数据量达到1000w或以上使用分库分表提升数据库操作性能
作者：互联网
数据切分根据其切分类型，可以分为两种方式：垂直（纵向）切分和水平（横向）切分
1.ShardingSphere-Jdbc
ShardingSphere-Jdbc定位为轻量级Java框架，在Java的Jdbc层提供的额外服务。它使用客户端直连数据库，以jar包形式提供服务，可理解为增强版的Jdbc驱动，完全兼容Jdbc和各种ORM框架
2、MySQL主从复制
docker配置mysql主从复制
1）创建主服务器所需目录
mkdir -p /usr/local/mysqlData/master/cnf
mkdir -p /usr/local/mysqlData/master/data
2）定义主服务器配置文件
vim /usr/local/mysqlData/master/cnf/mysql.cnf
[mysqld]
## 设置server_id,注意要唯一
server-id=1
## 开启binlog
log-bin=mysql-bin
## binlog缓存
binlog_cache_size=1M
## binlog格式(mixed、statement、row,默认格式是statement)
binlog_format=mixed
3）创建并启动mysql主服务
docker run -itd -p 3306:3306 --name master -v /usr/local/mysqlData/master/cnf:/etc/mysql/conf.d -v /usr/local/mysqlData/master/data:/var/lib/mysql -e MYSQL_ROOT_PASSWORD=123456 mysql:5.7
4）添加复制master数据的用户reader，供从服务器使用
[root@aliyun /]# docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
6af1df686fff mysql:5.7 "docker-entrypoint..." 5 seconds ago Up 4 seconds 0.0.0.0:3306->3306/tcp, 33060/tcp master
[root@aliyun /]# docker exec -it master /bin/bash
root@41d795785db1:/# mysql -u root -p123456
mysql> GRANT REPLICATION SLAVE ON *.* to 'reader'@'%' identified by 'reader';
Query OK, 0 rows affected, 1 warning (0.00 sec)
mysql> FLUSH PRIVILEGES;
Query OK, 0 rows affected (0.00 sec)
5）创建从服务器所需目录，编辑配置文件
mkdir /usr/local/mysqlData/slave/cnf -p
vim /usr/local/mysqlData/slave/cnf/mysql.cnf
[mysqld]
## 设置server_id,注意要唯一
server-id=2
## 开启binlog,以备Slave作为其它Slave的Master时使用
log-bin=mysql-slave-bin
## relay_log配置中继日志
relay_log=edu-mysql-relay-bin
## 如果需要同步函数或者存储过程
log_bin_trust_function_creators=true
## binlog缓存
binlog_cache_size=1M
## binlog格式(mixed、statement、row,默认格式是statement)
binlog_format=mixed
## 跳过主从复制中遇到的所有错误或指定类型的错误,避免slave端复制中断
## 如:1062错误是指一些主键重复,1032错误是因为主从数据库数据不一致
slave_skip_errors=1062
6）创建并运行mysql从服务器
docker run -itd -p 3307:3306 --name slaver -v /usr/local/mysqlData/slave/cnf:/etc/mysql/conf.d -v /usr/local/mysqlData/slave/data:/var/lib/mysql -e MYSQL_ROOT_PASSWORD=123456 mysql:5.7
7）在从服务器上配置连接主服务器的信息
首先主服务器上查看master_log_file、master_log_pos两个参数，然后切换到从服务器上进行主服务器的连接信息的设置
主服务上执行：
root@6af1df686fff:/# mysql -u root -p123456
mysql> show master status;
+------------------+----------+--------------+------------------+-------------------+
| File | Position | Binlog_Do_DB | Binlog_Ignore_DB | Executed_Gtid_Set |
+------------------+----------+--------------+------------------+-------------------+
| mysql-bin.000003 | 591 | | | |
+------------------+----------+--------------+------------------+-------------------+
1 row in set (0.00 sec)
docker查看主服务器容器的ip地址
[root@aliyun /]# docker inspect --format='{{.NetworkSettings.IPAddress}}' master
172.17.0.2
从服务器上执行：
[root@aliyun /]# docker exec -it slaver /bin/bash
root@fe8b6fc2f1ca:/# mysql -u root -p123456
mysql> change master to master_host='172.17.0.2',master_user='reader',master_password='reader',master_log_file='mysql-bin.000003',master_log_pos=591;
8）从服务器启动I/O 线程和SQL线程
mysql> start slave;
Query OK, 0 rows affected, 1 warning (0.00 sec)
mysql> show slave status\G
*************************** 1. row ***************************
Slave_IO_State: Waiting for master to send event
Master_Host: 172.17.0.2
Master_User: reader
Master_Port: 3306
Connect_Retry: 60
Master_Log_File: mysql-bin.000003
Read_Master_Log_Pos: 591
Relay_Log_File: edu-mysql-relay-bin.000002
Relay_Log_Pos: 320
Relay_Master_Log_File: mysql-bin.000003
Slave_IO_Running: Yes
Slave_SQL_Running: Yes
Slave_IO_Running: Yes，Slave_SQL_Running: Yes即表示启动成功。
4）两阶段提交
3、Sharding-Jdbc实现读写分离
1）、新建Springboot工程，引入相关依赖
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.mybatis.spring.boot</groupId>
<artifactId>mybatis-spring-boot-starter</artifactId>
<version>2.1.4</version>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<scope>runtime</scope>
</dependency>
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>druid-spring-boot-starter</artifactId>
<version>1.1.21</version>
</dependency>
<dependency>
<groupId>org.apache.shardingsphere</groupId>
<artifactId>sharding-jdbc-spring-boot-starter</artifactId>
<version>4.0.0-RC1</version>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<optional>true</optional>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
</dependencies>
2）、application.properties配置文件
spring.main.allow-bean-definition-overriding=true
#显示sql
spring.shardingsphere.props.sql.show=true
#配置数据源
spring.shardingsphere.datasource.names=ds1,ds2,ds3
#master-ds1数据库连接信息
spring.shardingsphere.datasource.ds1.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.ds1.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.ds1.url=jdbc:mysql://47.101.58.187:3306/sharding-jdbc-db?useUnicode=true&useSSL=false&serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.ds1.username=root
spring.shardingsphere.datasource.ds1.password=123456
spring.shardingsphere.datasource.ds1.maxPoolSize=100
spring.shardingsphere.datasource.ds1.minPoolSize=5
#slave-ds2数据库连接信息
spring.shardingsphere.datasource.ds2.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.ds2.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.ds2.url=jdbc:mysql://47.101.58.187:3307/sharding-jdbc-db?useUnicode=true&useSSL=false&serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.ds2.username=root
spring.shardingsphere.datasource.ds2.password=123456
spring.shardingsphere.datasource.ds2.maxPoolSize=100
spring.shardingsphere.datasource.ds2.minPoolSize=5
#slave-ds3数据库连接信息
spring.shardingsphere.datasource.ds3.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.ds3.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.ds3.url=jdbc:mysql://47.101.58.187:3307/sharding-jdbc-db?useUnicode=true&useSSL=false&serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.ds3.username=root
spring.shardingsphere.datasource.ds3.password=123456
spring.shardingsphere.datasource.ds.maxPoolSize=100
spring.shardingsphere.datasource.ds3.minPoolSize=5
#配置默认数据源ds1 默认数据源,主要用于写
spring.shardingsphere.sharding.default-data-source-name=ds1
#配置主从名称
spring.shardingsphere.masterslave.name=ms
#置主库master,负责数据的写入
spring.shardingsphere.masterslave.master-data-source-name=ds1
#配置从库slave节点
spring.shardingsphere.masterslave.slave-data-source-names=ds2,ds3
#配置slave节点的负载均衡均衡策略,采用轮询机制
spring.shardingsphere.masterslave.load-balance-algorithm-type=round_robin
#整合mybatis的配置
mybatis.type-aliases-package=com.ppdai.shardingjdbc.entity
3）、创建t_user表
CREATE TABLE `t_user` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`nickname` varchar(100) DEFAULT NULL,
`password` varchar(100) DEFAULT NULL,
`sex` int(11) DEFAULT NULL,
`birthday` varchar(50) DEFAULT NULL,
PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=4 DEFAULT CHARSET=utf8mb4;
4）、定义Controller、Mapper、Entity
@Data
public class User {
private Integer id;
private String nickname;
private String password;
private Integer sex;
private String birthday;
}
@RestController
@RequestMapping("/api/user")
public class UserController {
@Autowired
private UserMapper userMapper;
@PostMapping("/save")
public String addUser() {
User user = new User();
user.setNickname("zhangsan" + new Random().nextInt());
user.setPassword("123456");
user.setSex(1);
user.setBirthday("1997-12-03");
userMapper.addUser(user);
return "success";
}
@GetMapping("/findUsers")
public List<User> findUsers() {
return userMapper.findUsers();
}
}
public interface UserMapper {
@Insert("insert into t_user(nickname,password,sex,birthday) values(#{nickname},#{password},#{sex},#{birthday})")
void addUser(User user);
@Select("select * from t_user")
List<User> findUsers();
}
5）、验证
经校验写数据进入ds1数据库，而读操作则是ds2,ds3两个数据库轮询操作。
4、MySQL分库分表原理
1）、分库分表
5、Sharding-Jdbc实现分库分表
1）、逻辑表
用户数据根据订单id%2拆分为2个表，分别是：t_order0和t_order1。他们的逻辑表名是：t_order
多数据源相同表：
#多数据源$->{0..N}.逻辑表名$->{0..N} 相同表
spring.shardingsphere.sharding.tables.t_order.actual-data-nodes=ds$->{0..1}.t_order$->{0..1}
多数据源不同表：
#多数据源$->{0..N}.逻辑表名$->{0..N} 不同表
spring.shardingsphere.sharding.tables.t_order.actual-data-nodes=ds0.t_order$->{0..1},ds1.t_order$->{2..4}
单库分表：
#单数据源的配置方式
spring.shardingsphere.sharding.tables.t_order.actual-data-nodes=ds0.t_order$->{0..4}
全部手动指定：
spring.shardingsphere.sharding.tables.t_order.actual-data-nodes=ds0.t_order0,ds1.t_order0,ds0.t_order1,ds1.t_order1
2）、inline分片策略
spring.shardingsphere.sharding.tables.t_order.actual-data-nodes=ds$->{0..1}.t_order$->{0..1}
#数据源分片策略
spring.shardingsphere.sharding.tables.t_order.database-strategy.inline.sharding-column=user_id
#数据源分片算法
spring.shardingsphere.sharding.tables.t_order.database-strategy.inline.algorithm-expression=ds$->{user_id%2}
#表分片策略
spring.shardingsphere.sharding.tables.t_order.table-strategy.inline.sharding-column=order_id
#表分片算法
spring.shardingsphere.sharding.tables.t_order.table-strategy.inline.algorithm-expression=t_order$->{order_id%2}
上面的配置通过user_id%2来决定具体数据源，通过order_id%2来决定具体表
insert into t_order(user_id,order_id) values(2,3)，user_id%2 = 0使用数据源ds0，order_id%2 = 1使用t_order1，insert语句最终操作的是数据源ds0的t_order1表。
3）、分布式主键配置
Sharding-Jdbc可以配置分布式主键生成策略。默认使用雪花算法（snowflake），生成64bit的长整型数据，也支持UUID的方式
#主键的列名
spring.shardingsphere.sharding.tables.t_order.key-generator.column=id
#主键生成策略
spring.shardingsphere.sharding.tables.t_order.key-generator.type=SNOWFLAKE
4）、inline分片策略实现分库分表
需求：
对1000w的用户数据进行分库分表，对用户表的数据进行分表和分库的操作。根据年龄奇数存储在t_user1，偶数t_user0，同时性别奇数存储在ds1，偶数ds0
表结构：
CREATE TABLE `t_user0` (
`id` bigint(20) DEFAULT NULL,
`nickname` varchar(200) DEFAULT NULL,
`password` varchar(200) DEFAULT NULL,
`age` int(11) DEFAULT NULL,
`sex` int(11) DEFAULT NULL,
`birthday` varchar(100) DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
CREATE TABLE `t_user1` (
`id` bigint(20) DEFAULT NULL,
`nickname` varchar(200) DEFAULT NULL,
`password` varchar(200) DEFAULT NULL,
`age` int(11) DEFAULT NULL,
`sex` int(11) DEFAULT NULL,
`birthday` varchar(100) DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
两个数据库中都包含t_user0和t_user1两张表
application.properties：
spring.main.allow-bean-definition-overriding=true
#显示sql
spring.shardingsphere.props.sql.show=true
#配置数据源
spring.shardingsphere.datasource.names=ds0,ds1
#ds0数据库连接信息
spring.shardingsphere.datasource.ds0.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.ds0.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.ds0.url=jdbc:mysql://47.101.58.187:3306/t_user_db0?useUnicode=true&useSSL=false&serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.ds0.username=root
spring.shardingsphere.datasource.ds0.password=123456
spring.shardingsphere.datasource.ds0.maxPoolSize=100
spring.shardingsphere.datasource.ds0.minPoolSize=5
#ds1数据库连接信息
spring.shardingsphere.datasource.ds1.type=com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.ds1.driver-class-name=com.mysql.cj.jdbc.Driver
spring.shardingsphere.datasource.ds1.url=jdbc:mysql://47.101.58.187:3306/t_user_db1?useUnicode=true&useSSL=false&serverTimezone=Asia/Shanghai
spring.shardingsphere.datasource.ds1.username=root
spring.shardingsphere.datasource.ds1.password=123456
spring.shardingsphere.datasource.ds1.maxPoolSize=100
spring.shardingsphere.datasource.ds1.minPoolSize=5
#整合mybatis的配置
mybatis.type-aliases-package=com.ppdai.shardingjdbc.entity
spring.shardingsphere.sharding.tables.t_user.actual-data-nodes=ds$->{0..1}.t_user$->{0..1}
#数据源分片策略
spring.shardingsphere.sharding.tables.t_user.database-strategy.inline.sharding-column=sex
#数据源分片算法
spring.shardingsphere.sharding.tables.t_user.database-strategy.inline.algorithm-expression=ds$->{sex%2}
#表分片策略
spring.shardingsphere.sharding.tables.t_user.table-strategy.inline.sharding-column=age
#表分片算法
spring.shardingsphere.sharding.tables.t_user.table-strategy.inline.algorithm-expression=t_user$->{age%2}
#主键的列名
spring.shardingsphere.sharding.tables.t_user.key-generator.column=id
spring.shardingsphere.sharding.tables.t_user.key-generator.type=SNOWFLAKE
测试类：
@SpringBootTest
class ShardingJdbcApplicationTests {
@Autowired
private UserMapper userMapper;
/**
* sex:奇数
* age:奇数
* ds1.t_user1
*/
@Test
public void test01() {
User user = new User();
user.setNickname("zhangsan" + new Random().nextInt());
user.setPassword("123456");
user.setAge(17);
user.setSex(1);
user.setBirthday("1997-12-03");
userMapper.addUser(user);
}
/**
* sex:奇数
* age:偶数
* ds1.t_user0
*/
@Test
public void test02() {
User user = new User();
user.setNickname("zhangsan" + new Random().nextInt());
user.setPassword("123456");
user.setAge(18);
user.setSex(1);
user.setBirthday("1997-12-03");
userMapper.addUser(user);
}
/**
* sex:偶数
* age:奇数
* ds0.t_user1
*/
@Test
public void test03() {
User user = new User();
user.setNickname("zhangsan" + new Random().nextInt());
user.setPassword("123456");
user.setAge(17);
user.setSex(2);
user.setBirthday("1997-12-03");
userMapper.addUser(user);
}
/**
* sex:偶数
* age:偶数
* ds0.t_user0
*/
@Test
public void test04() {
User user = new User();
user.setNickname("zhangsan" + new Random().nextInt());
user.setPassword("123456");
user.setAge(18);
user.setSex(2);
user.setBirthday("1997-12-03");
userMapper.addUser(user);
}
}
标签：分库,spring,mysql,ds1,1000w,user,数据量,shardingsphere,datasource 来源： https://blog.csdn.net/zouyang920/article/details/121861954