Canal + Kafka 同步 MySQL 数据到 Redis

解决缓存和数据库一致性问题

一般来说，缓存中的数据没什么问题，但是数据库更新后，就容易出现缓存（Redis）和数据库（MySQL）间的数据一致性问题。由于写和读是并发的，没法保证顺序，就会出现缓存和数据库的数据不一致的问题

Canal工作原理
canal模拟mysql slave的交互协议，伪装自己为mysql slave，向mysql master发送dump协议
mysql master收到dump请求，开始推送binary log给slave(也就是canal)
canal解析binary log对象(原始为byte流)

可参考官方文档

QuickStart · alibaba/canal Wiki · GitHub

1、Kafka，ZK安装略，本博主其它文章有

安装好后，先启动ZK，在启动Kafka

2、win10编辑my.ini

[mysqld]
#开启 binlog
log-bin=mysql-bin
#选择 ROW 模式
binlog-format=ROW 
# 配置 MySQL replaction 需要定义，不要和 canal 的 slaveId 重复
server_id=1

开启授权
CREATE USER canal IDENTIFIED BY 'canal';  
GRANT SELECT, REPLICATION SLAVE, REPLICATION CLIENT ON *.* TO 'canal'@'%';
-- GRANT ALL PRIVILEGES ON *.* TO 'canal'@'%' ;
FLUSH PRIVILEGES;

3、下载canal

下载地址：Releases · alibaba/canal · GitHub

解压后会有5文件夹

进入conf

编辑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 = 127.0.0.1:8089
canal.admin.port = 11110
canal.admin.user = admin
canal.admin.passwd = 4ACFE3202A5FF5CF467898FC58AAB1D615029441
# admin auto register
#canal.admin.register.auto = true
#canal.admin.register.cluster =
#canal.admin.register.name =canal.zkServers =
# flush data to zk
canal.zookeeper.flush.period = 1000
canal.withoutNetty = false
# tcp, kafka, rocketMQ, rabbitMQ
canal.serverMode = kafka
# 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 = example
# 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 = falsecanal.instance.tsdb.spring.xml = classpath:spring/tsdb/h2-tsdb.xml
#canal.instance.tsdb.spring.xml = classpath:spring/tsdb/mysql-tsdb.xmlcanal.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 = localcanal.mq.database.hash = true
canal.mq.send.thread.size = 30
canal.mq.build.thread.size = 8##################################################
######### 		     Kafka 		     #############
##################################################
##kafka地址
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 = 0kafka.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 =
rabbitmq.virtual.host =
rabbitmq.exchange =
rabbitmq.username =
rabbitmq.password =
rabbitmq.deliveryMode =

进入canal\conf\example

编辑instance.properties

#################################################
## mysql serverId , v1.0.26+ will autoGen
# canal.instance.mysql.slaveId=0# enable gtid use true/false
canal.instance.gtidon=false# position info
canal.instance.master.address=127.0.0.1:3306
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 这里是你的数据库
canal.instance.dbUsername=root
canal.instance.dbPassword=12345678
canal.instance.connectionCharset = UTF-8
# enable druid Decrypt database password
canal.instance.enableDruid=false
#canal.instance.pwdPublicKey=MFwwDQYJKoZIhvcNAQEBBQADSwAwSAJBALK4BUxdDltRRE5/zXpVEVPUgunvscYFtEip3pmLlhrWpacX7y7GCMo2/JM6LeHmiiNdH1FWgGCpUfircSwlWKUCAwEAAQ==# table regex 这里是你要监听的表，多个用，隔开
canal.instance.filter.regex=test.user
# 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 这里是你要用哪个topic监听
canal.mq.topic=myTestTopic
# dynamic topic route by schema or table regex
#canal.mq.dynamicTopic=mytest1.user,mytest2\\..*,.*\\..*
canal.mq.partition=0
# hash partition config
#canal.mq.partitionsNum=3
#canal.mq.partitionHash=test.table:id^name,.*\\..*
#canal.mq.dynamicTopicPartitionNum=test.*:4,mycanal:6
#################################################

启动canal

双击bin目录的 startup.bat

4、在pom.xml引入Kafka、canal的依赖

<dependency><groupId>org.springframework.kafka</groupId><artifactId>spring-kafka</artifactId>
</dependency>
<dependency><groupId>org.springframework.kafka</groupId><artifactId>spring-kafka-test</artifactId><scope>test</scope>
</dependency>
<dependency><groupId>com.alibaba.otter</groupId><artifactId>canal.client</artifactId><version>1.1.4</version>
</dependency>

yml添加Kafka的配置

  kafka:#kafka配置bootstrap-servers: 127.0.0.1:9092producer: #生产者retries: 3 #设置大于0的值，则客户端会将发送失败的记录重新发送的次数# 每次批量发送消息的数量batch-size: 16384buffer-memory: 33554432# 指定消息key和消息体的编解码方式key-serializer: org.apache.kafka.common.serialization.StringSerializervalue-serializer: org.apache.kafka.common.serialization.StringSerializeracks: -1consumer:# 指定默认消费者group idgroup-id: my-consumer-groupauto-offset-reset: earliestenable-auto-commit: falseauto-commit-interval: 5000# 指定消息key和消息体的编解码方式key-deserializer: org.apache.kafka.common.serialization.StringDeserializervalue-deserializer: org.apache.kafka.common.serialization.StringDeserializerlistener:ack-mode: manual_immediate

5、定义消费者


import com.fan.li.myspringboot.util.RedisClient;
import lombok.extern.slf4j.Slf4j;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.kafka.support.Acknowledgment;
import org.springframework.stereotype.Component;/*** @ClassName CanalConsumer* @Description TODO* @Author fan* @Date 2024/2/23 14:11* @Version 1.0*/
@Component
@Slf4j
public class CanalConsumer {@AutowiredRedisClient redisClient;//redis工具类，自己封装即可@KafkaListener(topics = "myTestTopic", groupId = "canalKafka-groupId")public void canalListenerKafkaToRedis(ConsumerRecord<String, String> record, Acknowledgment ack) {//数据表变动的值String value = record.value();log.info("数据表发生变动:{}", value);//简单存入redisredisClient.setKey("你的key",value);//手动提交ack.acknowledge();}
}