SpringBoot整合Canal与RabbitMQ监听数据变更记录

2022-11-13 16:11:14 整合监听变更

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();
        }
    }

    
    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;
    }

    
    @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";


@Configuration
public class CanalProvider {
    
    @Bean
    public Queue canalQueue() {
        
        return new Queue(RabbitConstant.CanalQueue, true);
    }

    
    @Bean
    DirectExchange canalExchange() {
        return new DirectExchange(RabbitConstant.CanalExchange, true, false);
    }

    
    @Bean
    Binding bindingCanal() {
        return BindingBuilder.bind(canalQueue()).to(canalExchange()).with(RabbitConstant.CanalRouting);
    }
}

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。

到此这篇关于SpringBoot整合Canal与RabbitMQ监听数据变更记录的文章就介绍到这了,更多相关SpringBoot整合Canal 内容请搜索以前的文章或继续浏览下面的相关文章希望大家以后多多支持！

相关文章