利用Sharding-Jdbc进行分库分表的操作代码

目录

• 1. Sharding-Jdbc介绍
• 2. Sharding-Jdbc引入使用
• 3. 配置广播表
• 4. 配置绑定表
• 5. 读写分离配置

1. Sharding-Jdbc介绍

https://shardingsphere.apache.org/

• sharding-jdbc是一个分布式的关系型数据库中间件
• 客户端代理模式，不需要搭建服务器，只需要后端数据库即可，有个IDE就行了
• 定位于轻量级的Java框架，以jar的方式提供服务
• 可以理解为增强版的jdbc驱动
• 完全兼容主流的ORM框架

sharding-jdbc提供了4种配置

• Java API
• yaml
• properties
• spring命名空间

与MyCat的区别

• MyCat是服务端的代理，Sharding-Jdbc是客户端代理
• 实际开发中如果企业有DBA建议使用MyCat，都是开发人员建议使用sharding-jdbc
• MyCat不支持在一个库内进行水平分表，而sharding-jdbc支持在同一个数据库中进行水平分表

名词解释

• 逻辑表：物流的合并表
• 真实表：存放数据的地方
• 数据节点：存储数据的MySQL节点
• 绑定表：相当于MyCat中的子表
• 广播表：相当于MyCat中的全局表

2. Sharding-Jdbc引入使用

# 0.首先在两个MySQL上创建两个数据：shard_order
# 1.分表给两个库创建两个表order_info_1,order_info_2
CREATE TABLE `order_info_1` (
  `id` int(11) NOT NULL,
  `order_amount` decimal(10,2) DEFAULT NULL,
  `order_status` int(255) DEFAULT NULL,
  `user_id` int(11) DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;
CREATE TABLE `order_info_2` (
  `id` int(11) NOT NULL,
  `order_amount` decimal(10,2) DEFAULT NULL,
  `order_status` int(255) DEFAULT NULL,
  `user_id` int(11) DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;
# 2.切分规则，按照id的奇偶数切分到两个数据库，在自己的数据库按照user_id进行表切分

代码导入POM依赖

 <dependency>
            <groupId>org.apache.shardingsphere</groupId>
            <artifactId>sharding-jdbc-spring-boot-starter</artifactId>
            <version>4.0.0-RC2</version>
        </dependency>

配置properties

# 给两个数据源命名
spring.shardingsphere.datasource.names=ds0,ds1
# 数据源链接ds0要和命名一致
spring.shardingsphere.datasource.ds0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds0.jdbcUrl=jdbc:mysql://39.103.163.215:3306/shard_order
spring.shardingsphere.datasource.ds0.username=gavin
spring.shardingsphere.datasource.ds0.password=123456
# 数据源链接ds1要和命名一致
spring.shardingsphere.datasource.ds1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds1.jdbcUrl=jdbc:mysql://39.101.221.95:3306/shard_order
spring.shardingsphere.datasource.ds1.username=gavin
spring.shardingsphere.datasource.ds1.password=123456
# 具体的分片规则,基于数据节点
spring.shardingsphere.sharding.tables.order_info.actual-data-nodes=ds$->{0..1}.order_info_$->{1..2}
# 分库的规则
spring.shardingsphere.sharding.tables.order_info.database-strategy.inline.sharding-column=id
spring.shardingsphere.sharding.tables.order_info.database-strategy.inline.algorithm-expression=ds$->{id % 2}
# 分表的规则
spring.shardingsphere.sharding.tables.order_info.table-strategy.inline.sharding-column=user_id
spring.shardingsphere.sharding.tables.order_info.table-strategy.inline.algorithm-expression=order_info_$->{user_id % 2 + 1}

//测试代码
@SpringBootTest
class ShardingjdbcProjectApplicationTests {
    @Autowired
    JdbcTemplate jdbcTemplate;
    @Test
    void insertTest(){
        String sql = "insert into order_info(id,order_amount,order_status,user_id) values(3,213.88,1,2)";
        int i = jdbcTemplate.update(sql);
        System.out.println("影响行数:"+i);
    }
}

作业：自己练习一下sharding-jdbc的分库分表

3. 配置广播表

先在两个库上创建广播表province_info

CREATE TABLE `province_info` (
  `id` int(11) NOT NULL,
  `name` varchar(255) DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

在properties里增加配置

spring.shardingsphere.sharding.broadcast-tables=province_info

测试插入和查询的代码

 @Test
    void insertBroadcast(){
        String sql = "insert into province_info(id,name) values(1,'beijing')";
        int i = jdbcTemplate.update(sql);
        System.out.println("******* 影响的结果："+i);
    }

    @Test
    void selectBroadcast(){
        String sql = "select * from province_info";
        List<Map<String,Object>> result = jdbcTemplate.queryForList(sql);
        for (Map<String,Object> val: result) {
            System.out.println("=========== "+val.get("id")+" ----- "+val.get("name"));

        }
    }

4. 配置绑定表

首先按照order_info的建表顺序创建order_item分别在两个库上建立order_item_1,order_item_2

​
 @Test
    void insertBroadcast(){
        String sql = "insert into province_info(id,name) values(1,'beijing')";
        int i = jdbcTemplate.update(sql);
        System.out.println("******* 影响的结果："+i);
    }

    @Test
    void selectBroadcast(){
        String sql = "select * from province_info";
        List<Map<String,Object>> result = jdbcTemplate.queryForList(sql);
        for (Map<String,Object> val: result) {
            System.out.println("=========== "+val.get("id")+" ----- "+val.get("name"));

        }
    }

​

配置绑定表，将两个表的分表逻辑和order_info保持一致

# 给两个数据源命名
spring.shardingsphere.datasource.names=ds0,ds1
# 数据源链接ds0要和命名一致
spring.shardingsphere.datasource.ds0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds0.jdbcUrl=jdbc:mysql://39.103.163.215:3306/shard_order
spring.shardingsphere.datasource.ds0.username=gavin
spring.shardingsphere.datasource.ds0.password=123456
# 数据源链接ds1要和命名一致
spring.shardingsphere.datasource.ds1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.ds1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.ds1.jdbcUrl=jdbc:mysql://39.101.221.95:3306/shard_order
spring.shardingsphere.datasource.ds1.username=gavin
spring.shardingsphere.datasource.ds1.password=123456

# 具体的分片规则,基于数据节点
spring.shardingsphere.sharding.tables.order_info.actual-data-nodes=ds$->{0..1}.order_info_$->{1..2}
# 分库的规则
spring.shardingsphere.sharding.tables.order_info.database-strategy.inline.sharding-column=id
spring.shardingsphere.sharding.tables.order_info.database-strategy.inline.algorithm-expression=ds$->{id % 2}
# 分表的规则
spring.shardingsphere.sharding.tables.order_info.table-strategy.inline.sharding-column=user_id
spring.shardingsphere.sharding.tables.order_info.table-strategy.inline.algorithm-expression=order_info_$->{user_id % 2 + 1}

# 具体的分片规则,基于数据节点
spring.shardingsphere.sharding.tables.order_item.actual-data-nodes=ds$->{0..1}.order_item_$->{1..2}
# 分库的规则
spring.shardingsphere.sharding.tables.order_item.database-strategy.inline.sharding-column=order_id
spring.shardingsphere.sharding.tables.order_item.database-strategy.inline.algorithm-expression=ds$->{order_id % 2}
# 分表的规则
spring.shardingsphere.sharding.tables.order_item.table-strategy.inline.sharding-column=user_id
spring.shardingsphere.sharding.tables.order_item.table-strategy.inline.algorithm-expression=order_item_$->{user_id % 2 + 1}

# 绑定表关系
spring.shardingsphere.sharding.binding-tables=order_info,order_item

# 广播表
spring.shardingsphere.sharding.broadcast-tables=province_info

5. 读写分离配置

首先配置properties的数据源，如果有主机配置就必须要有从机配置

# 指定主从的配置节点
spring.shardingsphere.datasource.names=master0,master0slave0,master1,master1slave0
# master0数据源链接配置
spring.shardingsphere.datasource.master0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.master0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.master0.jdbcUrl=jdbc:mysql://39.103.163.215:3306/shard_order
spring.shardingsphere.datasource.master0.username=gavin
spring.shardingsphere.datasource.master0.password=123456
# master0slave0数据源链接配置
spring.shardingsphere.datasource.master0slave0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.master0slave0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.master0slave0.jdbcUrl=jdbc:mysql://39.99.212.46:3306/shard_order
spring.shardingsphere.datasource.master0slave0.username=gavin
spring.shardingsphere.datasource.master0slave0.password=123456
# master1数据源链接配置
spring.shardingsphere.datasource.master1.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.master1.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.master1.jdbcUrl=jdbc:mysql://39.101.221.95:3306/shard_order
spring.shardingsphere.datasource.master1.username=gavin
spring.shardingsphere.datasource.master1.password=123456
# master1slave0数据源链接配置
spring.shardingsphere.datasource.master1slave0.type=com.zaxxer.hikari.HikariDataSource
spring.shardingsphere.datasource.master1slave0.driver-class-name=com.mysql.jdbc.Driver
spring.shardingsphere.datasource.master1slave0.jdbcUrl=jdbc:mysql://localhost:3306/shard_order
spring.shardingsphere.datasource.master1slave0.username=root
spring.shardingsphere.datasource.master1slave0.password=gavin

# 具体的分片规则,基于数据节点
spring.shardingsphere.sharding.tables.order_info.actual-data-nodes=ds$->{0..1}.order_info_$->{1..2}
# 分库的规则
spring.shardingsphere.sharding.tables.order_info.database-strategy.inline.sharding-column=id
spring.shardingsphere.sharding.tables.order_info.database-strategy.inline.algorithm-expression=ds$->{id % 2}
# 分表的规则
spring.shardingsphere.sharding.tables.order_info.table-strategy.inline.sharding-column=user_id
spring.shardingsphere.sharding.tables.order_info.table-strategy.inline.algorithm-expression=order_info_$->{user_id % 2 + 1}

# 具体的分片规则,基于数据节点
spring.shardingsphere.sharding.tables.order_item.actual-data-nodes=ds$->{0..1}.order_item_$->{1..2}
# 分库的规则
spring.shardingsphere.sharding.tables.order_item.database-strategy.inline.sharding-column=order_id
spring.shardingsphere.sharding.tables.order_item.database-strategy.inline.algorithm-expression=ds$->{order_id % 2}
# 分表的规则
spring.shardingsphere.sharding.tables.order_item.table-strategy.inline.sharding-column=user_id
spring.shardingsphere.sharding.tables.order_item.table-strategy.inline.algorithm-expression=order_item_$->{user_id % 2 + 1}

# 绑定表关系
spring.shardingsphere.sharding.binding-tables=order_info,order_item

# 广播表
spring.shardingsphere.sharding.broadcast-tables=province_info

# 读写分离主从关系绑定
spring.shardingsphere.sharding.master-slave-rules.ds0.master-data-source-name=master0
spring.shardingsphere.sharding.master-slave-rules.ds0.slave-data-source-names=master0slave0
spring.shardingsphere.sharding.master-slave-rules.ds0.load-balance-algorithm-type=round_robin

spring.shardingsphere.sharding.master-slave-rules.ds1.master-data-source-name=master1
spring.shardingsphere.sharding.master-slave-rules.ds1.slave-data-source-names=master1slave0
spring.shardingsphere.sharding.master-slave-rules.ds1.load-balance-algorithm-type=random

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