学习笔记-Mysql主从复制（作读写分离）

Mysql主从复制（作读写分离）

1. 启动docker的mysql实例
2. 写配置文件，配置需要同步和忽略的库
3. 从库连接主库同步数据

一、创建Master实例

启动docker容器

docker run -p 3307:3306 --name mysql-master \
-v /mydata/mysql/master/log:/var/log/mysql \
-v /mydata/mysql/master/data:/var/lib/mysql \
-v /mydata/mysql/master/conf:/etc/mysql \
-e MYSQL_ROOT_PASSWORD=bestvincent_mysql \
-d mysql:5.7 
参数说明
	-p 3307:3306：将容器的3306端口映射到主机的3307端口
	-v /mydata/mysql/master/conf:/etc/mysql：将配置文件夹挂在到主机
	-v /mydata/mysql/master/log:/var/log/mysql：将日志文件夹挂载到主机
	-v /mydata/mysql/master/data:/var/lib/mysql/：将配置文件夹挂载到主机
	-e MYSQL_ROOT_PASSWORD=root：初始化root用户的密码

配置mysql

#修改master基本配置
vim /mydata/mysql/master/conf/my.cnf

[client]
default-character-set=utf8
 
[mysql]
default-character-set=utf8
 
[mysqld]
init_connect='SET collation_connection = utf8_unicode_ci'
init_connect='SET NAMES utf8'
character-set-server=utf8
collation-server=utf8_unicode_ci
skip-character-set-client-handshake
skip-name-resolve
#注意：skip-name-resolve一定要加，不然连接mysql会超级慢
#添加master主从复制部分配置
server_id=1
log-bin=mysql-bin
read-only=0
binlog-do-db=gmall_ums
binlog-do-db=gmall_pms
binlog-do-db=gmall_oms
binlog-do-db=gmall_sms
binlog-do-db=gmall_cms


replicate-ignore-db=mysql
replicate-ignore-db=sys
replicate-ignore-db=information_schema
replicate-ignore-db=performance_schema
#重启master

二、创建Slave并启动

启动从机docker容器

docker run -p 3316:3306 --name mysql-slaver-01 \
-v /mydata/mysql/slaver/log:/var/log/mysql \
-v /mydata/mysql/slaver/data:/var/lib/mysql \
-v /mydata/mysql/slaver/conf:/etc/mysql \
-e MYSQL_ROOT_PASSWORD=root \
-d mysql:5.7 

配置从机

#修改slave基本配置
vim /mydata/mysql/slaver/conf/my.cnf

[client]
default-character-set=utf8
 
[mysql]
default-character-set=utf8
 
[mysqld]
init_connect='SET collation_connection = utf8_unicode_ci'
init_connect='SET NAMES utf8'
character-set-server=utf8
collation-server=utf8_unicode_ci
skip-character-set-client-handshake
skip-name-resolve 
#添加master主从复制部分配置
server_id=2
log-bin=mysql-bin
read-only=1
binlog-do-db=gmall_ums
binlog-do-db=gmall_pms
binlog-do-db=gmall_oms
binlog-do-db=gmall_sms
binlog-do-db=gmall_cms


replicate-ignore-db=mysql
replicate-ignore-db=sys
replicate-ignore-db=information_schema
replicate-ignore-db=performance_schema
#重启slaver

三、主库授权配置

进入mysql容器内部

#从docker进入mysql内部命令
docker exec -it mysql-master /bin/bash
#进入后运行mysql命令进入mysql命令行
mysql -uroot -proot

授权远程访问用户

#1）、授权root可以远程访问（ 主从无关，为了方便我们远程连接mysql）
grant all privileges on *.* to 'root'@'%' identified by 'root' with grant option;
flush privileges;
#2）、添加用来同步的用户
GRANT REPLICATION SLAVE ON *.* to 'backup'@'%' identified by '123456';
#3、查看master状态
show master status\G;

四、从库连接配置

进入从库容器内部后，配置主库连接信息

#1）、授权root可以远程访问（ 主从无关，为了方便我们远程连接mysql）
grant all privileges on *.* to 'root'@'%' identified by 'root' with grant option;
flush privileges;

#2）、设置主库连接
change master to master_host='192.168.159.128',master_user='backup',master_password='123456',master_log_file='mysql-bin.000001',master_log_pos=0,master_port=3307;
#3）、启动从库同步
start slave;
#4）、查看从库状态
show slave status\G;

五、整合sharding实现多数据源的读写分离

• 添加maven的sharding依赖

  <dependency>
      <groupId>io.shardingjdbc</groupId>
      <artifactId>sharding-jdbc-core</artifactId>
      <version>2.0.3</version>
  </dependency>
  

• 创建yml配置文件

  dataSources:
    db_master: !!com.zaxxer.hikari.HikariDataSource
      driverClassName: com.mysql.jdbc.Driver
      jdbcUrl: jdbc:mysql://192.168.214.131:3307/gmall_pms?useUnicode=true&characterEncoding=utf-8&useSSL=false
      username: root
      password: root
    db_slave: !!com.zaxxer.hikari.HikariDataSource
      driverClassName: com.mysql.jdbc.Driver
      jdbcUrl: jdbc:mysql://192.168.214.131:3316/gmall_pms?useUnicode=true&characterEncoding=utf-8&useSSL=false
      username: root
      password: root
  masterSlaveRule:
    name: db_ms
    masterDataSourceName: db_master
    slaveDataSourceNames: [db_slave]
  

• 创建配置类

  package com.bv.gmall.pms.config;
  
  import io.shardingjdbc.core.api.MasterSlaveDataSourceFactory;
  import org.springframework.context.annotation.Bean;
  import org.springframework.context.annotation.Configuration;
  import org.springframework.util.ResourceUtils;
  
  import javax.sql.DataSource;
  import java.io.File;
  import java.io.FileNotFoundException;
  import java.io.IOException;
  import java.sql.SQLException;
  
  @Configuration
  public class PmsDataSourceConfig {
      @Bean
      public DataSource dataSource() {
          DataSource dataSource = null;
          try {
              //加载配置文件
              File file = ResourceUtils.getFile("classpath:sharing-jdbc.yaml");
              //使用数据源工厂创建数据源实例
              dataSource = MasterSlaveDataSourceFactory.createDataSource(file);
          } catch (FileNotFoundException e) {
              e.printStackTrace();
          } catch (SQLException e) {
              e.printStackTrace();
          } catch (IOException e) {
              e.printStackTrace();
          }
          return dataSource;
      }
  }