本博客属于 《RabbitMQ基础组件封装—整体结构》的子博客
一、整体架构
step1:消息落库,业务数据存库的同时,也要将消息记录存入数据库,二者要保证原子性;
step2:Producer发送消息到MQ Broker;
step3:Producer收到 broker 返回的确认消息;
step4:更改消息记录库的状态(定义三种状态:0待确认、1已确认、2确认失败);
step5:定时任务获取长时间处于待确认状态的消息;
step6:Producer重试发送消息;
step7:重试次数超过3次,将消息状态更新为确认失败,后续根据具体业务再处理确认失败的消息;
二、消息记录的增删改查
1. 当前项目名为 rabbit-core-producer,为了实现消息记录入库,需要跟数据库打交道,这里首先添加依赖:
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-jdbc</artifactId>
</dependency>
<dependency>
<groupId>org.mybatis.spring.boot</groupId>
<artifactId>mybatis-spring-boot-starter</artifactId>
<version>1.1.1</version>
</dependency>
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>druid</artifactId>
<version>1.1.10</version>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
</dependency>
2. 消息记录的建表语句 rabbit-producer-message-schema.sql
-- 表 broker_message.broker_message 结构
CREATE TABLE IF NOT EXISTS `broker_message` (
`message_id` varchar(128) NOT NULL,
`message` varchar(4000),
`try_count` int(4) DEFAULT 0,
`status` varchar(10) DEFAULT '',
`next_retry` timestamp NOT NULL DEFAULT '0000-00-00 00:00:00',
`create_time` timestamp NOT NULL DEFAULT '0000-00-00 00:00:00',
`update_time` timestamp NOT NULL DEFAULT '0000-00-00 00:00:00',
PRIMARY KEY (`message_id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;
将 rabbit-producer-message-schema.sql 放在 rabbit-core-producer 项目下的 /src/main/resources/rabbit-producer-message-schema.sql, rabbit-core-producer项目 在 RabbitMQ基础组件封装—整体结构 有具体说明(当前博客是 RabbitMQ基础组件封装—整体结构 的其中一个章节)。
3. 数据源的配置文件 rabbit-producer-message.properties
rabbit.producer.druid.type=com.alibaba.druid.pool.DruidDataSource
rabbit.producer.druid.jdbc.url=jdbc:mysql://localhost:3306/broker_message?characterEncoding=UTF-8&autoReconnect=true&zeroDateTimeBehavior=convertToNull&useUnicode=true&serverTimezone=GMT
rabbit.producer.druid.jdbc.driver-class-name=com.mysql.jdbc.Driver
rabbit.producer.druid.jdbc.username=root
rabbit.producer.druid.jdbc.password=root
rabbit.producer.druid.jdbc.initialSize=5
rabbit.producer.druid.jdbc.minIdle=1
rabbit.producer.druid.jdbc.maxActive=100
rabbit.producer.druid.jdbc.maxWait=60000
rabbit.producer.druid.jdbc.timeBetweenEvictionRunsMillis=60000
rabbit.producer.druid.jdbc.minEvictableIdleTimeMillis=300000
rabbit.producer.druid.jdbc.validationQuery=SELECT 1 FROM DUAL
rabbit.producer.druid.jdbc.testWhileIdle=true
rabbit.producer.druid.jdbc.testOnBorrow=false
rabbit.producer.druid.jdbc.testOnReturn=false
rabbit.producer.druid.jdbc.poolPreparedStatements=true
rabbit.producer.druid.jdbc.maxPoolPreparedStatementPerConnectionSize= 20
rabbit.producer.druid.jdbc.filters=stat,wall,log4j
rabbit.producer.druid.jdbc.useGlobalDataSourceStat=true
同样需要将该文件放在 rabbit-core-producer 项目下的 /src/main/resources/rabbit-producer-message.properties。
因为上面配置中有用到数据库 broker_message,所以需要自己提前建好一个数据库 broker_message。
4. BrokerMessage.java
public class BrokerMessage implements Serializable {
private static final long serialVersionUID = 7447792462810110841L;
private String messageId;
private Message message;
private Integer tryCount = 0;
private String status;
private Date nextRetry;
private Date createTime;
private Date updateTime;
// getter、setter方法省略
}
5. BrokerMessageMapper.xml
<?xml version="1.0" encoding="UTF-8" ?>
<!DOCTYPE mapper PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN" "http://mybatis.org/dtd/mybatis-3-mapper.dtd" >
<mapper namespace="com.didiok.rabbit.producer.mapper.BrokerMessageMapper" >
<resultMap id="BaseResultMap" type="com.didiok.rabbit.producer.entity.BrokerMessage" >
<id column="message_id" property="messageId" jdbcType="VARCHAR" />
<result column="message" property="message" jdbcType="VARCHAR" typeHandler="com.didiok.rabbit.common.mybatis.handler.MessageJsonTypeHandler" />
<result column="try_count" property="tryCount" jdbcType="INTEGER" />
<result column="status" property="status" jdbcType="VARCHAR" />
<result column="next_retry" property="nextRetry" jdbcType="TIMESTAMP" />
<result column="create_time" property="createTime" jdbcType="TIMESTAMP" />
<result column="update_time" property="updateTime" jdbcType="TIMESTAMP" />
</resultMap>
<sql id="Base_Column_List" >
message_id, message, try_count, status, next_retry, create_time, update_time
</sql>
<select id="selectByPrimaryKey" resultMap="BaseResultMap" parameterType="java.lang.String" >
select
<include refid="Base_Column_List" />
from broker_message
where message_id = #{messageId,jdbcType=VARCHAR}
</select>
<delete id="deleteByPrimaryKey" parameterType="java.lang.String" >
delete from broker_message
where message_id = #{messageId,jdbcType=VARCHAR}
</delete>
<insert id="insert" parameterType="com.didiok.rabbit.producer.entity.BrokerMessage" >
insert into broker_message (message_id, message, try_count,
status, next_retry, create_time,
update_time)
values (#{messageId,jdbcType=VARCHAR}, #{message,jdbcType=VARCHAR, typeHandler=com.didiok.rabbit.common.mybatis.handler.MessageJsonTypeHandler}, #{tryCount,jdbcType=INTEGER},
#{status,jdbcType=VARCHAR}, #{nextRetry,jdbcType=TIMESTAMP}, #{createTime,jdbcType=TIMESTAMP},
#{updateTime,jdbcType=TIMESTAMP})
</insert>
<insert id="insertSelective" parameterType="com.didiok.rabbit.producer.entity.BrokerMessage" >
insert into broker_message
<trim prefix="(" suffix=")" suffixOverrides="," >
<if test="messageId != null" >
message_id,
</if>
<if test="message != null" >
message,
</if>
<if test="tryCount != null" >
try_count,
</if>
<if test="status != null" >
status,
</if>
<if test="nextRetry != null" >
next_retry,
</if>
<if test="createTime != null" >
create_time,
</if>
<if test="updateTime != null" >
update_time,
</if>
</trim>
<trim prefix="values (" suffix=")" suffixOverrides="," >
<if test="messageId != null" >
#{messageId,jdbcType=VARCHAR},
</if>
<if test="message != null" >
#{message,jdbcType=VARCHAR, typeHandler=com.didiok.rabbit.common.mybatis.handler.MessageJsonTypeHandler},
</if>
<if test="tryCount != null" >
#{tryCount,jdbcType=INTEGER},
</if>
<if test="status != null" >
#{status,jdbcType=VARCHAR},
</if>
<if test="nextRetry != null" >
#{nextRetry,jdbcType=TIMESTAMP},
</if>
<if test="createTime != null" >
#{createTime,jdbcType=TIMESTAMP},
</if>
<if test="updateTime != null" >
#{updateTime,jdbcType=TIMESTAMP},
</if>
</trim>
</insert>
<update id="updateByPrimaryKeySelective" parameterType="com.didiok.rabbit.producer.entity.BrokerMessage" >
update broker_message
<set >
<if test="message != null" >
message = #{message,jdbcType=VARCHAR, typeHandler=com.didiok.rabbit.common.mybatis.handler.MessageJsonTypeHandler},
</if>
<if test="tryCount != null" >
try_count = #{tryCount,jdbcType=INTEGER},
</if>
<if test="status != null" >
status = #{status,jdbcType=VARCHAR},
</if>
<if test="nextRetry != null" >
next_retry = #{nextRetry,jdbcType=TIMESTAMP},
</if>
<if test="createTime != null" >
create_time = #{createTime,jdbcType=TIMESTAMP},
</if>
<if test="updateTime != null" >
update_time = #{updateTime,jdbcType=TIMESTAMP},
</if>
</set>
where message_id = #{messageId,jdbcType=VARCHAR}
</update>
<update id="updateByPrimaryKey" parameterType="com.didiok.rabbit.producer.entity.BrokerMessage" >
update broker_message
set message = #{message,jdbcType=VARCHAR, typeHandler=com.didiok.rabbit.common.mybatis.handler.MessageJsonTypeHandler},
try_count = #{tryCount,jdbcType=INTEGER},
status = #{status,jdbcType=VARCHAR},
next_retry = #{nextRetry,jdbcType=TIMESTAMP},
create_time = #{createTime,jdbcType=TIMESTAMP},
update_time = #{updateTime,jdbcType=TIMESTAMP}
where message_id = #{messageId,jdbcType=VARCHAR}
</update>
<update id="changeBrokerMessageStatus" >
update broker_message bm
set bm.status = #{brokerMessageStatus,jdbcType=VARCHAR},
bm.update_time = #{updateTime, jdbcType=TIMESTAMP}
where bm.message_id = #{brokerMessageId,jdbcType=VARCHAR}
</update>
<select id="queryBrokerMessageStatus4Timeout" resultMap="BaseResultMap" >
<![CDATA[
select message_id, message, try_count, status, next_retry, create_time, update_time
from broker_message bm
where bm.status = #{brokerMessageStatus,jdbcType=VARCHAR}
and bm.next_retry < sysdate()
]]>
</select>
<select id="queryBrokerMessageStatus" resultMap="BaseResultMap" >
select message_id, message, try_count, status, next_retry, create_time, update_time
from broker_message bm
where bm.status = #{brokerMessageStatus,jdbcType=VARCHAR}
</select>
<update id="update4TryCount" >
update broker_message bm
set bm.try_count = bm.try_count + 1,
bm.update_time = #{updateTime,jdbcType=TIMESTAMP}
where bm.message_id = #{brokerMessageId,jdbcType=VARCHAR}
</update>
</mapper>
6. BrokerMessageMapper.java
@Mapper
public interface BrokerMessageMapper {
int deleteByPrimaryKey(String messageId);
int insert(BrokerMessage record);
int insertSelective(BrokerMessage record);
BrokerMessage selectByPrimaryKey(String messageId);
int updateByPrimaryKeySelective(BrokerMessage record);
int updateByPrimaryKeyWithBLOBs(BrokerMessage record);
int updateByPrimaryKey(BrokerMessage record);
void changeBrokerMessageStatus(@Param("brokerMessageId")String brokerMessageId, @Param("brokerMessageStatus")String brokerMessageStatus, @Param("updateTime")Date updateTime);
List<BrokerMessage> queryBrokerMessageStatus4Timeout(@Param("brokerMessageStatus")String brokerMessageStatus);
List<BrokerMessage> queryBrokerMessageStatus(@Param("brokerMessageStatus")String brokerMessageStatus);
int update4TryCount(@Param("brokerMessageId")String brokerMessageId, @Param("updateTime")Date updateTime);
}
7. MessageStoreService.java(这里不加接口类了,直接在MessageStoreService.java中写具体逻辑实现)
@Service
public class MessageStoreService {
@Autowired
private BrokerMessageMapper brokerMessageMapper;
public int insert(BrokerMessage brokerMessage) {
return this.brokerMessageMapper.insert(brokerMessage);
}
public BrokerMessage selectByMessageId(String messageId) {
return this.brokerMessageMapper.selectByPrimaryKey(messageId);
}
public void succuess(String messageId) {
this.brokerMessageMapper.changeBrokerMessageStatus(messageId,
BrokerMessageStatus.SEND_OK.getCode(),
new Date());
}
public void failure(String messageId) {
this.brokerMessageMapper.changeBrokerMessageStatus(messageId,
BrokerMessageStatus.SEND_FAIL.getCode(),
new Date());
}
public List<BrokerMessage> fetchTimeOutMessage4Retry(BrokerMessageStatus brokerMessageStatus){
return this.brokerMessageMapper.queryBrokerMessageStatus4Timeout(brokerMessageStatus.getCode());
}
public int updateTryCount(String brokerMessageId) {
return this.brokerMessageMapper.update4TryCount(brokerMessageId, new Date());
}
}
三、整合数据源
1. 读取配置文件,生成数据源,RabbitProducerDataSourceConfiguration.java
@Configuration
@PropertySource({"classpath:rabbit-producer-message.properties"})
public class RabbitProducerDataSourceConfiguration {
private static Logger LOGGER = org.slf4j.LoggerFactory.getLogger(RabbitProducerDataSourceConfiguration.class);
@Value("${rabbit.producer.druid.type}")
private Class<? extends DataSource> dataSourceType;
@Bean(name = "rabbitProducerDataSource")
@Primary
// 以这个rabbit.producer.druid.jdbc为前缀的属性值都会注入到DataSource中
@ConfigurationProperties(prefix = "rabbit.producer.druid.jdbc")
public DataSource rabbitProducerDataSource() throws SQLException {
DataSource rabbitProducerDataSource = DataSourceBuilder.create().type(dataSourceType).build();
LOGGER.info("============= rabbitProducerDataSource : {} ================", rabbitProducerDataSource);
return rabbitProducerDataSource;
}
public DataSourceProperties primaryDataSourceProperties(){
return new DataSourceProperties();
}
public DataSource primaryDataSource(){
return primaryDataSourceProperties().initializeDataSourceBuilder().build();
}
}
2. 执行指定的sql脚本 ,BrokerMessageConfiguration.java
/**
* $BrokerMessageConfiguration
* 帮我执行SQL脚本
* 帮我进行数据库表结构的创建
*
*/
@Configuration
public class BrokerMessageConfiguration {
@Autowired
private DataSource rabbitProducerDataSource;
/**
* 加载 rabbit-producer-message-schema.sql 脚本(这是一个建表语句)
*/
@Value("classpath:rabbit-producer-message-schema.sql")
private Resource schemaScript;
@Bean
public DataSourceInitializer initDataSourceInitializer() {
System.err.println("--------------rabbitProducerDataSource-----------:" + rabbitProducerDataSource);
final DataSourceInitializer initializer = new DataSourceInitializer();
// 设置之前生成的数据源
initializer.setDataSource(rabbitProducerDataSource);
// 执行指定的sql脚本
initializer.setDatabasePopulator(databasePopulator());
return initializer;
}
/**
* 执行指定的sql脚本
* @return
*/
private DatabasePopulator databasePopulator() {
final ResourceDatabasePopulator populator = new ResourceDatabasePopulator();
populator.addScript(schemaScript);
return populator;
}
}
3. 接下来是和 Mybatis 配置相关的文件:RabbitProducerMyBatisConfiguration.java
@Configuration
// @AutoConfigureAfter是指等到RabbitProducerDataSourceConfiguration执行完才能执行,即数据源生成之后才能执行当前类
@AutoConfigureAfter(value = {RabbitProducerDataSourceConfiguration.class})
public class RabbitProducerMyBatisConfiguration {
@Resource(name= "rabbitProducerDataSource")
private DataSource rabbitProducerDataSource;
@Bean(name="rabbitProducerSqlSessionFactory")
public SqlSessionFactory rabbitProducerSqlSessionFactory(DataSource rabbitProducerDataSource) {
SqlSessionFactoryBean bean = new SqlSessionFactoryBean();
bean.setDataSource(rabbitProducerDataSource);
ResourcePatternResolver resolver = new PathMatchingResourcePatternResolver();
try {
// mapper.xml文件加载,这些配置本可以写在 application.yml 中,但是由于要作为一个基础组件,所以写在代码里,跟业务层面解绑,让业务层面无感知
bean.setMapperLocations(resolver.getResources("classpath:com/didiok/rabbit/producer/mapping/*.xml"));
SqlSessionFactory sqlSessionFactory = bean.getObject();
sqlSessionFactory.getConfiguration().setCacheEnabled(Boolean.TRUE);
return sqlSessionFactory;
} catch (Exception e) {
throw new RuntimeException(e);
}
}
@Bean(name="rabbitProducerSqlSessionTemplate")
public SqlSessionTemplate rabbitProducerSqlSessionTemplate(SqlSessionFactory sqlSessionFactory) {
return new SqlSessionTemplate(sqlSessionFactory);
}
}
4. Mapper扫描配置相关的文件: RabbitProducerMybatisMapperScanerConfig.java
@Configuration
// @AutoConfigureAfter是指等到RabbitProducerDataSourceConfiguration执行完才能执行,即数据源生成之后才能执行当前类
@AutoConfigureAfter(RabbitProducerDataSourceConfiguration.class)
public class RabbitProducerMybatisMapperScanerConfig {
@Bean(name="rabbitProducerMapperScannerConfigurer")
public MapperScannerConfigurer rabbitProducerMapperScannerConfigurer() {
// mapper.java文件加载,这些配置本可以写在 application.yml 中,但是由于要作为一个基础组件,所以写在代码里,跟业务层面解绑,让业务层面无感知
MapperScannerConfigurer mapperScannerConfigurer = new MapperScannerConfigurer();
mapperScannerConfigurer.setSqlSessionFactoryBeanName("rabbitProducerSqlSessionFactory");
mapperScannerConfigurer.setBasePackage("com.didiok.rabbit.producer.mapper");
return mapperScannerConfigurer;
}
}
四、可靠性发送消息代码实现
/**
* $RabbitBrokerImpl 真正的发送不同类型的消息实现类
*
*/
@Slf4j
@Component
public class RabbitBrokerImpl implements RabbitBroker {
@Autowired
private RabbitTemplateContainer rabbitTemplateContainer;
@Autowired
private MessageStoreService messageStoreService;
/**
* 可靠性消息发送
*/
@Override
public void reliantSend(Message message) {
message.setMessageType(MessageType.RELIANT);
BrokerMessage bm = messageStoreService.selectByMessageId(message.getMessageId());
if(bm == null) {
//1. 把数据库的消息发送日志先记录好
Date now = new Date();
BrokerMessage brokerMessage = new BrokerMessage();
brokerMessage.setMessageId(message.getMessageId());
brokerMessage.setStatus(BrokerMessageStatus.SENDING.getCode());
//tryCount默认等于0 所以在最开始发送的时候不需要进行设置
brokerMessage.setNextRetry(DateUtils.addMinutes(now, BrokerMessageConst.TIMEOUT));
brokerMessage.setCreateTime(now);
brokerMessage.setUpdateTime(now);
brokerMessage.setMessage(message);
messageStoreService.insert(brokerMessage);
}
//2. 执行真正的发送消息逻辑
sendKernel(message);
}
@Override
public void rapidSend(Message message) {
// 省略...
}
/**
* $sendKernel 发送消息的核心方法 使用异步线程池进行发送消息
* @param message
*/
private void sendKernel(Message message) {
AsyncBaseQueue.submit((Runnable) () -> {
CorrelationData correlationData =
// 回调函数confirm中需要用到message.getMessageId(), message.getMessageType()。所以可以放在CorrelationData中
new CorrelationData(String.format("%s#%s#%s",
message.getMessageId(),
System.currentTimeMillis(),
message.getMessageType()));
String topic = message.getTopic();
String routingKey = message.getRoutingKey();
RabbitTemplate rabbitTemplate = rabbitTemplateContainer.getTemplate(message);
rabbitTemplate.convertAndSend(topic, routingKey, message, correlationData);
log.info("#RabbitBrokerImpl.sendKernel# send to rabbitmq, messageId: {}", message.getMessageId());
});
}
@Override
public void confirmSend(Message message) {
// 省略...
}
@Override
public void sendMessages() {
// 省略...
}
}
并且在回调函数中,也要添加相应的逻辑:
/**
* $RabbitTemplateContainer池化封装
* 每一个topic 对应一个RabbitTemplate
* 1. 提高发送的效率
* 2. 可以根据不同的需求制定化不同的RabbitTemplate, 比如每一个topic 都有自己的routingKey规则
*/
@Slf4j
@Component
public class RabbitTemplateContainer implements RabbitTemplate.ConfirmCallback {
private Map<String /* TOPIC */, RabbitTemplate> rabbitMap = Maps.newConcurrentMap();
private Splitter splitter = Splitter.on("#");
private SerializerFactory serializerFactory = JacksonSerializerFactory.INSTANCE;
@Autowired
private ConnectionFactory connectionFactory;
@Autowired
private MessageStoreService messageStoreService;
public RabbitTemplate getTemplate(Message message) throws MessageRunTimeException {
// 省略...
}
/**
* 无论是 confirm 消息 还是 reliant 消息 ,发送消息以后 broker都会去回调confirm
*/
@Override
public void confirm(CorrelationData correlationData, boolean ack, String cause) {
// 具体的消息应答
List<String> strings = splitter.splitToList(correlationData.getId());
String messageId = strings.get(0);
long sendTime = Long.parseLong(strings.get(1));
String messageType = strings.get(2);
if(ack) {
// 当Broker 返回ACK成功时, 就是更新一下日志表里对应的消息发送状态为 SEND_OK
// 如果当前消息类型为reliant 我们就去数据库查找并进行更新
if(MessageType.RELIANT.endsWith(messageType)) {
this.messageStoreService.succuess(messageId);
}
log.info("send message is OK, confirm messageId: {}, sendTime: {}", messageId, sendTime);
} else {
log.error("send message is Fail, confirm messageId: {}, sendTime: {}", messageId, sendTime);
}
}
}
上面大部分代码都是在实现迅速类型的消息发送时已经编写了,只是在 confirm()方法中添加了:
// 如果当前消息类型为reliant 我们就去数据库查找并进行更新
if(MessageType.RELIANT.endsWith(messageType)) {
this.messageStoreService.succuess(messageId);
}
五、定时任务获取长时间处于待确认状态的消息并重新发送
1. 实现分布式定时任务
这里的定时任务是使用 ElasticJob,并对其进行封装,封装在项目 rabbit-task中,封装成为了两个注解 @EnableElasticJob 和 @ElasticJobConfig 。
具体的 ElasticJob 的使用和封装过程可参考教程:ElasticJob使用与封装
2. 将封装好的项目 rabbit-task 添加到 当前项目中并使用
(1)引入 rabbit-task 的依赖
<dependency>
<groupId>com.bfxy.base.rabbit</groupId>
<artifactId>rabbit-task</artifactId>
<version>0.0.1-SNAPSHOT</version>
</dependency>
(2)使用注解@EnableElasticJob
在当前项目 rabbit-core-producer 中的 自动装配类 中添加注解 @EnableElasticJob,使得当 应用程序启动的时候,就能对 ZooKeeper注册中心进行初始化,以及 ElasticJob的定时任务解析类 ElasticJobConfParser 的初始化。
/**
* $RabbitProducerAutoConfiguration 自动装配
*
*/
@EnableElasticJob
@Configuration
@ComponentScan({"com.didiok.rabbit.producer.*"})
public class RabbitProducerAutoConfiguration {
}
(3)实现定时任务的具体处理逻辑并在类上加注解@EnableElasticJob
这里为了消息的可靠性发送,我们需要抓取 超时却仍处于待确认状态 的消息,进行重新发送消息。这里使用 ElasticJob 的流式定时任务 DataFlowJob。
@Component
@ElasticJobConfig(
name= "com.bfxy.rabbit.producer.task.RetryMessageDataflowJob",
cron= "0/10 * * * * ?",
description = "可靠性投递消息补偿任务",
overwrite = true,
shardingTotalCount = 1
)
@Slf4j
public class RetryMessageDataflowJob implements DataflowJob<BrokerMessage>{
@Autowired
private MessageStoreService messageStoreService;
@Autowired
private RabbitBroker rabbitBroker;
private static final int MAX_RETRY_COUNT = 3;
@Override
public List<BrokerMessage> fetchData(ShardingContext shardingContext) {
// 抓取状态为未确认,而且 next_retry 小于当前时间的这些消息,为了确定百分百能发送成功,需要再进行重发
List<BrokerMessage> list = messageStoreService.fetchTimeOutMessage4Retry(BrokerMessageStatus.SENDING);
log.info("--------@@@@@ 抓取数据集合, 数量: {} @@@@@@-----------" , list.size());
return list;
}
@Override
public void processData(ShardingContext shardingContext, List<BrokerMessage> dataList) {
dataList.forEach( brokerMessage -> {
String messageId = brokerMessage.getMessageId();
if(brokerMessage.getTryCount() >= MAX_RETRY_COUNT) {
// 重试次数大于3,就不再进行重发了,直接认为发送失败,更改标记为失败
this.messageStoreService.failure(messageId);
log.warn(" -----消息设置为最终失败,消息ID: {} -------", messageId);
} else {
// 每次重发的时候要更新一下try_count和next_retry字段
this.messageStoreService.updateTryCount(messageId);
// 重发消息
this.rabbitBroker.reliantSend(brokerMessage.getMessage());
}
});
}
}
上面的代码中加入了注解
@ElasticJobConfig( name= "com.bfxy.rabbit.producer.task.RetryMessageDataflowJob", cron= "0/10 * * * * ?", description = "可靠性投递消息补偿任务", overwrite = true, shardingTotalCount = 1 )
则该类中的逻辑会定时执行。文章来源:https://www.toymoban.com/news/detail-442204.html
对于重发消息的代码 this.rabbitBroker.reliantSend(brokerMessage.getMessage());,之前已经做过说明,这里不再赘述。文章来源地址https://www.toymoban.com/news/detail-442204.html
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