Canal1.1.4获取数据后直接发送到kafka的Topic

Canal修改配置文件

在原有Canal已经启动运行成功的情况下，

停掉服务，找到这个配置文件中对应项进行修改：

第一个配置文件

vim /opt/canal/conf/canal.properties

# 配置zk
canal.zkServers = hadoop1:2181,hadoop2:2181,hadoop3:2181

# 设置成row
canal.instance.binlog.format = ROW

# 可选项: tcp(默认), kafka, RocketMQ
canal.serverMode = kafka

# 填写你的kafka地址和端口，可以不用都写
canal.mq.servers = hadoop1:9092,hadoop2:9092,hadoop3:9092

# 配置你的mysql地址，数据库的名称不用改，它默认全是这个名字，刚开始改名了，后来嫌麻烦改回来了
# 涉及到配置账号密码的都设置好别漏掉一个
canal.instance.tsdb.url = jdbc:mysql://hadoop1:3306/canal_tsdb
canal.instance.tsdb.dbUsername = canal
canal.instance.tsdb.dbPassword = 123456

#这里要配置成mysql的，不变的话链接mysql会报 java.sql.SQLExceptionjava.sql.SQL：driverClass org.h2.Driver
# canal.instance.tsdb.spring.xml = classpath:spring/tsdb/h2-tsdb.xml
  canal.instance.tsdb.spring.xml = classpath:spring/tsdb/mysql-tsdb.xml

第二个配置文件

vim /opt/canal/conf/example/instance.properties

# 配置mysql
canal.instance.tsdb.url=jdbc:mysql://hadoop1:3306/canal_tsdb
canal.instance.tsdb.dbUsername=canal
canal.instance.tsdb.dbPassword=123456

# 配置过滤，可以在这里指定表和库，只获取他们的binlog
canal.instance.filter.regex=.*\\..*

# 配置多topic，在这里可以指定你的数据放kafka的哪个topic，还可以自己指定topic的名称，不存在的topic会自动创建
canal.mq.dynamicTopic=exercise_topic:exercise\\.user,exercise_topic2:exercise2\\.user2

上面配置文件中的特殊参数配置说明可以在下面进行查看

conf/example/instance.properties配置文件中的canal.instance.filter.regex= 属性：

mysql 数据解析关注的表，Perl正则表达式.多个正则之间以逗号(,)分隔，转义符需要双斜杠(\)
常见例子：

1. 所有表：.* or .\…
2. canal schema下所有表： canal\…*
3. canal下的以canal打头的表：canal\.canal.*
4. canal schema下的一张表：canal.test1
5. 多个规则组合使用：canal\…*,mysql.test1,mysql.test2 (逗号分隔)
   注意：此过滤条件只针对row模式的数据有效(ps. mixed/statement因为不解析sql，所以无法准确提取tableName进行过滤)

conf/example/instance.properties配置文件的canal.mq.dynamicTopic 表达式说明：

canal 1.1.3版本之后, 支持配置格式：schema 或 schema.table，多个配置之间使用逗号或分号分隔：

• 例子1：test.test 指定匹配的单表，发送到以test_test为名字的topic上
• 例子2：… 匹配所有表，则每个表都会发送到各自表名的topic上
• 例子3：test 指定匹配对应的库，一个库的所有表都会发送到库名的topic上
• 例子4：test.* 指定匹配的表达式，针对匹配的表会发送到各自表名的topic上
• 例子5：test,test1.test1，指定多个表达式，会将test库的表都发送到test的topic上，test1.test1的表发送到对应的test1_test1 topic上，其余的表发送到默认的canal.mq.topic值
  为满足更大的灵活性，允许对匹配条件的规则指定发送的topic名字，配置格式：topicName:schema 或 topicName:schema.table：
• 例子1: test:test.test 指定匹配的单表，发送到以test为名字的topic上
• 例子2: test:… 匹配所有表，因为有指定topic，则每个表都会发送到test的topic下
• 例子3: test:test 指定匹配对应的库，一个库的所有表都会发送到test的topic下
• 例子4：testA:test.* 指定匹配的表达式，针对匹配的表会发送到testA的topic下
• 例子5：test0:test,test1:test1.test1，指定多个表达式，会将test库的表都发送到test0的topic下，test1.test1的表发送到对应的test1的topic下，其余的表发送到默认的canal.mq.topic值

conf/example/instance.properties配置文件的canal.mq.partitionHash 表达式说明：
canal 1.1.3版本之后, 支持配置格式：schema.table:pk1^pk2，多个配置之间使用逗号分隔：

• 例子1：test.test:pk1^pk2 指定匹配的单表，对应的hash字段为pk1 + pk2
• 例子2：…:id 正则匹配，指定所有正则匹配的表对应的hash字段为id
• 例子3：…:pk 正则匹配，指定所有正则匹配的表对应的hash字段为表主键(自动查找)
• 例子4: 匹配规则啥都不写，则默认发到0这个partition上
• 例子5：… ，不指定pk信息的正则匹配，将所有正则匹配的表,对应的hash字段为表名。按表hash: 一张表的所有数据可以发到同一个分区，不同表之间会做散列 (会有热点表分区过大问题)
• 例子6: test.test:id,…* , 针对test的表按照id散列,其余的表按照table散列
• 注意：设置匹配规则，多条匹配规则之间是按照顺序进行匹配(命中一条规则就返回)

启动Canal

配置完成，启动canal，然后查看日志

tail -10 logs/canal/canal.log

tail -10 logs/example/example.log

没有报错信息，启动成功！

查看kafka的topic列表

kafka-topics --list --bootstrap-server hadoop1:9092,hadoop2:9092,hadoop3:9092

没有我要的发数据的topic

打开mysql执行一句delete或者insert
再次查看kafka的topics，发现已经生成了topic
进行消费数据

kafka-console-consumer --bootstrap-server hadoop1:9092,hadoop2:9092,hadoop3:9092 --from-beginning --topic exercise_topic

可以看到消费到了数据

配置好用好这个就不用写canal客户端代码了
到这里就完成了，如果有什么没有表述清楚，可以告知，会改。

下面是我整体的配置文件

canal.properties 整体配置文件：

#################################################
######### 		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

canal.zkServers = hadoop1:2181,hadoop2:2181,hadoop3:2181
# flush data to zk
canal.zookeeper.flush.period = 1000
canal.withoutNetty = false
# tcp, kafka, RocketMQ
# canal.serverMode = tcp
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.format = ROW 
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 = 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

#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 		     #############
##################################################
canal.mq.servers = hadoop1:9092,hadoop2:9092,hadoop3:9092
canal.mq.retries = 2
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"

instance.properties 整体配置文件：

#################################################
## 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=hadoop1:3306
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.tsdb.url=jdbc:mysql://hadoop1:3306/canal_tsdb
canal.instance.tsdb.dbUsername=canal
canal.instance.tsdb.dbPassword=123456

#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=123456
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=.*\\..*
canal.instance.filter.regex=exercise.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
# mq config
canal.mq.topic=example
# 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,.*\\..*
#################################################