canal+kafka实现数据库同步

canal实现数据库同步

1.1.1 canal的工作原理

• 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 (即 canal )
• canal 解析 binary log 对象(原始为 byte 流)

1.1.2 数据库设置

修改需要被同步的数据库 /etc/my.cfg配置，有则修改无则添加

[mysqld]
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
binlog-rows-query-log-events  = 1  #查看完整的sql语句

1.1.3 cannal的安装

下载地址：canal.deployer-1.1.3.tar.gz（目前最新版是v1.1.3）

注：

修改instance 配置文件 vi conf/example/instance.properties

# 数据库实例地址，主数据库
canal.instance.master.address=192.168.1.48:3306
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 数据库帐号密码
canal.instance.dbUsername=tradesrv
canal.instance.dbPassword=Qt!S!U3wkmuu97_I
canal.instance.connectionCharset = UTF-8
# enable druid Decrypt database password
canal.instance.enableDruid=false

修改canal 配置文件vi /usr/local/canal/conf/canal.properties

#################################################
#########               common argument         ############# 
#################################################
#canal.manager.jdbc.url=jdbc:mysql://127.0.0.1:3306/canal_manager?useUnicode=true&characterEncoding=UTF-8
#canal.manager.jdbc.username=root
#canal.manager.jdbc.password=121212
#canal server的唯一标识，没有实际意义，但是我们建议同一个cluster上的不同节点，其ID尽可能唯一
canal.id =150 
#此IP主要为canalServer提供TCP服务而使用，将会被注册到ZK中,Consumer将与此IP建立连接。
canal.ip =192.168.1.150
#cannal server的TCP端口
canal.port = 11111
canal.metrics.pull.port = 11112
#zookeeper地址，可集群
canal.zkServers =192.168.1.150:2181
# 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将parse、position数据写入的本地文件目录 
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 = 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            ############# 
#################################################
#同步多个数据库只需在后面添加对应的实例，并复制instance.properties到实例目录下即可
canal.destinations = example,example1
# 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 = 127.0.0.1:1099
#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 = 127.0.0.1:9092
canal.mq.retries = 0
canal.mq.batchSize = 16384
canal.mq.maxRequestSize = 1048576
canal.mq.lingerMs = 1
canal.mq.bufferMemory = 33554432
canal.mq.producerGroup = Canal-Producer
canal.mq.canalBatchSize = 30
canal.mq.canalGetTimeout = 100
canal.mq.flatMessage = true
canal.mq.compressionType = none
canal.mq.acks = all
# use transaction for kafka flatMessage batch produce
canal.mq.transaction = false
#canal.mq.properties. =

mq相关参数说明

参数名	参数说明	默认值
canal.mq.servers	kafka为bootstrap.servers rocketMQ中为nameserver列表	127.0.0.1:6667
canal.mq.retries	发送失败重试次数	0
canal.mq.batchSize	kafka为ProducerConfig.BATCH_SIZE_CONFIG rocketMQ无意义	16384
canal.mq.maxRequestSize	kafka为ProducerConfig.MAX_REQUEST_SIZE_CONFIG rocketMQ无意义	1048576
canal.mq.lingerMs	kafka为ProducerConfig.LINGER_MS_CONFIG , 如果是flatMessage格式建议将该值调大, 如: 200 rocketMQ无意义	1
canal.mq.bufferMemory	kafka为ProducerConfig.BUFFER_MEMORY_CONFIG rocketMQ无意义	33554432
canal.mq.producerGroup	kafka无意义 rocketMQ为ProducerGroup名	Canal-Producer
canal.mq.canalBatchSize	获取canal数据的批次大小	50
canal.mq.canalGetTimeout	获取canal数据的超时时间	100
canal.mq.flatMessage	是否为json格式 如果设置为false,对应MQ收到的消息为protobuf格式 需要通过CanalMessageDeserializer进行解码	true
canal.mq.transaction	kafka消息投递是否使用事务, 主要针对flatMessage的异步发送和动态多topic消息投递进行事务控制来保持和canal binlog position的一致性, flatMessage模式下建议开启(需要kafka版本支持)。如果设置为false, flatMessage消息将会采用逐条同步的方式投递, 可能会产生消息丢失或者重复投递 rocketMQ无意义	false
—	—	—
canal.mq.topic	mq里的topic名	无
canal.mq.dynamicTopic	mq里的动态topic规则, 1.1.3版本支持	无
canal.mq.partition	单队列模式的分区下标，	1
canal.mq.partitionsNum	散列模式的分区数	无
canal.mq.partitionHash	散列规则定义 库名.表名 : 唯一主键，比如mytest.person: id 1.1.3版本支持新语法，见下文	无

1.1.4 kafka安装

1下载压缩包, 复制到固定目录并解压

到官网下载压缩包

wget https://www.apache.org/dyn/closer.cgi?path=/kafka/1.1.1/kafka_2.11-1.1.1.tgz
mkdir  -p /usr/local/kafka
cp   kafka_2.11-1.1.1.tgz   /usr/local/kafka
tar -zxvf kafka_2.11-1.1.1.tgz

2 修改配置文件

vim /usr/local/kafka/kafka_2.11-1.1.1/config/server.properties 修改参数

zookeeper.connect=192.168.1.110:2181
listeners=PLAINTEXT://:9092
advertised.listeners=PLAINTEXT://192.168.1.117:9092 #本机ip
# ...

3 启动server

• start脚本

# bin/kafka-server-start.sh  -daemon  config/server.properties &

• 查看所有topic

# bin/kafka-topics.sh --list --zookeeper 192.168.1.110:2181

参考链接：https://kafka.apache.org/quickstart

1.1.5 kafka-manager可视化界面布署

下载：https://github.com/yahoo/kafka-manager/releases

1. 进入kafka-manager的解压目录,进入/bin文件夹,执行命令:

   ./sbt clean dist
   

2. 编译完成后, kafka-manager的解压目录下就会多了一个target文件夹, 我们的可执行程序就在target/universal/kafka-manager-xxx.zip里面

3. 解压这个kafka-manager-xxx.zip

4. 进入刚刚编译好的kafka-manager可执行程序的根目录下, 找到/conf/application.conf文件, 打开并修改:

   kafka-manager.zkhosts="localhost:2181"
   #注：kafka默认是9000端口，可在配置文件修改
   

5. 然后, 进入/bin目录, 执行:

   ./kafka-manager