如何使用Canal同步MySQL的Binlog到Kafka
如何使用Canal同步MySQL的Binlog到Kafka
Eights
发布于 2020-09-10 15:15:17
发布于 2020-09-10 15:15:17
本篇文章大概5525字，阅读时间大约15分钟
Canal是阿里开源的增量解析MySQL binlog组件。通过将binlog投递到kafka，一方面可以直接进行指标计算。另一方面，可以减轻夜间离线数仓数据同步的压力。本文基于canal-1.1.4版本进行binlog解析和投递到kafka功能测试
1
主要内容
- 记录canal-1.1.4集群搭建
- 摄取mysql的binlog发送到kafka
集群环境
- centos7.4
- canal-1.1.4
- mysql-5.6
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Canal集群搭建
需求背景
业务需要做关于控车指令失败的告警及多维统计，需要增量订阅mysql业务表的binlog，投递到kafka，最后采用Flink引擎进行实时指标计算
组件介绍
canal是一个增量解析MySQL binlog日志解析，提供增量数据订阅和消费的组件。
官方github
https://github.com/alibaba/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canal
- canal解析binary log
版本选择
cancal-1.1.4版本，引入了canal-admin，有了Web UI，便于对canal进行动态管理，支持配置、任务、日志等运维能力
集群搭建
集群规划
Canal | utility1 | utility2 | utility3 |
|---|---|---|---|
admin | √ | ||
server | √ | √ | √ |
下载地址
https://github.com/alibaba/canal/releases
canal-admin部署
# 建立canal目录
mkdir -p /opt/canal
# 解压
tar -zxvf canal.admin-1.1.4.tar.gz -C /opt/canal/
# 修改配置
主要是元数据存放的mysql和canal admin的用户名
# 初始化元数据库
在数据库中运行 conf/canal_manager.sql
# 运行/bin/startup.sh启动 - 登陆 admin - 123456
- 查看启动日志
- 访问端口8089进入canal-admin界面
- 新建集群，输入集群名称和ZK地址
- 载入Carbond集群的主配置，保存，这一步一定要做，否则canal-server启动不成功
canal-server部署
# 建立canal目录
mkdir -p /opt/canal-server
# 解压
tar -zxvf canal.deployer-1.1.4.tar.gz -C /opt/canal-server- 配置canal_local.properties
# register ip
canal.register.ip =
# canal admin config
canal.admin.manager = ip:8089
canal.admin.port = 11110
canal.admin.user = admin
canal.admin.passwd = xxxx
# admin auto register
canal.admin.register.auto = true
canal.admin.register.cluster = true- 启动server，在canal-admin页面上可以看到server
sh startup.sh local
集群主配置修改
- 这里主要注意canal.zkServers和MQ的配置
#################################################
######### 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
# 这里需要注意！！！
canal.zkServers = 10.64.xx.xx:2181,10.64.xx.xx:2181,10.64.xx.xx:2181
# flush data to zk
canal.zookeeper.flush.period = 1000
canal.withoutNetty = false
# 这里需要改成kafka
# tcp, kafka, RocketMQ
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
# 这里选择把dml过滤掉，这部分不需要
# false可能会报错，参考：https://blog.csdn.net/ashic/article/details/104722999
canal.instance.filter.query.dml = true
canal.instance.filter.query.ddl = false
canal.instance.filter.table.error = false
canal.instance.filter.rows = false
canal.instance.filter.transaction.entry = 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
# aliyun ak/sk , support rds/mq
canal.aliyun.accessKey =
canal.aliyun.secretKey =
#################################################
######### destinations #############
#################################################
canal.destinations =
# 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
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 = manager
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
# 这里需要填上kafka的相关配置
##################################################
######### MQ #############
##################################################
canal.mq.servers = dn21.eights.com:9092,dn22.eights.com:9092,dn23.eights.com:9092
canal.mq.retries = 0
canal.mq.batchSize = 16384
canal.mq.maxRequestSize = 1048576
canal.mq.lingerMs = 100
canal.mq.bufferMemory = 33554432
canal.mq.canalBatchSize = 50
canal.mq.canalGetTimeout = 100
canal.mq.flatMessage = true
canal.mq.compressionType = none
canal.mq.acks = all
#canal.mq.properties. =
canal.mq.producerGroup = canal-prod
# Set this value to "cloud", if you want open message trace feature in aliyun.
# canal.mq.accessChannel = local
# aliyun mq namespace
#canal.mq.namespace =
##################################################
######### Kafka Kerberos Info #############
##################################################
canal.mq.kafka.kerberos.enable = false
canal.mq.kafka.kerberos.krb5FilePath = "../conf/kerberos/krb5.conf"
canal.mq.kafka.kerberos.jaasFilePath = "../conf/kerberos/jaas.conf"新建实例
- 修改实例配置
- 这里需要注意的是配置同步的库表，目前做测试，接入4张表
- mq config中需要把canal.mq.topic和canal.mq.dynamicTopic都配上，动态topic没匹配上的进入默认topic
下面给出instance的配置
#################################################
## 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=10.64.xx.xx: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=mysql的用户名-同步binlog账号
canal.instance.dbPassword=mysql的密码-同步binlog账号
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=carbond.log_sms_sended_task,carbond.si_sim_info,carbond.global_user_car,carbond.core_terminal_device
# table black regex
canal.instance.filter.black.regex=
# 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
# 配置一个默认topic
# mq config
canal.mq.topic=carbond_binlog_default_227
# 配置动态topic,指定哪个表进入哪个分区
# dynamic topic route by schema or table regex
canal.mq.dynamicTopic=carbond_log_sms_sended_task:carbond.log_sms_sended_task,carbond_si_sim_info:carbond.si_sim_info,carbond_global_user_car:carbond.global_user_car,carbond_core_terminal_device:carbond.core_terminal_device
canal.mq.partition=0
# hash partition config
#canal.mq.partitionsNum=3
#canal.mq.partitionHash=test.table:id^name,.*\\..*
#################################################3
功能测试
- 启动instance，观察到kafka的topic中是否有数据
- 注意如果kafka关闭了自动创建topic，需要先把topic建好
- kafka的topic中已经有数据写入，binlog投递到kafka完成
4
总结
采用Binlog抓取，关系库数据同步方式-CDC，一方面可以将dump出来的binlog进行实时计算，做指标。另一方面，解耦离线数仓的关系库抽数层ods，减轻夜间抽数时业务库的压力。Canal可以胜任这个场景，并且1.1.4版本提供了WebUI做集群管理，值得一试~
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原始发表：2020-09-04，如有侵权请联系 cloudcommunity@tencent.com 删除
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