Sharding-JDBC 垂直分库和公共表

Posted 2021-02-20 路上的风景

垂直分库是指按照业务将表进行分类，分布到不同的数据库上面，每个库可以放在不同的服务器上，它的核心理念是专库专用。

　　(1)创建数据库，创建表

CREATE DATABASE `user_db` CHARACTER SET ‘utf8‘ COLLATE ‘utf8_general_ci‘;

USE user_db;

DROP TABLE IF EXISTS `t_user` ;

CREATE TABLE `t_user` (
  `user_id` BIGINT (20) NOT NULL COMMENT ‘用户id‘,
  `fullname` VARCHAR (255) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT ‘用户姓名‘,
  `user_type` CHAR(1) DEFAULT NULL COMMENT ‘用户类型‘,
  PRIMARY KEY (`user_id`) USING BTREE
) ENGINE = INNODB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = DYNAMIC;

　　(2)修改Sharding-JDBC规则

# sharding-jdbc分片规则配置
# 数据源，新增m0，对应user_db
spring.shardingsphere.datasource.names = m0,m1,m2

# m0数据源
spring.shardingsphere.datasource.m0.type = com.alibaba.druid.pool.DruidDataSource
spring.shardingsphere.datasource.m0.driver-class-name = com.mysql.jdbc.Driver
spring.shardingsphere.datasource.m0.url = jdbc:mysql://localhost:3306/user_db?useUnicode=true
spring.shardingsphere.datasource.m0.username = root
spring.shardingsphere.datasource.m0.password = root

......

# t_user分表策略，固定分配至m0的t_user真实表
spring.shardingsphere.sharding.tables.t_user.actual-data-nodes = m0.t_user

......

# 没有分表可以不配置表的分片策略(主键生成策略也可以不配，默认采用数据库的)
#spring.shardingsphere.sharding.tables.t_user.table-strategy.inline.sharding-column = user_id
#spring.shardingsphere.sharding.tables.t_user.table-strategy.inline.algorithm-expression = t_user

　　(3)持久层

@Mapper
public interface UserDao {

    /**
     * 新增用户
     * @return
     * @param fullname 用户姓名
     */
    @Insert("insert into t_user(fullname) values(#{fullname})")
    int insertUser(String fullname);

    /**
     * 根据id列表查询多个用户
     * @return      
     * @param userIds 用户id列表
     */
    @Select("<script>" +
            "select" +
            " * " +
            " from t_user u " +
            " where u.user_id in " +
            " <foreach collection=‘userIds‘ open=‘(‘ separator=‘,‘ close=‘)‘ item=‘id‘> " +
            " #{id} " +
            " </foreach>" +
            "</script>")
    List<Map> selectUserbyIds(@Param("userIds") List<Long> userIds);
}

　　(4)测试

    @Test
    public void testInsertUser() {
        for (int i = 1; i <= 10; i++) {
            userDao.insertUser("姓名" + i);
        }
    }

    @Test
    public void testSelectUserbyIds() {
        List<Long> userIds = new ArrayList<>();
        userIds.add(1L);
        userIds.add(2L);
        List<Map> users = userDao.selectUserbyIds(userIds);
        System.out.println(users);
    }

公共表属于系统中数据量较小，变动少，而且属于高频联合查询的依赖表。参数表、数据字典表等属于此类型。可以将这类表在每个数据库都保存一份，所有更新操作都同时发送到所有分库执行。
　　(1)分别在user_db、order_db_1、order_db_2中创建t_dict表：

CREATE TABLE `t_dict`  (
 `dict_id` bigint(20) NOT NULL COMMENT ‘字典id‘,
 `type` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT ‘字典类型‘,
 `code` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT ‘字典编码‘,
 `value` varchar(50) CHARACTER SET utf8 COLLATE utf8_general_ci NOT NULL COMMENT ‘字典值‘,
 PRIMARY KEY (`dict_id`) USING BTREE
) ENGINE = InnoDB CHARACTER SET = utf8 COLLATE = utf8_general_ci ROW_FORMAT = Dynamic;

　　(2)修改Sharding-JDBC规则

# 指定t_dict为公共表
spring.shardingsphere.sharding.broadcast‐tables = t_dict

　　(3)持久层

@Mapper
public interface DictDao {

    /**
     * 新增字典
     * @param type  字典类型
     * @param code  字典编码
     * @param value 字典值
     * @return
     */
    @Insert("insert into t_dict(type, code, value) values(#{dictId}, #{type}, #{code}, #{value})")
    int insertDict(String type, String code, String value);

    /**
     * 删除字典
     * @param dictId 字典id
     * @return
     */
    @Delete("delete from t_dict where dict_id = #{dictId}")
    int deleteDict(Long dictId);
}

　　(4)测试

    @Test
    public void testInsertDict() {
        dictDao.insertDict("user_type", "0", "管理员");
        dictDao.insertDict("user_type", "1", "操作员");
    }

    @Test
    public void testDeleteDict() {
        dictDao.deleteDict(1L);
        dictDao.deleteDict(2L);
    }