SpringBoot整合Canal+RabbitMQ监听数据变更
-
需求
-
步骤
-
环境搭建
-
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 #
## 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。