SpringBoot整合Canal+RabbitMQ监听数据变更
canal
alibaba/canal: Canal 是由阿里巴巴开源的分布式数据库同步系统，主要用于实现MySQL数据库的日志解析和实时增量数据订阅与消费，广泛应用于数据库变更消息的捕获、数据迁移、缓存更新等场景。
项目地址：https://gitcode.com/gh_mirrors/ca/canal
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需求
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步骤
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环境搭建
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整合SpringBoot Canal实现客户端
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Canal整合RabbitMQ
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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
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Canal服务模式设为TCP，用Java编写客户端代码，监听MySQL的binlog修改
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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
#################################################
######## RabbitMQ ############
#################################################
rabbitmq.host = myrabbit
rabbitmq.virtual.host = /
rabbitmq.exchange = canal-exchange
rabbitmq.username = admin
rabbitmq.password = RabbitMQ密码
rabbitmq.deliveryMode =
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
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。
GitHub 加速计划 / ca / canal
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alibaba/canal: Canal 是由阿里巴巴开源的分布式数据库同步系统，主要用于实现MySQL数据库的日志解析和实时增量数据订阅与消费，广泛应用于数据库变更消息的捕获、数据迁移、缓存更新等场景。
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