sharding:
  jdbc:
    config:
      sharding:
        tables:
          myorder:
            key-generator-column-name: id  #主键
            actual-data-nodes: db$->{0..1}.myorder_$->{0..1}
            #分库策略
            database‐strategy:
              standard:
                sharding-column: id
                #精确分库分片配置类
                precise-algorithm-class-name: org.test.sharding.ShardingConfig
            #分表策略
            table-strategy:
              standard:
                sharding-column: id
                #精确分表分片配置类
                precise-algorithm-class-name: org.test.sharding.ShardingTableConfig
          orderitem:  #test
            key-generator-column-name: id  #主键
            actual-data-nodes: db$->{0..1}.orderitem_$->{0..2}    #数据节点,均匀分布
            #分库策略
            database‐strategy:
              inline:
                sharding-column: id
                algorithm-expression: db$->{id%2}
            table-strategy:
              inline:
                sharding-column: id
                algorithm-expression: orderitem_$->{id%2+1}
        #当两个分表的表进行关联查询的时候一定要将这两个表设置绑定表，否则会出现笛卡尔积
        binding-tables[0]: orderitem,myorder
      props:
        sql:
          show: true

    datasource:
      names: db0,db1
      db0:
        type: com.alibaba.druid.pool.DruidDataSource
        driver-class-name: com.mysql.jdbc.Driver
        url: jdbc:mysql://localhost:3306/demo
        username: root
        password: 123456
      db1:
        type: com.alibaba.druid.pool.DruidDataSource
        driver-class-name: com.mysql.jdbc.Driver
        url: jdbc:mysql://localhost:3306/demo1
        username: root
        password: 123456

精确分库策略配置类

/**
 * @author huQi
 * @email
 * @data 2021/1/20 13:04
 */

import io.shardingsphere.api.algorithm.sharding.PreciseShardingValue;
import io.shardingsphere.api.algorithm.sharding.standard.PreciseShardingAlgorithm;
import org.springframework.stereotype.Component;
import java.util.*;
@Component
public class ShardingConfig implements PreciseShardingAlgorithm<Long> {

    /**
     *  在开发的环境中一定不要用随机数来决定是在哪个库，会出现无法准确的定位库的情况
     * @param collection  库名集合
     * @param preciseShardingValue 分片列
     * @return
     */
    
    @Override
    public String doSharding(Collection<String> collection, PreciseShardingValue<Long> preciseShardingValue) {
        // 分片字段值
        Long value = preciseShardingValue.getValue();
        // 现在算法是:%2 求余如果是0则ds0.xmjbq_user,如果是1则ds0.xmjbq_user。但是由于id是字符串而且是很长的，所以截取最后一位然后转为Integer类型再求余

        Random random = new Random();
        int pick = random.nextInt(1);
        for (String s : collection) {
            if(s.contains(String.valueOf(pick))){
                return s;
            }
        }
        throw new UnsupportedOperationException();
    }

}

精确分表配置类

import io.shardingsphere.api.algorithm.sharding.PreciseShardingValue;
import io.shardingsphere.api.algorithm.sharding.standard.PreciseShardingAlgorithm;
import org.springframework.stereotype.Component;

import java.util.Collection;
import java.util.Random;

/**
 * @author huQi
 * @email
 * @data 2021/1/20 14:19
 */
@Component
public class ShardingTableConfig  implements PreciseShardingAlgorithm<Long> {
    /**
     * 在开发的环境中一定不要用随机数来决定是在哪个表，会出现无法准确的定位表的情况
     *
     * */
    @Override
    public String doSharding(Collection<String> tables, PreciseShardingValue<Long> preciseShardingValue) {
        // 分片字段值
        Long value = preciseShardingValue.getValue();
        // 现在算法是:%2 求余如果是0则ds0.xmjbq_user,如果是1则ds0.xmjbq_user。但是由于id是字符串而且是很长的，所以截取最后一位然后转为Integer类型再求余

        Random random = new Random();
        int pick = 0;
        if(tables.size()>1){
            pick = random.nextInt(3);
        }

        for (String s : tables) {
            System.out.println("sharding:"+s+"随机数"+pick);
                if(s.contains(String.valueOf(pick))){
                    return s;
                }
        }

        throw new UnsupportedOperationException();
    }
}

数据库

demo:myorder_0,myorder_1,orderitem_0,orderitem_1,orderitem_2

demo1:myorder_0,myorder_1,orderitem_0,orderitem_1,orderitem_2