How to use SpringBoot+Canal to implement real-time database monitoring
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 slave(也就是 Canal)
Canal 解析 binary log 对象(原始为 byte 流)
MySQL 打开 binlog 模式
在 MySQL 配置文件 my.cnf 设置如下信息:
[mysqld] # 打开binlog log-bin=mysql-bin # 选择ROW(行)模式 binlog-format=ROW # 配置MySQL replaction需要定义,不要和canal的slaveId重复 server_id=1
改了配置文件之后,重启 MySQL,使用命令查看是否打开 binlog 模式:
SHOW VARIABLES LIKE 'log_bin';
查看 binlog 日志文件列表:SHOW BINARY LOGS;
查看当前正在写入的 binlog 文件:SHOW MASTER STATUS;
记录文件名 File 和 Position 值。
启动 Canal 服务
详细配置可以参考:
conf\example\instance.properties ################################################# ## mysql serverId , v1.0.26+ will autoGen # canal.instance.mysql.slaveId=0 //每个instance都会伪装成一个mysql slave , 此id对于canal前端的Mysql实例而言,必须是唯一的,但是同一个Canal中相同的instance,此slaveld应该一样 # enable gtid use true/false canal.instance.gtidon=false # position info canal.instance.master.address=127.0.0.1:3306 //需要连接的数据库地址及端口 canal.instance.master.journal.name= //需要读取的起始的binlog文件 canal.instance.master.position= //需要读取的起始的binlog文件的偏移量 canal.instance.master.timestamp= //需要读取的起始的binlog的时间戳 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 //v1.0.25版本新增,是否开启table meta的时间序列版本记录功能 #canal.instance.tsdb.url=jdbc:mysql://127.0.0.1:3306/canal_tsdb //v1.0.25版本新增,table meta的时间序列版本的本地存储路径,默认为instance目录 #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=canal //数据库账号 canal.instance.dbPassword=canal //数据库密码 canal.instance.connectionCharset = UTF-8 //数据库解析编码格式 canal.instance.defaultDatabaseName =test //数据库连接时默认schema # enable druid Decrypt database password canal.instance.enableDruid=false #canal.instance.pwdPublicKey=MFwwDQYJKoZIhvcNAQEBBQADSwAwSAJBALK4BUxdDltRRE5/zXpVEVPUgunvscYFtEip3pmLlhrWpacX7y7GCMo2/JM6LeHmiiNdH1FWgGCpUfircSwlWKUCAwEAAQ== # table regex canal.instance.filter.regex=.*\\..* //mysql 数据解析关注的表,Perl正则表达式. # table black regex canal.instance.filter.black.regex= //canal将会过滤那些不符合要求的table,这些table的数据将不会被解析和传送 #################################################
conf\canal.properties ################################################# ######### common argument ############# ################################################# canal.id= 1 #每个canal server实例的唯一标识 canal.ip= #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, canal.port=11111 #canal server提供socket tcp服务的端口 canal.metrics.pull.port=11112 canal.zkServers= #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持久化数据到file上的目录 canal.file.flush.period = 1000 #canal持久化数据到file上的更新频率,单位毫秒 ## memory store RingBuffer size, should be Math.pow(2,n) canal.instance.memory.buffer.size = 16384 #canal内存store中可缓存buffer记录数,需要为2的指数 ## memory store RingBuffer used memory unit size , default 1kb canal.instance.memory.buffer.memunit = 1024 # 内存记录的单位大小,默认1KB,和buffer.size组合决定最终的内存使用大小 ## meory store gets mode used MEMSIZE or ITEMSIZE canal.instance.memory.batch.mode = MEMSIZE #canal内存store中数据缓存模式 1. ITEMSIZE : 根据buffer.size进行限制,只限制记录的数量 2. MEMSIZE : 根据buffer.size * buffer.memunit的大小,限制缓存记录的大小 canal.instance.memory.rawEntry = true ## detecing config canal.instance.detecting.enable = false #是否开启心跳检查 #canal.instance.detecting.sql = insert into retl.xdual values(1,now()) on duplicate key update x=now() canal.instance.detecting.sql = select 1 #心跳检查sql canal.instance.detecting.interval.time = 3 #心跳检查频率,单位秒 canal.instance.detecting.retry.threshold = 3 #心跳检查失败重试次数 ##非常注意:interval.time * retry.threshold值,应该参考既往DBA同学对数据库的故障恢复时间, ##“太短”会导致集群运行态角色“多跳”;“太长”失去了活性检测的意义,导致集群的敏感度降低,Consumer断路可能性增加。 canal.instance.detecting.heartbeatHaEnable = false #心跳检查失败后,是否开启自动mysql自动切换 #说明:比如心跳检查失败超过阀值后,如果该配置为true,canal就会自动链到mysql备库获取binlog数据 false # support maximum transaction size, more than the size of the transaction will be cut into multiple transactions delivery canal.instance.transaction.size = 1024 # 最大事务完整解析的长度支持超过该长度后,一个事务可能会被拆分成多次提交到canal store中,无法保证事务的完整可见性 # mysql fallback connected to new master should fallback times canal.instance.fallbackIntervalInSeconds = 60 #canal发生mysql切换时,在新的mysql库上查找 binlog时需要往前查找的时间,单位秒 说明:mysql主备库可能存在解析延迟或者时钟不统一,需要回退一段时间,保证数据不丢 # network config canal.instance.network.receiveBufferSize = 16384 #网络链接参数,SocketOptions.SO_RCVBUF canal.instance.network.sendBufferSize = 16384 #网络链接参数,SocketOptions.SO_SNDBUF canal.instance.network.soTimeout = 30 #网络链接参数,SocketOptions.SO_TIMEOUT # binlog filter config canal.instance.filter.druid.ddl = true canal.instance.filter.query.dcl = false #ddl语句是否隔离发送,开启隔离可保证每次只返回发送一条ddl数据,不和其他dml语句混合返回.(otter ddl同步使用) canal.instance.filter.query.dml = false #是否忽略DML的query语句,比如insert/update/delete table.(mysql5.6的ROW模式可以包含statement模式的query记录) canal.instance.filter.query.ddl = false #是否忽略DDL的query语句,比如create table/alater table/drop table/rename table/create index/drop index. (目前支持的ddl类型主要为table级别的操作,create databases/trigger/procedure暂时划分为dcl类型) 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 //关于时间序列版本 canal.instance.tsdb.enable=true canal.instance.tsdb.dir=${canal.file.data.dir:../conf}/${canal.instance.destination:} canal.instance.tsdb.url=jdbc:h3:${canal.instance.tsdb.dir}/h3;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 # rds oss binlog account canal.instance.rds.accesskey = canal.instance.rds.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 #开启instance自动扫描 如果配置为true,canal.conf.dir目录下的instance配置变化会自动触发: a. instance目录新增: 触发instance配置载入,lazy为true时则自动启动 b. instance目录删除:卸载对应instance配置,如已启动则进行关闭 c. instance.properties文件变化:reload instance配置,如已启动自动进行重启操作 canal.auto.scan.interval = 5 #instance自动扫描的间隔时间,单位秒 canal.instance.tsdb.spring.xml=classpath:spring/tsdb/h3-tsdb.xml #canal.instance.tsdb.spring.xml=classpath:spring/tsdb/mysql-tsdb.xml canal.instance.global.mode = spring #instance管理模式,Production级别我们要求使用spring canal.instance.global.lazy = false #全局lazy模式 #canal.instance.global.manager.address = 127.0.0.1:1099 #全局的manager配置方式的链接信息 #canal.instance.global.spring.xml = classpath:spring/memory-instance.xml canal.instance.global.spring.xml = classpath:spring/file-instance.xml #全局的spring配置方式的组件文件 #canal.instance.global.spring.xml = classpath:spring/default-instance.xml
1)canal.deployer-1.1.5\conf\canal.properties
进行全局配置,可以修改 IP、端口号或实例
# 默认有一个 example,需要增加实例的可以配置 canal.destinations = example
2)canal.deployer-1.1.5\conf\example\instance.properties
进行局部实例配置,可以修改数据库账号和密码、数据库表名、binlog 文件名和 position 等
# 没有改变的就没有贴出来,注意 MySQL 的用户名和密码 canal.instance.master.address=192.168.58.131:3306 # username/password canal.instance.dbUsername=test canal.instance.dbPassword=liubihao canal.instance.connectionCharset = UTF-8 # enable druid Decrypt database password canal.instance.enableDruid=false # table regex canal.instance.filter.regex=.*\\..* # table black regex canal.instance.filter.black.regex=
ysql 数据解析m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)
bin/start.sh
启动服务(Windows 系统为bin/start.bat
)
后端进行相应配置
修改 pom.xml
<dependency> <groupId>com.alibaba.otter</groupId> <artifactId>canal.client</artifactId> <version>1.1.4</version> </dependency>
新建 CanalClient.java
package org.nwpu.atcss.util; import com.alibaba.otter.canal.client.CanalConnector; import com.alibaba.otter.canal.client.CanalConnectors; import com.alibaba.otter.canal.protocol.CanalEntry.*; import com.alibaba.otter.canal.protocol.Message; import org.springframework.stereotype.Component; import java.util.List; import java.net.InetSocketAddress; @Component public class CanalClient { private static void printEntries(List<Entry> entries) throws Exception { for (Entry entry : entries) { if (entry.getEntryType() != EntryType.ROWDATA) { continue; } RowChange rowChange = RowChange.parseFrom(entry.getStoreValue()); EventType eventType = rowChange.getEventType(); System.out.println(String.format("================> binlog[%s:%s] , name[%s,%s] , eventType : %s", entry.getHeader().getLogfileName(), entry.getHeader().getLogfileOffset(), entry.getHeader().getSchemaName(), entry.getHeader().getTableName(), eventType)); for (RowData rowData : rowChange.getRowDatasList()) { switch (rowChange.getEventType()) { case INSERT: System.out.println("INSERT "); printColumns(rowData.getAfterColumnsList()); break; case UPDATE: System.out.println("UPDATE "); printColumns(rowData.getAfterColumnsList()); break; case DELETE: System.out.println("DELETE "); printColumns(rowData.getBeforeColumnsList()); break; default: break; } } } } private static void printColumns(List<Column> columns) { for (Column column : columns) { System.out.println(column.getName() + " : " + column.getValue() + " update=" + column.getUpdated()); } } public static void main(String[] args) throws Exception { // hostname, port, destination, username, password CanalConnector connector = CanalConnectors.newSingleConnector(new InetSocketAddress("127.0.0.1", 11111), "example", "", ""); try { connector.connect(); // 监听的表,格式为数据库.表名,数据库.表名 connector.subscribe(".*\\..*"); connector.rollback(); while (true) { Message message = connector.getWithoutAck(100); // 获取指定数量的数据 long batchId = message.getId(); if (batchId == -1 || message.getEntries().isEmpty()) { Thread.sleep(1000); continue; } // System.out.println(message.getEntries()); printEntries(message.getEntries()); connector.ack(batchId); // 提交确认,消费成功,通知server删除数据 // connector.rollback(batchId);// 处理失败, 回滚数据,后续重新获取数据 } } catch (Exception e) { System.out.println("Something Error."); } finally { connector.disconnect(); } } }
测试
启动 CanalClient.java
;
修改本地数据库内容之后,控制台成功监听并报告更新信息。
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