目录

• 需求
• 步骤
• 环境搭建
• canal.properties
• instance.properties
• 修改canal配置文件
• 整合SpringBoot Canal实现客户端
• Canal整合RabbitMQ
• SpringBoot整合RabbitMQ

需求

我想要在SpringBoot中采用一种与业务代码解耦合的方式，来实现数据的变更记录，记录的内容是新数据，如果是更新操作还得有旧数据内容。

经过调研发现，使用Canal来监听MySQL的binlog变化可以实现这个需求，可是在监听到变化后需要马上保存变更记录，除非再做一些逻辑处理，于是我又结合了RabbitMQ来处理保存变更记录的操作。

步骤

• 启动MySQL环境，并开启binlog
• 启动Canal环境，为其创建一个MySQL账号，然后以Slave的形式连接MySQL
• Canal服务模式设为TCP，用Java编写客户端代码，监听MySQL的binlog修改
• Canal服务模式设为RabbitMQ，启动RabbitMQ环境，配置Canal和RabbitMQ的连接，用消息队列去接收binlog修改事件

环境搭建

环境搭建基于docker-compose：

version: "3"
services:
    mysql:
        network_mode: mynetwork
        container_name: mymysql
        ports:
            - 3306:3306
        restart: always
        volumes:
            - /etc/localtime:/etc/localtime
            - /home/mycontainers/mymysql/data:/data
            - /home/mycontainers/mymysql/mysql:/var/lib/mysql
            - /home/mycontainers/mymysql/conf:/etc/mysql
        environment:
            - MYSQL_ROOT_PASSWORD=root
        command: 
            --character-set-server=utf8mb4
            --collation-server=utf8mb4_unicode_ci
            --log-bin=/var/lib/mysql/mysql-bin
            --server-id=1
            --binlog-format=ROW
            --expire_logs_days=7
            --max_binlog_size=500M
        image: mysql:5.7.20
    rabbitmq:   
        container_name: myrabbit
        ports:
            - 15672:15672
            - 5672:5672
        restart: always
        volumes:
            - /etc/localtime:/etc/localtime
            - /home/mycontainers/myrabbit/rabbitmq:/var/lib/rabbitmq
        network_mode: mynetwork
        environment:
            - RABBITMQ_DEFAULT_USER=admin
            - RABBITMQ_DEFAULT_PASS=123456
        image: rabbitmq:3.8-management
    canal-server:
        container_name: canal-server
        restart: always
        ports:
            - 11110:11110
            - 11111:11111
            - 11112:11112
        volumes:
            - /home/mycontainers/canal-server/conf/canal.properties:/home/admin/canal-server/conf/canal.properties
            - /home/mycontainers/canal-server/conf/instance.properties:/home/admin/canal-server/conf/example/instance.properties
            - /home/mycontainers/canal-server/logs:/home/admin/canal-server/logs
        network_mode: mynetwork
        depends_on:
            - mysql
            - rabbitmq
            # - canal-admin
        image: canal/canal-server:v1.1.5

我们需要修改下Canal环境的配置文件：canal.properties和instance.properties，映射Canal中的以下两个路径：

• /home/admin/canal-server/conf/canal.properties：配置文件中，canal.destinations意思是server上部署的instance列表，
• /home/admin/canal-server/conf/example/instance.properties：这里的/example是指instance即实例名，要和上面canal.properties内instance配置对应，canal会为实例创建对应的文件夹，一个Client对应一个实例

以下是我们需要准备的两个配置文件具体内容：

canal.properties

#################################################
#########     common argument   #############
#################################################
# tcp bind ip
canal.ip =
# register ip to zookeeper
canal.register.ip =
canal.port = 11111
canal.metrics.pull.port = 11112
# canal instance user/passwd
# canal.user = canal
# canal.passwd = E3619321C1A937C46A0D8BD1DAC39F93B27D4458
​
# canal admin config
# canal.admin.manager = canal-admin:8089
​
# canal.admin.port = 11110
# canal.admin.user = admin
# canal.admin.passwd = 6BB4837EB74329105EE4568DDA7DC67ED2CA2AD9
​
# admin auto register 自动注册
# canal.admin.register.auto = true
# 集群名，单机则不写
# canal.admin.register.cluster =
# Canal Server 名字
# canal.admin.register.name = canal-admin
​
canal.zkServers =
# flush data to zk
canal.zookeeper.flush.period = 1000
canal.withoutNetty = false
# tcp, kafka, rocketMQ, rabbitMQ, pulsarMQ
canal.serverMode = tcp
# flush meta cursor/parse position to file
canal.file.data.dir = ${canal.conf.dir}
canal.file.flush.period = 1000
## memory store RingBuffer size, should be Math.pow(2,n)
canal.instance.memory.buffer.size = 16384
## memory store RingBuffer used memory unit size , default 1kb
canal.instance.memory.buffer.memunit = 1024 
## meory store gets mode used MEMSIZE or ITEMSIZE
canal.instance.memory.batch.mode = MEMSIZE
canal.instance.memory.rawEntry = true
​
## detecing config
canal.instance.detecting.enable = false
#canal.instance.detecting.sql = insert into retl.xdual values(1,now()) on duplicate key update x=now()
canal.instance.detecting.sql = select 1
canal.instance.detecting.interval.time = 3
canal.instance.detecting.retry.threshold = 3
canal.instance.detecting.heartbeatHaEnable = false
​
# support maximum transaction size, more than the size of the transaction will be cut into multiple transactions delivery
canal.instance.transaction.size =  1024
# mysql fallback connected to new master should fallback times
canal.instance.fallbackIntervalInSeconds = 60
​
# network config
canal.instance.network.receiveBufferSize = 16384
canal.instance.network.sendBufferSize = 16384
canal.instance.network.soTimeout = 30
​
# binlog filter config
canal.instance.filter.druid.ddl = true
canal.instance.filter.query.dcl = false
canal.instance.filter.query.dml = false
canal.instance.filter.query.ddl = false
canal.instance.filter.table.error = false
canal.instance.filter.rows = false
canal.instance.filter.transaction.entry = false
canal.instance.filter.dml.insert = false
canal.instance.filter.dml.update = false
canal.instance.filter.dml.delete = false
​
# binlog format/image check
canal.instance.binlog.format = ROW,STATEMENT,MIXED 
canal.instance.binlog.image = FULL,MINIMAL,NOBLOB
​
# binlog ddl isolation
canal.instance.get.ddl.isolation = false
​
# parallel parser config
canal.instance.parser.parallel = true
## concurrent thread number, default 60% available processors, suggest not to exceed Runtime.getRuntime().availableProcessors()
canal.instance.parser.parallelThreadSize = 16
## disruptor ringbuffer size, must be power of 2
canal.instance.parser.parallelBufferSize = 256
​
# table meta tsdb info
canal.instance.tsdb.enable = true
canal.instance.tsdb.dir = ${canal.file.data.dir:../conf}/${canal.instance.destination:}
canal.instance.tsdb.url = jdbc:h2:${canal.instance.tsdb.dir}/h2;CACHE_SIZE=1000;MODE=MYSQL;
canal.instance.tsdb.dbUsername = canal
canal.instance.tsdb.dbPassword = canal
# dump snapshot interval, default 24 hour
canal.instance.tsdb.snapshot.interval = 24
# purge snapshot expire , default 360 hour(15 days)
canal.instance.tsdb.snapshot.expire = 360
​
#################################################
#########     destinations    #############
#################################################
canal.destinations = canal-exchange
# conf root dir
canal.conf.dir = ../conf
# auto scan instance dir add/remove and start/stop instance
canal.auto.scan = true
canal.auto.scan.interval = 5
# set this value to 'true' means that when binlog pos not found, skip to latest.
# WARN: pls keep 'false' in production env, or if you know what you want.
canal.auto.reset.latest.pos.mode = false
​
canal.instance.tsdb.spring.xml = classpath:spring/tsdb/h2-tsdb.xml
#canal.instance.tsdb.spring.xml = classpath:spring/tsdb/mysql-tsdb.xml
​
canal.instance.global.mode = spring
canal.instance.global.lazy = false
canal.instance.global.manager.address = ${canal.admin.manager}
#canal.instance.global.spring.xml = classpath:spring/memory-instance.xml
canal.instance.global.spring.xml = classpath:spring/file-instance.xml
#canal.instance.global.spring.xml = classpath:spring/default-instance.xml
​
##################################################
#########         MQ Properties      #############
##################################################
# aliyun ak/sk , support rds/mq
canal.aliyun.accessKey =
canal.aliyun.secretKey =
canal.aliyun.uid=
​
canal.mq.flatMessage = true
canal.mq.canalBatchSize = 50
canal.mq.canalGetTimeout = 100
# Set this value to "cloud", if you want open message trace feature in aliyun.
canal.mq.accessChannel = local
​
canal.mq.database.hash = true
canal.mq.send.thread.size = 30
canal.mq.build.thread.size = 8
​
##################################################
#########          Kafka         #############
##################################################
kafka.bootstrap.servers = 127.0.0.1:9092
kafka.acks = all
kafka.compression.type = none
kafka.batch.size = 16384
kafka.linger.ms = 1
kafka.max.request.size = 1048576
kafka.buffer.memory = 33554432
kafka.max.in.flight.requests.per.connection = 1
kafka.retries = 0
​
kafka.kerberos.enable = false
kafka.kerberos.krb5.file = "../conf/kerberos/krb5.conf"
kafka.kerberos.jaas.file = "../conf/kerberos/jaas.conf"
​
##################################################
#########         RocketMQ       #############
##################################################
rocketmq.producer.group = test
rocketmq.enable.message.trace = false
rocketmq.customized.trace.topic =
rocketmq.namespace =
rocketmq.namesrv.addr = 127.0.0.1:9876
rocketmq.retry.times.when.send.failed = 0
rocketmq.vip.channel.enabled = false
rocketmq.tag = 
​
##################################################
#########         RabbitMQ       #############
##################################################
rabbitmq.host = myrabbit
rabbitmq.virtual.host = /
rabbitmq.exchange = canal-exchange
rabbitmq.username = admin
rabbitmq.password = RabbitMQ密码
rabbitmq.deliveryMode =
​
##################################################
#########           Pulsar         #############
##################################################
pulsarmq.serverUrl =
pulsarmq.roleToken =
pulsarmq.topicTenantPrefix =

此时canal.serverMode = tcp，即TCP直连，我们先开启这个服务，然后手写Java客户端代码去连接它，等下再改为RabbitMQ。

通过注释可以看到，canal支持的服务模式有：tcp, kafka, rocketMQ, rabbitMQ, pulsarMQ，即主流的消息队列都支持。

instance.properties

#################################################
## mysql serverId , v1.0.26+ will autoGen
#canal.instance.mysql.slaveId=123
​
# enable gtid use true/false
canal.instance.gtidon=false
​
# position info
canal.instance.master.address=mymysql:3306
canal.instance.master.journal.name=
canal.instance.master.position=
canal.instance.master.timestamp=
canal.instance.master.gtid=
​
# rds oss binlog
canal.instance.rds.accesskey=
canal.instance.rds.secretkey=
canal.instance.rds.instanceId=
​
# table meta tsdb info
canal.instance.tsdb.enable=true
#canal.instance.tsdb.url=jdbc:mysql://127.0.0.1:3306/canal_tsdb
#canal.instance.tsdb.dbUsername=canal
#canal.instance.tsdb.dbPassword=canal
​
#canal.instance.standby.address =
#canal.instance.standby.journal.name =
#canal.instance.standby.position =
#canal.instance.standby.timestamp =
#canal.instance.standby.gtid=
​
# username/password
canal.instance.dbUsername=canal
canal.instance.dbPassword=canal
canal.instance.connectionCharset = UTF-8
# enable druid Decrypt database password
canal.instance.enableDruid=false
#canal.instance.pwdPublicKey=MFwwDQYJKoZIhvcNAQEBBQADSwAwSAJBALK4BUxdDltRRE5/zXpVEVPUgunvscYFtEip3pmLlhrWpacX7y7GCMo2/JM6LeHmiiNdH1FWgGCpUfircSwlWKUCAwEAAQ==
​
# table regex
canal.instance.filter.regex=.*\..*
# table black regex
canal.instance.filter.black.regex=mysql\.slave_.*
# table field filter(format: schema1.tableName1:field1/field2,schema2.tableName2:field1/field2)
#canal.instance.filter.field=test1.t_product:id/subject/keywords,test2.t_company:id/name/contact/ch
# table field black filter(format: schema1.tableName1:field1/field2,schema2.tableName2:field1/field2)
#canal.instance.filter.black.field=test1.t_product:subject/product_image,test2.t_company:id/name/contact/ch
​
# mq config
canal.mq.topic=canal-routing-key
# dynamic topic route by schema or table regex
#canal.mq.dynamicTopic=mytest1.user,topic2:mytest2\..*,.*\..*
canal.mq.partition=0
# hash partition config
#canal.mq.enableDynamicQueuePartition=false
#canal.mq.partitionsNum=3
#canal.mq.dynamicTopicPartitionNum=test.*:4,mycanal:6
#canal.mq.partitionHash=test.table:id^name,.*\..*
#################################################

把这两个配置文件映射好，再次提醒，注意实例的路径名，默认是：/example/instance.properties

修改canal配置文件

我们需要修改这个实例配置文件，去连接MySQL，确保以下的配置正确：

canal.instance.master.address=mymysql:3306
canal.instance.dbUsername=canal
canal.instance.dbPassword=canal

mymysql是同为docker容器的MySQL环境，端口3306是指内部端口。

这里多说明一下，docker端口配置时假设为：13306:3306，那么容器对外的端口就是13306，内部是3306，在本示例中，MySQL和Canal都是容器环境，所以Canal连接MySQL需要满足以下条件：

• 处于同一网段（docker-compose.yml中的mynetwork）
• 访问内部端口（即3306，而非13306）

dbUsername和dbPassword为MySQL账号密码，为了开发方便可以使用root/root，但是我仍建议自行创建用户并分配访问权限：

# 进入docker中的mysql容器
docker exec -it mymysql bash
# 进入mysql指令模式
mysql -uroot -proot
​
# 编写MySQL语句并执行
> ...
-- 选择mysql
use mysql;
-- 创建canal用户，账密：canal/canal
create user 'canal'@'%' identified by 'canal';
-- 分配权限，以及允许所有主机登录该用户
grant SELECT, INSERT, UPDATE, DELETE, REPLICATION SLAVE, REPLICATION CLIENT on *.* to 'canal'@'%';
​
-- 刷新一下使其生效
flush privileges;
​
-- 附带一个删除用户指令
drop user 'canal'@'%';

用navicat或者shell去登录canal这个用户，可以访问即创建成功

整合SpringBoot Canal实现客户端

Maven依赖：

<canal.version>1.1.5</canal.version>
​
<!--canal-->
<dependency>
  <groupId>com.alibaba.otter</groupId>
  <artifactId>canal.client</artifactId>
  <version>${canal.version}</version>
</dependency>
<dependency>
  <groupId>com.alibaba.otter</groupId>
  <artifactId>canal.protocol</artifactId>
  <version>${canal.version}</version>
</dependency>

新增组件并启动：

import com.alibaba.otter.canal.client.CanalConnector;
import com.alibaba.otter.canal.client.CanalConnectors;
import com.alibaba.otter.canal.protocol.CanalEntry;
import com.alibaba.otter.canal.protocol.Message;
import org.springframework.boot.CommandLineRunner;
import org.springframework.stereotype.Component;
import java.net.InetSocketAddress;
import java.util.List;
@Component
public class CanalClient {
    private final static int BATCH_SIZE = 1000;
    public void run() {
        // 创建链接
        CanalConnector connector = CanalConnectors.newSingleConnector(new InetSocketAddress("localhost", 11111), "canal-exchange", "canal", "canal");
        try {
            //打开连接
            connector.connect();
            //订阅数据库表,全部表
            connector.subscribe(".*\..*");
            //回滚到未进行ack的地方，下次fetch的时候，可以从最后一个没有ack的地方开始拿
            connector.rollback();
            while (true) {
                // 获取指定数量的数据
                Message message = connector.getWithoutAck(BATCH_SIZE);
                //获取批量ID
                long batchId = message.getId();
                //获取批量的数量
                int size = message.getEntries().size();
                //如果没有数据
                if (batchId == -1 || size == 0) {
                    try {
                        //线程休眠2秒
                        Thread.sleep(2000);
                    } catch (InterruptedException e) {
                        e.printStackTrace();
                    }
                } else {
                    //如果有数据,处理数据
                    printEntry(message.getEntries());
                }
                //进行 batch id 的确认。确认之后，小于等于此 batchId 的 Message 都会被确认。
                connector.ack(batchId);
            }
        } catch (Exception e) {
            e.printStackTrace();
        } finally {
            connector.disconnect();
        }
    }
​
    /**
     * 打印canal server解析binlog获得的实体类信息
     */
    private static void printEntry(List<CanalEntry.Entry> entrys) {
        for (CanalEntry.Entry entry : entrys) {
            if (entry.getEntryType() == CanalEntry.EntryType.TRANSACTIONBEGIN || entry.getEntryType() == CanalEntry.EntryType.TRANSACTIONEND) {
                //开启/关闭事务的实体类型，跳过
                continue;
            }
            //RowChange对象，包含了一行数据变化的所有特征
            //比如isDdl 是否是ddl变更操作 sql 具体的ddl sql beforeColumns afterColumns 变更前后的数据字段等等
            CanalEntry.RowChange rowChage;
            try {
                rowChage = CanalEntry.RowChange.parseFrom(entry.getStoreValue());
            } catch (Exception e) {
                throw new RuntimeException("ERROR ## parser of eromanga-event has an error , data:" + entry.toString(), e);
            }
            //获取操作类型：insert/update/delete类型
            CanalEntry.EventType eventType = rowChage.getEventType();
            //打印Header信息
            System.out.println(String.format("================》; binlog[%s:%s] , name[%s,%s] , eventType : %s",
                    entry.getHeader().getLogfileName(), entry.getHeader().getLogfileOffset(),
                    entry.getHeader().getSchemaName(), entry.getHeader().getTableName(),
                    eventType));
            //判断是否是DDL语句
            if (rowChage.getIsDdl()) {
                System.out.println("================》;isDdl: true,sql:" + rowChage.getSql());
            }
            //获取RowChange对象里的每一行数据，打印出来
            for (CanalEntry.RowData rowData : rowChage.getRowDatasList()) {
                //如果是删除语句
                if (eventType == CanalEntry.EventType.DELETE) {
                    printColumn(rowData.getBeforeColumnsList());
                    //如果是新增语句
                } else if (eventType == CanalEntry.EventType.INSERT) {
                    printColumn(rowData.getAfterColumnsList());
                    //如果是更新的语句
                } else {
                    //变更前的数据
                    System.out.println("------->; before");
                    printColumn(rowData.getBeforeColumnsList());
                    //变更后的数据
                    System.out.println("------->; after");
                    printColumn(rowData.getAfterColumnsList());
                }
            }
        }
    }
​
    private static void printColumn(List<CanalEntry.Column> columns) {
        for (CanalEntry.Column column : columns) {
            System.out.println(column.getName() + " : " + column.getValue() + "    update=" + column.getUpdated());
        }
    }
}

启动类Application：

@SpringBootApplication
public class BaseApplication implements CommandLineRunner {
    @Autowired
    private CanalClient canalClient;
​
    @Override
    public void run(String... args) throws Exception {
        canalClient.run();
    }
}

启动程序，此时新增或修改数据库中的数据，我们就能从客户端中监听到

不过我建议监听的信息放到消息队列中，在空闲的时候去处理，所以直接配置Canal整合RabbitMQ更好。

Canal整合RabbitMQ

修改canal.properties中的serverMode：

canal.serverMode = rabbitMQ

修改instance.properties中的topic：

canal.mq.topic=canal-routing-key

然后找到关于RabbitMQ的配置：

##################################################
#########         RabbitMQ       #############
##################################################
# 连接rabbit，写IP，因为同个网络下，所以可以写容器名
rabbitmq.host = myrabbit
rabbitmq.virtual.host = /
# 交换器名称，等等我们要去手动创建
rabbitmq.exchange = canal-exchange
# 账密
rabbitmq.username = admin
rabbitmq.password = 123456
# 暂不支持指定端口，使用的是默认的5762，好在在本示例中适用

重新启动容器，进入RabbitMQ管理页面创建exchange交换器和队列queue：

• 新建exchange，命名为：canal-exchange
• 新建queue，命名为：canal-queue
• 绑定exchange和queue，routing-key设置为：canal-routing-key，这里对应上面instance.properties的canal.mq.topic

顺带一提，上面这段可以忽略，因为在SpringBoot的RabbitMQ配置中，会自动创建交换器exchange和队列queue，不过手动创建的话，可以在忽略SpringBoot的基础上，直接在RabbitMQ的管理页面上看到修改记录的消息。

SpringBoot整合RabbitMQ

依赖：

<amqp.version>2.3.4.RELEASE</amqp.version>
​
<!--消息队列-->
<dependency>
  <groupId>org.springframework.boot</groupId>
  <artifactId>spring-boot-starter-amqp</artifactId>
  <version>${amqp.version}</version>
</dependency>

application.yml：

spring:
  rabbitmq:
    #    host: myserverhost
    host: 192.168.0.108
    port: 5672
    username: admin
    password: RabbitMQ密码
    # 消息确认配置项
    # 确认消息已发送到交换机(Exchange)
    publisher-confirm-type: correlated
    # 确认消息已发送到队列(Queue)
    publisher-returns: true

RabbitMQ配置类：

@Configuration
public class RabbitConfig {
    @Bean
    public RabbitTemplate rabbitTemplate(ConnectionFactory connectionFactory) {
        RabbitTemplate template = new RabbitTemplate();
        template.setConnectionFactory(connectionFactory);
        template.setMessageConverter(new Jackson2JsonMessageConverter());
​
        return template;
    }
​
    /**
     * template.setMessageConverter(new Jackson2JsonMessageConverter());
     * 这段和上面这行代码解决RabbitListener循环报错的问题
     */
    @Bean
    public SimpleRabbitListenerContainerFactory rabbitListenerContainerFactory(ConnectionFactory connectionFactory) {
        SimpleRabbitListenerContainerFactory factory = new SimpleRabbitListenerContainerFactory();
        factory.setConnectionFactory(connectionFactory);
        factory.setMessageConverter(new Jackson2JsonMessageConverter());
        return factory;
    }
}

Canal消息生产者：

public static final String CanalQueue = "canal-queue";
public static final String CanalExchange = "canal-exchange";
public static final String CanalRouting = "canal-routing-key";
/**
 * Canal消息提供者，canal-server生产的消息通过RabbitMQ消息队列发送
 */
@Configuration
public class CanalProvider {
    /**
     * 队列
     */
    @Bean
    public Queue canalQueue() {
        /**
         * durable:是否持久化，默认false，持久化队列：会被存储在磁盘上，当消息代理重启时仍然存在；暂存队列：当前连接有效
         * exclusive:默认为false，只能被当前创建的连接使用，而且当连接关闭后队列即被删除。此参考优先级高于durable
         * autoDelete:是否自动删除，当没有生产者或者消费者使用此队列，该队列会自动删除
         */
        return new Queue(RabbitConstant.CanalQueue, true);
    }
​
    /**
     * 交换机，这里使用直连交换机
     */
    @Bean
    DirectExchange canalExchange() {
        return new DirectExchange(RabbitConstant.CanalExchange, true, false);
    }
​
    /**
     * 绑定交换机和队列，并设置匹配键
     */
    @Bean
    Binding bindingCanal() {
        return BindingBuilder.bind(canalQueue()).to(canalExchange()).with(RabbitConstant.CanalRouting);
    }
}

Canal消息消费者：

/**
 * Canal消息消费者
 */
@Component
@RabbitListener(queues = RabbitConstant.CanalQueue)
public class CanalComsumer {
    private final SysBackupService sysBackupService;
​
    public CanalComsumer(SysBackupService sysBackupService) {
        this.sysBackupService = sysBackupService;
    }
​
    @RabbitHandler
    public void process(Map<String, Object> msg) {
        System.out.println("收到canal消息：" + msg);
        boolean isDdl = (boolean) msg.get("isDdl");
​
        // 不处理DDL事件
        if (isDdl) {
            return;
        }
​
        // TiCDC的id，应该具有唯一性，先保存再说
        int tid = (int) msg.get("id");
        // TiCDC生成该消息的时间戳，13位毫秒级
        long ts = (long) msg.get("ts");
        // 数据库
        String database = (String) msg.get("database");
        // 表
        String table = (String) msg.get("table");
        // 类型：INSERT/UPDATE/DELETE
        String type = (String) msg.get("type");
        // 每一列的数据值
        List<?> data = (List<?>) msg.get("data");
        // 仅当type为UPDATE时才有值，记录每一列的名字和UPDATE之前的数据值
        List<?> old = (List<?>) msg.get("old");
​
        // 跳过sys_backup，防止无限循环
        if ("sys_backup".equalsIgnoreCase(table)) {
            return;
        }
​
        // 只处理指定类型
        if (!"INSERT".equalsIgnoreCase(type)
                && !"UPDATE".equalsIgnoreCase(type)
                && !"DELETE".equalsIgnoreCase(type)) {
            return;
        }
    }
}

测试一下，修改MySQL中的一条消息，Canal就会发送信息到RabbitMQ，我们就能从监听的RabbitMQ队列中得到该条消息。