使用canal实现增量同步MySQL的数据
搭建环境
- 操作系统： CentOS release 6.5 (Final)
- MySQL版本： 10.0.33-MariaDB-wsrep
- JDK版本：1.8（强力要求，否则会导致ES和canal-adapter无法启动）
- ElasticSearch版本：6.8.0
- canal版本： 1.1.3
- zookeeper
技术方案概览
- 开启MySQL的binary log日志记录
- 修改MySQL的binary log模式为
ROW - canal-server充当MySQL集群的一个slave，获取master的binary log信息
- canal-server将拿到的binary log信息推送给canal-adapter
- canal-server和canal-adapter采用多节点部署的方式提高可用性
- canal-adapter将数据同步到es集群
MySQL配置
- 开启master的binary log记录功能，并且选择模式为ROW
log-bin=mysql-bin #添加这一行就ok
binlog-format=ROW #选择row模式
server_id=1 #配置mysql replaction需要定义，不能和canal的slaveId重复
- canal的原理是模拟自己为mysql slave，所以这里一定需要做为mysql slave的相关权限.
CREATE USER canal IDENTIFIED BY 'canal';
GRANT SELECT, REPLICATION SLAVE, REPLICATION CLIENT ON *.* TO 'canal'@'%';
-- GRANT ALL PRIVILEGES ON *.* TO 'canal'@'%' ;
FLUSH PRIVILEGES;
ES安装
下载安装包
- 进入到Elasticsearch的官网下载页面
https://www.elastic.co/cn/downloads/elasticsearch
-
如果不想安装最新版本，可以选择历史版本
-
本次安装版本号选用6.8.0
- 下载安装包
wget https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-6.8.0.tar.gz
新增系统用户
- 由于elasticsearch不能使用root用户启动，所以我们创建一个新的用户
# 新建用户
adduser es
# 给新用户添加密码
passwd es
# 切换登陆用户
su es
- 将安装包copy到路径
/home/es/elasticsearch下
mv elasticsearch-6.8.0.tar.gz /home/es/elasticsearch
解压安装包
cd /home/es/elasticsearch
tar -xzvf elasticsearch-6.8.0.tar.gz
修改配置文件
vi config/elasticsearch.yml
#集群的名称，同一个集群该值必须设置成相同的
cluster.name: okami-application
#该节点的名字
node.name: node-1
#该节点有机会成为master节点
node.master: true
#该节点可以存储数据
node.data: true
#shard的数目
#index.number_of_shards: 5
#数据副本的数目
#index.number_of_replicas: 3
#设置绑定的IP地址，可以是IPV4或者IPV6
network.bind_host: 0.0.0.0
#设置其他节点与该节点交互的IP地址
network.publish_host: 192.168.10.1
#该参数用于同时设置bind_host和publish_host
network.host: 192.168.10.1
#设置节点之间交互的端口号
transport.tcp.port: 9300
#设置是否压缩tcp上交互传输的数据
transport.tcp.compress: true
#设置对外服务的http端口号
http.port: 9200
#设置http内容的最大大小
http.max_content_length: 100mb
#是否开启http服务对外提供服务
http.enabled: true
#设置这个参数来保证集群中的节点可以知道其它N个有master资格的节点。默认为1，对于大的集群来说，可以设置大一点的值（2-4）
discovery.zen.minimum_master_nodes: 1
#设置集群中自动发现其他节点时ping连接的超时时间
discovery.zen.ping_timeout: 120s
#设置是否打开多播发现节点
#discovery.zen.ping.multicast.enabled: true
#设置集群中的Master节点的初始列表，可以通过这些节点来自动发现其他新加入集群的节点
discovery.zen.ping.unicast.hosts: ["192.168.10.1:9300"]
path.data: /usr/hdp/2.5.0.0-1245/esdata
path.logs: /usr/hdp/2.5.0.0-1245/eslog
http.cors.enabled: true
http.cors.allow-origin: "*"
#--------------------------------------------------------------------------------
#index.analysis.analyzer.ik.type: "ik"
启动ES
- ES要求Java版本至少1.8，所以要检查Java版本,如果版本过低的话需要更新
[es@xxx elasticsearch-7.1.1]# java -version
java version "1.8.0_172"
Java(TM) SE Runtime Environment (build 1.8.0_172-b11)
Java HotSpot(TM) 64-Bit Server VM (build 25.172-b11, mixed mode)
- 启动ES(添加参数-d，后台启动)
./home/es/elasticsearch/elasticsearch-6.8.0/bin/elasticsearch -d
- 检查ES节点是否部署成功
[es@xxx ~]# curl http://127.0.0.1:9200
{
"name" : "node-1",
"cluster_name" : "okami-application",
"cluster_uuid" : "Q00-w01oQT6vsXx7E6KIeA",
"version" : {
"number" : "6.8.0",
"build_flavor" : "default",
"build_type" : "tar",
"build_hash" : "65b6179",
"build_date" : "2019-05-15T20:06:13.172855Z",
"build_snapshot" : false,
"lucene_version" : "7.7.0",
"minimum_wire_compatibility_version" : "5.6.0",
"minimum_index_compatibility_version" : "5.0.0"
},
"tagline" : "You Know, for Search"
}
安装部署其他主机
- 在同一个局域网段内的其他主机按照以上步骤安装部署ES
检查集群的部署情况
[es@xxx ~]# curl http://127.0.0.1:9200/_cluster/health
{"cluster_name":"okami-application","status":"green","timed_out":false,"number_of_nodes":3,"number_of_data_nodes":3,"active_primary_shards":0,"active_shards":0,"relocating_shards":0,"initializing_shards":0,"unassigned_shards":0,"delayed_unassigned_shards":0,"number_of_pending_tasks":0,"number_of_in_flight_fetch":0,"task_max_waiting_in_queue_millis":0,"active_shards_percent_as_number":100.0}
安装中遇到的问题
-
- max file descriptors [4096] for elasticsearch process is too low, increase to at least [65536]
- 每个进程最大同时打开文件数太小，可通过下面2个命令查看当前数量
ulimit -Hn ulimit -Sn- 修改/etc/security/limits.conf文件，增加配置，用户退出后重新登录生效
* soft nofile 65536 * hard nofile 65536
-
- max number of threads [3818] for user [es] is too low, increase to at least [4096]
- 问题同上，最大线程个数太低。修改配置文件/etc/security/limits.conf，增加配置
可通过命令查看* soft nproc 4096 * hard nproc 4096ulimit -Hu ulimit -Su
-
- max virtual memory areas vm.max_map_count [65530] is too low, increase to at least [262144]
- 修改/etc/sysctl.conf文件，增加配置vm.max_map_count=262144
vi /etc/sysctl.conf sysctl -p
- max virtual memory areas vm.max_map_count [65530] is too low, increase to at least [262144]
canal-server的安装
下载canal
- （可以直接下载安装包，也可以下载源码自己打包，我们采用直接下载的方式）, 已下载的话直接拷贝到安装目录即可
wget https://github.com/alibaba/canal/releases/download/canal-1.1.3/canal.deployer-1.1.3.tar.gz
- 将下载好的文件移动到自定义的安装路径
mv canal.deployer-1.1.3.tar.gz /opt/app/canal
解压
tar zxvf canal.deployer-1.1.3.tar.gz
修改配置文件
- vi /opt/app/canal/canal_server/conf/canal.properties
canal.id = 1 # 每个canal server实例的唯一标识，暂无实际意义
canal.ip = 192.111.112.103 # canal server绑定的本地IP信息，如果不配置，默认选择一个本机IP进行启动服务
canal.port = 11111 # canal server提供socket服务的端口
canal.metrics.pull.port = 11112
canal.zkServers = 192.168.1.111:2181 #canal server链接zookeeper集群的链接信息
# flush data to zk
canal.zookeeper.flush.period = 1000 #canal持久化数据到zookeeper上的更新频率，单位毫秒
canal.withoutNetty = false
# tcp, kafka, RocketMQ
canal.serverMode = tcp
# 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 = false
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 = password
# 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_01,example_02 # 当前server上部署的instance列表
# 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 # 全局配置加载方式
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 = 127.0.0.1:6667
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
# use transaction for kafka flatMessage batch produce
canal.mq.transaction = false
#canal.mq.properties. =
- 配置多个destination， 需要在conf下创建对应的目录
mkdir conf/example_01
mkdir conf/example_02
- 在对应的目录下边编写配置文件
instance.properties
canal.instance.mysql.slaveId=99
canal.instance.gtidon=false
# position info
canal.instance.master.address=
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=false
# username/password
canal.instance.dbUsername=username
canal.instance.dbPassword=password
canal.instance.defaultDatabaseName=dbName
canal.instance.connectionCharset = UTF-8
# enable druid Decrypt database password
canal.instance.enableDruid=false
# table regex
canal.instance.filter.regex=.*\\..*
# 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,.*\\..*
配置说明
mysql链接时的起始位置
canal.instance.master.journal.name + canal.instance.master.position : 精确指定一个binlog位点，进行启动
canal.instance.master.timestamp : 指定一个时间戳，canal会自动遍历mysql binlog，找到对应时间戳的binlog位点后，进行启动
不指定任何信息：默认从当前数据库的位点，进行启动
-
instance.xml配置文件
- memory-instance.xml： 所有的组件(parser , sink , store)都选择了内存版模式，记录位点的都选择了memory模式，重启后又会回到初始位点进行解析
- default-instance.xml： store选择了内存模式，其余的parser/sink依赖的位点管理选择了持久化模式，目前持久化的方式主要是写入zookeeper，保证数据集群共享.
- group-instance.xml： 主要针对需要进行多库合并时，可以将多个物理instance合并为一个逻辑instance，提供客户端访问
-
多个destination配置
- 在canal.properties里边配置
canal.destinations, 用英文逗号分隔 - 在conf路径下创建对应的路径并添加对应的instance.properties
- 在canal.properties里边配置
canal.instance.filter.regex的编写规则
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)
启动
-
进入到路径bin下边，有几个脚本
canal.pid # 记录服务的进程ID restart.sh # 重启服务 startup.sh # 启动脚本 stop.sh # 停止服务 运行
./startup.sh就可以启动了
查看日志
服务启动日志（logs/canal/canal.log)
实例运行日志 (logs/example/example.log)
canal-adapter的安装
下载安装包
wget https://github.com/alibaba/canal/releases/download/canal-1.1.3/canal.adapter-1.1.3.tar.gz
解压
tar xzvf canal.adapter-1.1.3.tar.gz
修改配置文件
- 修改conf/application.yml
server:
port: 8081
spring:
jackson:
date-format: yyyy-MM-dd HH:mm:ss
time-zone: GMT+8
default-property-inclusion: non_null
canal.conf:
mode: tcp
zookeeperHosts: 192.111.111.173:2181
# mqServers: 127.0.0.1:9092 #or rocketmq
# flatMessage: true
batchSize: 500
syncBatchSize: 1000
retries: 0
timeout:
accessKey:
secretKey:
srcDataSources:
defaultDS:
url: jdbc:mysql://192.168.1.100:3306/test?useUnicode=true
username: username
password: password
defaultDS2:
url: jdbc:mysql://192.168.1.101:3306/test?useUnicode=true
username: username
password: password
canalAdapters:
- instance: example_01
groups:
- groupId: g1
outerAdapters:
- name: logger
- name: es
hosts: 192.168.1.110:9300
properties:
cluster.name: okami-application
- instance: example_02
groups:
- groupId: g1
outerAdapters:
- name: logger
- name: es
hosts: 192.168.1.111:9300
properties:
cluster.name: okami-application
- 在conf/es/路径下添加配置文件example_01.yml 和 example_02.yml
vi conf/es/example_01.yml
dataSourceKey: defaultDS
destination: example_01
groupId: g1
esMapping:
_index: indexName
_type: typeName
_id: _id
upsert: true
# pk: id
sql: "select a.id as _id, a.name as _name, a.role_id as _role_id, b.role_name as _role_name,
a.c_time as _c_time from user a
left join role b on b.id=a.role_id"
# objFields:
# _labels: array:;
# etlCondition: "where a.c_time>='{0}'"
commitBatch: 3000
vi conf/es/example_02.yml
dataSourceKey: defaultDS2
destination: example_02
groupId: g1
esMapping:
_index: indexName
_type: typeName
_id: _id
upsert: true
# pk: id
sql: "select a.id as _id, a.name as _name, a.role_id as _role_id, b.role_name as _role_name,
a.c_time as _c_time from user a
left join role b on b.id=a.role_id"
# objFields:
# _labels: array:;
# etlCondition: "where a.c_time>='{0}'"
commitBatch: 3000
配置说明
- 一份数据可以被多个group同时消费, 多个group之间会是一个并行执行, 一个group内部是一个串行执行多个outerAdapters
启动
-
进入到路径bin下边，有几个脚本
canal.pid # 记录服务的进程ID restart.sh # 重启服务 startup.sh # 启动脚本 stop.sh # 停止服务 运行
./startup.sh就可以启动了
查看日志
tail -f logs/adapter/adapter.log
通过Http请求管理
-
查询所有订阅同步的canal instance：
http://112.33.11.124:8081/destinations
[
{
"destination": "example_01",
"status": "on"
},
{
"destination": "example_02",
"status": "on"
}
]
-
数据同步开关状态:
http://112.33.11.124:8081/syncSwitch/example_02
{
"stauts": "off"
}
-
数据同步开关
http://112.33.11.124:8081/syncSwitch/example_01/on PUT
{
"code": 20000,
"message": "实例: example_01 开启同步成功"
}