canal-admin1.1.14界面化安装配置canal集群详解
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2022-06-16 08:37:38
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安装准备
虚拟机服务器四台
192.168.23.128 (主机名mysql)
192.168.23.132 (主机名spark01)
192.168.23.133 (主机名spark02)
192.168.23.134 (主机名spark03)
canal.admin-1.1.4.tar.gz
canal.deployer-1.1.4.tar.gz
下载地址 https://github.com/alibaba/canal/releases/tag/canal-1.1.4/
页面底端
自行安装
zk集群 （本demo—zk地址192.168.23.132:2181,192.168.23.133:2181,192.168.23.134:2181）
mysql5.7（本demo—mysql地址192.168.23.128:3306）
kafka集群（本demo—kafka地址192.168.23.132:9092,192.168.23.133:9092,192.168.23.134:9092）
安装canal-admin
1.创建文件夹canal_admin，将canal.admin-1.1.4.tar.gz解压到该目录
mkdir canal_admin
tar -zxvf canal.admin-1.1.4.tar.gz -C /export/servers/canal_admin
2.修改配置application.yml
cd /export/servers/canal_admin/conf
vim application.yml
server:
port: 8089
spring:
jackson:
date-format: yyyy-MM-dd HH:mm:ss
time-zone: GMT+8
spring.datasource:
address: 192.168.23.128:3306
database: canal_manager
username: root
password: 123456
driver-class-name: com.mysql.jdbc.Driver
url: jdbc:mysql://${spring.datasource.address}/${spring.datasource.database}?useUnicode=true&characterEncoding=UTF-8&useSSL=false
hikari:
maximum-pool-size: 30
minimum-idle: 1
canal:
adminUser: admin
adminPasswd: 123456
3.mysql操作
a. 编辑 mysql配置文件/etc/my.cnf
vim /etc/my.cnf
在mysqld标签下新增如下代码
# For advice on how to change settings please see
# http://dev.mysql.com/doc/refman/5.7/en/server-configuration-defaults.html
[mysqld]
lower_case_table_names=1
log-bin=mysql-bin # 开启 binlog
binlog-format=ROW # 选择 ROW 模式
server_id=1 # 配置 MySQL replaction 需要定义，不要和 canal 的 slaveId 重复
#
# Remove leading # and set to the amount of RAM for the most important data
# cache in MySQL. Start at 70% of total RAM for dedicated server, else 10%.
# innodb_buffer_pool_size = 128M
#
# Remove leading # to turn on a very important data integrity option: logging
# changes to the binary log between backups.
# log_bin
#
# Remove leading # to set options mainly useful for reporting servers.
# The server defaults are faster for transactions and fast SELECTs.
# Adjust sizes as needed, experiment to find the optimal values.
# join_buffer_size = 128M
# sort_buffer_size = 2M
# read_rnd_buffer_size = 2M
datadir=/var/lib/mysql
socket=/var/lib/mysql/mysql.sock
# Disabling symbolic-links is recommended to prevent assorted security risks
symbolic-links=0
log-error=/var/log/mysqld.log
pid-file=/var/run/mysqld/mysqld.pid
validate_password=off
#server_id = 1
#log-bin=mysql-bin
#binlog_format = ROW
#log_timestamps=SYSTEM
b. 执行/export/servers/canal_admin/conf下的sql语句
cat canal_manager.sql
进入mysql，copy sql文件里的所有sql，直接执行
c.创建一个同步用的数据库
CREATE USER canal IDENTIFIED BY ‘123456’;
GRANT SELECT, REPLICATION SLAVE, REPLICATION CLIENT ON . TO ‘canal’@’%’;
– GRANT ALL PRIVILEGES ON . TO ‘canal’@’%’ ;
FLUSH PRIVILEGES;
4.启动canal-admin
cd /export/servers/canal_admin/bin
sh startup.sh
5.浏览器输入192.168.23.132:8089,输入用户名admin，密码123456
a.点击集群管理，新建集群（集群名称：canal_cluster ; zkurl：192.168.23.132:2181,192.168.23.133:2181,192.168.23.134:2181）
b.选择编辑集群配置，下拉选择主配置
具体代码如***：此时canal.destinations参数不需要配置，后面会讲到何时配置）
#################################################
######### 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 = 192.168.23.132:8089
canal.admin.port = 11110
canal.admin.user = admin
canal.admin.passwd = 6BB4837EB74329105EE4568DDA7DC67ED2CA2AD9
canal.zkServers = 192.168.23.132:2181,192.168.23.133:2181,192.168.23.134:2181
# flush data to zk
canal.zookeeper.flush.period = 1000
canal.withoutNetty = false
# 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
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
# 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 = 123456
# 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
##################################################
######### MQ #############
##################################################
canal.mq.servers = 192.168.23.132:9092,192.168.23.133:9092,192.168.23.134:9092
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 = test
# 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"
安装canal服务端
1.创建文件夹canal，将canal.deployer-1.1.4.tar.gz解压到该目录
mkdir canal
tar -zxvf canal.deployer-1.1.4.tar.gz -C /export/servers/canal
2.将canal_local.properties文件内容覆盖到canal.properties，并编辑canal.properties
# register ip
canal.register.ip = 192.168.23.132
# canal admin config
canal.admin.manager = 192.168.23.132:8089
canal.admin.port = 11110
canal.admin.user = admin
canal.admin.passwd = 6BB4837EB74329105EE4568DDA7DC67ED2CA2AD9
# admin auto register
canal.admin.register.auto = true
canal.admin.register.cluster = canal_cluster
3.将canal文件夹发送到 另外2台机
scp -r canal aaa@qq.com: /export/servers
scp -r canal aaa@qq.com: /export/servers
并修改canal.properties中canal.register.ip参数为各自服务器ip，其余参数保持不变
spark02上 canal.register.ip = 192.168.23.133
spark03上 canal.register.ip = 192.168.23.134
4.分别启动三台服务器上的canal服务
cd /export/servers/canal/bin
sh startup.sh
5.刷新浏览器，点击server管理，发现已自动注入三个实例
创建实时同步任务
同步任务：将mysql下test数据库表t_szft_user数据实时同步到kafka中（kafka名称user_topic），前提需先创建好kafka中主题user_topic
kafka-topics --zookeeper spark01:2181 --topic user_topic --create --replication-factor 1 --partitions 3
1.点击instance管理，新建instance，输入instance名称user_topic，选择canal_cluster集群，点击后面的载入模板，并修改
#################################################
## 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=192.168.23.128:3306
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=root
canal.instance.dbPassword=123456
canal.instance.defaultDatabaseName = test
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=test\\.t_szft_user
# 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
# mq config
canal.mq.topic=user_topic
# 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.t_szft_user:Id
#################################################
2.配置集群管理中的canal.destinations参数（细心的童鞋可能会注意到编辑集群配置中主配置时，该参数是空的）
canal.destinations = user_topic
3.查看instance发现已正常启动
4.打开kafka实时消费
bin/kafka-console-consumer.sh --bootstrap-server spark01:9092 --topic user_topic
5.修改mysql表t_szft_user中任意数据，发现kafka控制台已打印出修改的数据，实时同步数据成功