java rabbitmq 监听队列消息 rabbitmq监听不到消息

业务场景

用户触发某种行为动作，根据行为类型，分别执行延迟30s处理数据动作，和立即处理数据重做两种业务

思路

方案一：Redis key监听器，但是考虑实际key数量，放弃该方式
方案二：方案RabbitMQ延迟队列实现，程序同时监听两种队列即可，简单方便

踩坑记录

因为不熟悉RabbitMQ相关配置，导致很多奇奇怪怪的问题，特此记录

消费者篇

一、需要手动确认ACK + 动态设置消费者上限

理由：

1. 手动ACK是为了确保消息处理完毕，但是！消息处理性能一定要跟上，否则就需要做幂等控制
2. 动态设置消费者上限：是因为机器配置不一样，设置过大，可能导致低配的机器负载离谱

application.yml 如下

spring:
  # rabbitmq相关配置
  rabbitmq:
    # 链接超时时间
    connection-timeout: 1000
    cache:
      channel:
        # 要保留在高速缓存中的通道数
        size: 200
        # 如果已达到高速缓存大小，则等待获取通道的持续时间。如果为0，则始终创建一个新通道。
        checkout-timeout: 500
      connection:
        mode: channel
    publisher-returns: true
    publisher-confirm-type: simple

配置类如下

import com.alibaba.fastjson.JSON;
import lombok.extern.slf4j.Slf4j;
import org.springframework.amqp.core.AcknowledgeMode;
import org.springframework.amqp.core.Message;
import org.springframework.amqp.rabbit.config.SimpleRabbitListenerContainerFactory;
import org.springframework.amqp.rabbit.connection.ConnectionFactory;
import org.springframework.amqp.rabbit.core.RabbitTemplate;
import org.springframework.amqp.rabbit.listener.api.RabbitListenerErrorHandler;
import org.springframework.amqp.support.converter.Jackson2JsonMessageConverter;
import org.springframework.amqp.support.converter.MessageConverter;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

import java.util.Objects;



@Configuration
public class RabbitMqConfig {
    @Bean
    public SimpleRabbitListenerContainerFactory rabbitListenerContainerFactory(ConnectionFactory connectionFactory,
                                                                               MessageConverter messageConverter) {
        SimpleRabbitListenerContainerFactory factory = new SimpleRabbitListenerContainerFactory();
        factory.setConnectionFactory(connectionFactory);
        factory.setMessageConverter(messageConverter);
        factory.setAcknowledgeMode(AcknowledgeMode.MANUAL);
        // 根据CPU数量，动态调整消费者最大值
        int i = Runtime.getRuntime().availableProcessors();
        factory.setMaxConcurrentConsumers(i * 5);
        return factory;
    }

    @Bean
    public MessageConverter jsonMessageConverter() {
        return new Jackson2JsonMessageConverter();
    }
}

二、同时监听多个队列

消费者代码如下

import com.alibaba.fastjson.JSONObject;
import com.qlm.yfb.util.log.LogUtils;
import com.rabbitmq.client.Channel;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.amqp.rabbit.annotation.Exchange;
import org.springframework.amqp.rabbit.annotation.Queue;
import org.springframework.amqp.rabbit.annotation.QueueBinding;
import org.springframework.amqp.rabbit.annotation.RabbitListener;
import org.springframework.amqp.support.AmqpHeaders;
import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
import org.springframework.context.annotation.Configuration;
import org.springframework.messaging.handler.annotation.Header;

import javax.annotation.PostConstruct;
import java.io.IOException;

/**
 * @author chunyang.leng
 * @date 2022-06-17 9:52 PM
 */
@Configuration
public class WechatDeadLetterConsumer {

    private static final Logger logger = LoggerFactory.getLogger(WechatDeadLetterConsumer.class);

    @PostConstruct
    private void postConstruct(){
        LogUtils.info(logger,"启动 ========> 微信延迟队列消费者");
    }

    @RabbitListener(
            autoStartup = "true",
            bindings = {
                    @QueueBinding(
                        value = @Queue(name = "subscribeDelayQueue"),
                        exchange = @Exchange(name = "deadLetterExchange"),
                        key = {"subscribeDelayQueueRoutingKey"}
                    ),
                    @QueueBinding(
                            value = @Queue(name = "clickMenuQueue"),
                            exchange = @Exchange(name = "wechatPushExchange"),
                            key = {"clickMenuQueueRoutingKey"}
                    )
            }
    )
    // 幂等检查注解
    @IdempotenceCheck(redisKeyPrefix = "delay:strategy:")
    public void enterpriseWechatDeadLetterHandler(EnterpriseWechatDelayDTO enterpriseWechatDelayDTO, Channel channel, @Header(AmqpHeaders.DELIVERY_TAG) long tag){
        LogUtils.debug(logger,"消费到EnterpriseWechat死信队列数据:{}", JSONObject.toJSONString(enterpriseWechatDelayDTO));
        try {
            // todo 处理业务
      
        } catch (Exception e) {
            logger.error("rabbitmq 消费信息出现异常", e);
        } finally {
            try {
                channel.basicAck(tag, false);
            } catch (IOException e) {
                logger.error("rabbitmq ack出现异常", e);
            }
        }
    }
}

生产者篇

因生产者和消费者框架不同，配置方式不太一样，生产者为Spring MVC

配置类

import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Recoverable;
import com.rabbitmq.client.RecoveryListener;
import com.rabbitmq.client.ShutdownSignalException;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.amqp.core.AcknowledgeMode;
import org.springframework.amqp.core.AmqpTemplate;
import org.springframework.amqp.rabbit.config.SimpleRabbitListenerContainerFactory;
import org.springframework.amqp.rabbit.connection.*;
import org.springframework.amqp.rabbit.core.RabbitTemplate;
import org.springframework.amqp.rabbit.listener.ConditionalRejectingErrorHandler;
import org.springframework.amqp.rabbit.listener.RabbitListenerContainerFactory;
import org.springframework.amqp.rabbit.listener.api.RabbitListenerErrorHandler;
import org.springframework.amqp.support.converter.Jackson2JsonMessageConverter;
import org.springframework.amqp.support.converter.MessageConverter;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.retry.policy.SimpleRetryPolicy;
import org.springframework.retry.support.RetryTemplate;

/**
 * @author chunyang.leng
 * @date 2021-04-13 9:32 上午
 */
@Configuration
@PropertySource("classpath:rabbit-push.properties")
public class RabbitMqConfig {
    private static final Logger logger = LoggerFactory.getLogger(RabbitMqConfig.class);

    @Value("${rabbit.push.address:192.168.1.2}")
    private String rabbitPushAddress;
    @Value("${rabbit.push.username:xxx}")
    private String rabbitPushUsername ;
    @Value("${rabbit.push.password:xxxxxx}")
    private String rabbitPushPassword;
    @Value("${rabbit.consumesize:10}")
    private Integer consumesize;


    @Bean
    public ConnectionFactory wechatPushConnectionFactory(ConnectionListener wechatPushConnectionListener,
                                                         RecoveryListener wechatPushRecoveryListener,
                                                         ChannelListener wechatPushChannelListener) {
        CachingConnectionFactory connectionFactory = new CachingConnectionFactory();
        connectionFactory.setAddresses(rabbitPushAddress);
        connectionFactory.setUsername(rabbitPushUsername);
        connectionFactory.setPassword(rabbitPushPassword);
        connectionFactory.setVirtualHost("/");
        connectionFactory.setCacheMode(CachingConnectionFactory.CacheMode.CHANNEL);
		// 坑一，正确值应该设置大一些，比如200
        connectionFactory.setChannelCacheSize(5);
        // 坑二，正确值应该设置大一些，比如2000，单位毫秒
        connectionFactory.setChannelCheckoutTimeout(0);
        connectionFactory.setPublisherReturns(true);
        connectionFactory.setPublisherConfirmType(CachingConnectionFactory.ConfirmType.SIMPLE);
        connectionFactory.addConnectionListener(wechatPushConnectionListener);
        connectionFactory.addChannelListener(wechatPushChannelListener);
        connectionFactory.setRecoveryListener(wechatPushRecoveryListener);
        connectionFactory.getRabbitConnectionFactory().setRequestedChannelMax(500);
        return connectionFactory;

    }

    @Bean
    public RabbitListenerContainerFactory yfbPushListenerContainerFactory(ConnectionFactory wechatPushConnectionFactory,
                                                                          MessageConverter jsonMessageConverter) {
        SimpleRabbitListenerContainerFactory factory = new SimpleRabbitListenerContainerFactory();
        factory.setConnectionFactory(wechatPushConnectionFactory);
        factory.setMessageConverter(jsonMessageConverter);
        factory.setAcknowledgeMode(AcknowledgeMode.MANUAL);
        factory.setConcurrentConsumers(consumesize);
        factory.setMaxConcurrentConsumers(consumesize);
        factory.setPrefetchCount(1000);
        factory.setChannelTransacted(false);
        factory.setDefaultRequeueRejected(false);
        factory.setErrorHandler(new ConditionalRejectingErrorHandler());
        return factory;
    }

    @Bean
    public MessageConverter jsonMessageConverter() {
        return new Jackson2JsonMessageConverter();
    }
}

业务触发入口

import lombok.extern.slf4j.Slf4j;
import org.apache.commons.lang3.StringUtils;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;
import org.springframework.stereotype.Service;

import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;
import java.util.Map;


/**
 * 类名: MessageEventService </br>
 * 描述: 核心服务类 </br>
 */

@Slf4j
@RestController
public class MessageEvent {

    @Autowired
    private SubscribeEventListener subscribeEventListener;
    @Autowired
    private ClickMenuMessageEventListener clickMenuMessageEventListener;

    /**
     * 处理微信发来的请求
     * @param request
     * @return xml
     */
    @PostMapping("handle")
    public String processRequest(HttpServletRequest request, HttpServletResponse response) {          
	       // todo 用户关注事件
	     subscribeEventListener.onApplicationEvent(new SubscribeEvent(openid));
	                  
	      // todo 用户点击菜单事件
	     clickMenuMessageEventListener.onApplicationEvent(new ClickMenuEvent(openid));
      }              
}

Listener 超级大坑

import org.springframework.amqp.rabbit.core.RabbitTemplate;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.context.ApplicationListener;
import org.springframework.stereotype.Component;

/**
 *
 *
 * @author chunyang.leng
 * @date 2022-06-20 1:19 PM
 */
@Component
public class ClickMenuMessageEventListener implements ApplicationListener<ClickMenuEvent> {

    @Autowired
    private RabbitTemplate rabbitTemplate;

    @Override
    public void onApplicationEvent(ClickMenuEvent event) {
   
        String openId = event.getOpenId();

        EnterpriseWechatDelayDTO dto = new EnterpriseWechatDelayDTO();
        dto.setOpenId(openId);
        dto.setSource(EnterpriseWechatSource.CLICK_MENU_EVENT);
        dto.setDelayStrategy(DelayStrategyEnum.ENTERPRISE_WECHAT_CUSTOMER_SERVICE_PUSH);
        // 发送到mq，直接消费，不做延迟处理
        rabbitTemplate.convertAndSend("wechatPushExchange","clickMenuQueueRoutingKey",dto);
    }
}

生产者踩坑详解

以上代码上线之后，出现服务器内存增加，连接数暴增等现象

连接数异常

内存增长

问题分析过程

1. 检查上线代码：查看是否存在链接泄漏等情况（无）
2. 转储内存镜像（jmap命令）
3. 转储线程运行情况（jstack命令）

分析内存镜像，发现有大量http链接被卡住，导致内存增加

分析线程运行情况，发现大量amqp线程处理等待状态

查看amqp线程发现全部都在创建链接

查看源代码

最后发现，ThreadLocal

tomcat因为是BIO模式，因此每次请求都是一个线程在处理，而在投递信息的时候，直接调用的send，因此这里会一直是null，直到。。。tomcat所有线程执行完毕，并且每个线程都通过ThreadLocal绑定channel，才不会在继续创建channel而且，tomcat设置的线程数，，嗯.配置如下，后果自己脑补吧

解决方案，，，在线程池中使用amqpTemplate即可

修改后的示例代码

rabbitMqThreadPool.execute(()->{
 	// 发布用户关注事件
     subscribeEventListener.onApplicationEvent(new SubscribeEvent(openid));
});

线程池配置

@Bean
    public ThreadPoolTaskExecutor rabbitMqThreadPool(){
        ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
        //获取到服务器的cpu内核
        int i = Runtime.getRuntime().availableProcessors();
        //核心池大小
        executor.setCorePoolSize(i);
        //最大线程数
        executor.setMaxPoolSize(i * 2);
        //队列长度
        executor.setQueueCapacity(60000);
        //线程空闲时间
        executor.setKeepAliveSeconds(1000);
        //线程前缀名称
        executor.setThreadNamePrefix("rabbitMq-thread-pool-");
        //配置拒绝策略
        executor.setRejectedExecutionHandler(new ThreadPoolExecutor.DiscardPolicy());
        return executor;
    }

这样 channel的数量，就是线程池的maxCore数量了，搞定收工