopic()); requestHeader.setQueueId(mq.getQueueId()); requestHeader.setQueueOffset(offset); requestHeader.setMaxMsgNums(maxNums); requestHeader.setSysFlag(sysFlagInner); requestHeader.setCommitOffset(commitOffset); requestHeader.setSuspendTimeoutMillis(brokerSuspendMaxTimeMillis); requestHeader.setSubscription(subExpression); requestHeader.setSubVersion(subVersion); requestHeader.setExpressionType(expressionType); String brokerAddr = findBrokerResult.getBrokerAddr(); if (PullSysFlag.hasClassFilterFlag(sysFlagInner)) { brokerAddr = computPullFromWhichFilterServer(mq.getTopic(), brokerAddr); } PullResult pullResult = this.mQClientFactory.getMQClientAPIImpl().pullMessage( brokerAddr, requestHeader, timeoutMillis, communicationMode, pullCallback); return pullResult;
其中有一个参数是SuspendTimeoutMillis,做用是设置Broker的最长阻塞时间,默认为15秒,前提是没有消息的状况下,有消息会马上返回;
从名字能够看出,服务端用来处理pullMessage的服务,下面重点看一下processRequest方法,其中包括对获取不一样结果作的处理:
switch (response.getCode()) { case ResponseCode.SUCCESS: ...省略... break; case ResponseCode.PULL_NOT_FOUND: if (brokerAllowSuspend && hasSuspendFlag) { long pollingTimeMills = suspendTimeoutMillisLong; if (!this.brokerController.getBrokerConfig().isLongPollingEnable()) { pollingTimeMills = this.brokerController.getBrokerConfig().getShortPollingTimeMills(); } String topic = requestHeader.getTopic(); long offset = requestHeader.getQueueOffset(); int queueId = requestHeader.getQueueId(); PullRequest pullRequest = new PullRequest(request, channel, pollingTimeMills, this.brokerController.getMessageStore().now(), offset, subscriptionData); this.brokerController.getPullRequestHoldService().suspendPullRequest(topic, queueId, pullRequest); response = null; break; } case ResponseCode.PULL_RETRY_IMMEDIATELY: break; case ResponseCode.PULL_OFFSET_MOVED: ...省略... break; default: assert false;
一共处理了四个类型,咱们关心的是在没有获取到数据的状况下是如何处理的,能够重点看一下ResponseCode.PULL_NOT_FOUND,表示没有拉取到数据,此时会调用PullRequestHoldService服务,从名字能够看出此服务用来hold住请求,不会立马返回,response被至为了null,不给客户端响应;下面重点看一下PullRequestHoldService:
@Override public void run() { log.info("{} service started", this.getServiceName()); while (!this.isStopped()) { try { if (this.brokerController.getBrokerConfig().isLongPollingEnable()) { this.waitForRunning(5 * 1000); } else { this.waitForRunning(this.brokerController.getBrokerConfig().getShortPollingTimeMills()); } long beginLockTimestamp = this.systemClock.now(); this.checkHoldRequest(); long costTime = this.systemClock.now() - beginLockTimestamp; if (costTime > 5 * 1000) { log.info("[NOTIFYME] check hold request cost {} ms.", costTime); } } catch (Throwable e) { log.warn(this.getServiceName() + " service has exception. ", e); } } log.info("{} service end", this.getServiceName()); }
此方法主要就是经过不停的检查被hold住的请求,检查是否已经有数据了,具体检查哪些就是在ResponseCode.PULL_NOT_FOUND中调用的suspendPullRequest方法:
private ConcurrentHashMap<String/* topic@queueId */, ManyPullRequest> pullRequestTable = new ConcurrentHashMap<String, ManyPullRequest>(1024); public void suspendPullRequest(final String topic, final int queueId, final PullRequest pullRequest) { String key = this.buildKey(topic, queueId); ManyPullRequest mpr = this.pullRequestTable.get(key); if (null == mpr) { mpr = new ManyPullRequest(); ManyPullRequest prev = this.pullRequestTable.putIfAbsent(key, mpr); if (prev != null) { mpr = prev; } } mpr.addPullRequest(pullRequest); }
将须要hold处理的PullRequest放入到一个ConcurrentHashMap中,等待被检查;具体的检查代码在checkHoldRequest中:
private void checkHoldRequest() { for (String key : this.pullRequestTable.keySet()) { String[] kArray = key.split(TOPIC_QUEUEID_SEPARATOR); if (2 == kArray.length) { String topic = kArray[0]; int queueId = Integer.parseInt(kArray[1]); final long offset = this.brokerController.getMessageStore().getMaxOffsetInQuque(topic, queueId); try { this.notifyMessageArriving(topic, queueId, offset); } catch (Throwable e) { log.error("check hold request failed. topic={}, queueId={}", topic, queueId, e); } } } }
此方法用来获取指定messageQueue下最大的offset,而后用来和当前的offset来比较,来肯定是否有新的消息到来;往下看notifyMessageArriving方法:
public void notifyMessageArriving(final String topic, final int queueId, final long maxOffset, final Long tagsCode) { String key = this.buildKey(topic, queueId); ManyPullRequest mpr = this.pullRequestTable.get(key); if (mpr != null) { List<PullRequest> requestList = mpr.cloneListAndClear(); if (requestList != null) { List<PullRequest> replayList = new ArrayList<PullRequest>(); for (PullRequest request : requestList) { long newestOffset = maxOffset; if (newestOffset <= request.getPullFromThisOffset()) { newestOffset = this.brokerController.getMessageStore().getMaxOffsetInQuque(topic, queueId); } if (newestOffset > request.getPullFromThisOffset()) { if (this.messageFilter.isMessageMatched(request.getSubscriptionData(), tagsCode)) { try { this.brokerController.getPullMessageProcessor().executeRequestWhenWakeup(request.getClientChannel(), request.getRequestCommand()); } catch (Throwable e) { log.error("execute request when wakeup failed.", e); } continue; } } if (System.currentTimeMillis() >= (request.getSuspendTimestamp() + request.getTimeoutMillis())) { try { this.brokerController.getPullMessageProcessor().executeRequestWhenWakeup(request.getClientChannel(), request.getRequestCommand()); } catch (Throwable e) { log.error("execute request when wakeup failed.", e); } continue; } replayList.add(request); } if (!replayList.isEmpty()) { mpr.addPullRequest(replayList); } } } }
方法中两个重要的断定就是:比较当前的offset和maxoffset,看是否有新的消息到来,有新的消息返回客户端;另一个就是比较当前的时间和阻塞的时间,看是否超过了最大的阻塞时间,超过也一样返回;
此方法不光在PullRequestHoldService服务类中循环调用检查,同时在DefaultMessageStore中消息被存储的时候调用;其实就是主动检查和被动通知两种方式。
服务端处理完以后,给客户端响应,回调其中的PullCallback,其中在处理完消息以后,重要的一步就是再次把pullRequest放到PullMessageService服务中,等待下一次的轮询;
本文首先介绍了两种消费消息的模式,介绍了其中的优缺点,而后引出了长轮询,而且在本地简单模拟了长轮询,最后重点介绍了RocketMQ中是如何实现的长轮询。