从RocketMQ看长轮询(Long Polling)

前言

消息队列一般在消费端都会提供push和pull两种模式,RocketMQ同样实现了这两种模式,分别提供了两个实现类:DefaultMQPushConsumer和DefaultMQPullConsumer;两种方式各有优势:
push模式:推送模式,即服务端有数据之后立马推送消息给客户端,需要客户端和服务器建立长连接,实时性很高,对客户端来说也简单,接收处理消息即可;缺点就是服务端不知道客户端处理消息的能力,可能会导致数据积压,同时也增加了服务端的工作量,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,然后处理数据,再拉取数据,一直循环下去,具体拉取数据的时间间隔不好设定,太短可能会导致大量的连接拉取不到数据,太长导致数据接收不及时;
RocketMQ使用了长轮询的方式,兼顾了push和pull两种模式的优点,下面首先对长轮询做简单介绍,进而分析RocketMQ内置的长轮询模式。

长轮询

长轮询通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做了优化处理,服务端在没有数据的时候并不是马上返回数据,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,然后一直循环下去;下面看一下如何简单实现一个长轮询;

1.实现步骤

1.1客户端轮询发送请求

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;

1.2服务端处理数据

服务器接收到客户端请求之后,首先查看是否有数据,如果有数据则直接返回,如果没有则保持连接,等待获取数据,服务端获取数据之后,会通知之前的请求连接来获取数据,然后返回给客户端;

1.3客户端接收数据

正常情况下,客户端会马上接收到服务端的数据,或者等待一段时间获取到数据;如果一直获取不到数据,会有超时处理;在获取数据或者超时处理之后会关闭连接,然后再次发起长轮询请求;

2.实现实例

以下使用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;

服务端代码

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,直接使用即可,启动端口为8080;同时启动数据中心服务,相关代码如下:

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,需要等待的情况,这里使用BlockingQueue来模拟,不定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,如下:

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之后,从数据中心获取一条消息,如果没有数据,会进行等待,直到有数据为止;然后使用FullHttpResponse返回给客户端;客户端使用HttpURLConnection来和服务端建立连接,不停的拉取数据,代码如下:

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长轮询

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,所以下面重点分析此类;

1.PullMessage服务

从名字可以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");
    }

服务启动之后,会一直不停的循环调用拉取数据,PullRequest可以看作是拉取数据需要的参数,部分代码如下:

public class PullRequest {
    private String consumerGroup;
    private MessageQueue messageQueue;
    private ProcessQueue processQueue;
    private long nextOffset;
    private boolean lockedFirst = false;
    ...省略...
}

每个MessageQueue 对应了封装成了一个PullRequest,因为拉取数据是以每个Broker下面的Queue为单位,同时里面还一个ProcessQueue,每个MessageQueue也同样对应一个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,作用是设置Broker的最长阻塞时间,默认为15秒,前提是没有消息的情况下,有消息会立刻返回;

2.PullMessageProcessor服务

从名字可以看出,服务端用来处理pullMessage的服务,下面重点看一下processRequest方法,其中包括对获取不同结果做的处理:

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,我们关心的是在没有获取到数据的情况下是如何处理的,可以重点看一下ResponseCode.PULL_NOT_FOUND,表示没有拉取到数据,此时会调用PullRequestHoldService服务,从名字可以看出此服务用来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());
    }

此方法主要就是通过不停的检查被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);
    }

将需要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,然后用来和当前的offset来比较,来确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);
                }
            }
        }
    }

方法中两个重要的判定就是: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;另外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,超过也同样返回;
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。

3.PullCallback回调

服务端处理完之后,给客户端响应,回调其中的PullCallback,其中在处理完消息之后,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;

总结

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,然后引出了长轮询,并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。

示例代码地址

Github
Gitee

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