SQLserver中cube:多维数据集实例详解

(编辑:jimmy 日期: 2024/12/28 浏览:2)

1、cube:生成多维数据集,包含各维度可能组合的交叉表格,使用with 关键字连接 with cube

根据需要使用union all 拼接

判断 某一列的null值来自源数据还是 cube 使用GROUPING关键字

GROUPING([档案号]) = 1 : null值来自cube(代表所有的档案号)
GROUPING([档案号]) = 0 : null值来自源数据

举例:

SELECT * INTO ##GET
FROM 
  (SELECT *
    FROM ( SELECT
      CASE
      WHEN (GROUPING([档案号]) = 1) THEN
      '合计'
      ELSE [档案号]
      END AS '档案号',
      CASE
      WHEN (GROUPING([系列]) = 1) THEN
      '合计'
      ELSE [系列]
      END AS '系列',
      CASE
      WHEN (GROUPING([店长]) = 1) THEN
      '合计'
      ELSE [店长]
      END AS '店长', SUM (剩余次数) AS '总剩余',
      CASE
      WHEN (GROUPING([店名]) = 1) THEN
      '合计'
      ELSE [店名]
      END AS '店名'
    FROM ##PudianCard
    GROUP BY [档案号], [店名], [店长], [系列]
    WITH cube
    HAVING GROUPING([店名]) != 1
        AND GROUPING([档案号]) = 1 --AND GROUPING([系列]) = 1 ) AS M
    UNION
    ALL 
      (SELECT *
        FROM ( SELECT
          CASE
          WHEN (GROUPING([档案号]) = 1) THEN
          '合计'
          ELSE [档案号]
          END AS '档案号',
          CASE
          WHEN (GROUPING([系列]) = 1) THEN
          '合计'
          ELSE [系列]
          END AS '系列',
          CASE
          WHEN (GROUPING([店长]) = 1) THEN
          '合计'
          ELSE [店长]
          END AS '店长', SUM (剩余次数) AS '总剩余',
          CASE
          WHEN (GROUPING([店名]) = 1) THEN
          '合计'
          ELSE [店名]
          END AS '店名'
        FROM ##PudianCard
        GROUP BY [档案号], [店名], [店长], [系列]
        WITH cube
        HAVING GROUPING([店名]) != 1
            AND GROUPING([店长]) != 1 ) AS P )
        UNION
        ALL 
          (SELECT *
            FROM ( SELECT
              CASE
              WHEN (GROUPING([档案号]) = 1) THEN
              '合计'
              ELSE [档案号]
              END AS '档案号',
              CASE
              WHEN (GROUPING([系列]) = 1) THEN
              '合计'
              ELSE [系列]
              END AS '系列',
              CASE
              WHEN (GROUPING([店长]) = 1) THEN
              '合计'
              ELSE [店长]
              END AS '店长', SUM (剩余次数) AS '总剩余',
              CASE
              WHEN (GROUPING([店名]) = 1) THEN
              '合计'
              ELSE [店名]
              END AS '店名'
            FROM ##PudianCard
            GROUP BY [档案号], [店名], [店长], [系列]
            WITH cube
            HAVING GROUPING([店名]) != 1
                AND GROUPING([店长]) != 1 ) AS W )
            UNION
            ALL 
              (SELECT *
                FROM ( SELECT
                  CASE
                  WHEN (GROUPING([档案号]) = 1) THEN
                  '合计'
                  ELSE [档案号]
                  END AS '档案号',
                  CASE
                  WHEN (GROUPING([系列]) = 1) THEN
                  '合计'
                  ELSE [系列]
                  END AS '系列',
                  CASE
                  WHEN (GROUPING([店长]) = 1) THEN
                  '合计'
                  ELSE [店长]
                  END AS '店长', SUM (剩余次数) AS '总剩余',
                  CASE
                  WHEN (GROUPING([店名]) = 1) THEN
                  '合计'
                  ELSE [店名]
                  END AS '店名'
                FROM ##PudianCard
                GROUP BY [档案号], [店名], [店长], [系列]
                WITH cube
                HAVING GROUPING([店名]) = 1
                    AND GROUPING([店长]) = 1
                    AND GROUPING([档案号]) = 1 ) AS K ) ) AS T

2、rollup:功能跟cube相似

3、将某一列的数据作为列名,动态加载,使用存储过程,拼接字符串

DECLARE @st nvarchar (MAX) = '';SELECT @st =@st + 'max(case when [系列]=''' + CAST ([系列] AS VARCHAR) + ''' then [总剩余] else null end ) as [' + CAST ([系列] AS VARCHAR) + '],'
FROM ##GET
GROUP BY [系列]; print @st;

4、根据某一列分组,分别建表

SELECT
				'select ROW_NUMBER() over(order by [卡项] desc) as [序号], [会员],[档案号],[卡项],[剩余次数],[员工],[店名] into ' + ltrim([店名]) + ' from 查询 where [店名]=''' + [店名] + ''' ORDER BY [卡项] desc'
		FROM
			查询
		GROUP BY
			[店名]

总结

以上就是本文关于SQLserver中cube:多维数据集实例详解的全部内容,希望对大家有所帮助。感兴趣的朋友可以继续参阅:MYSQL子查询和嵌套查询优化实例解析、几个比较重要的MySQL变量、ORACLE SQL语句优化技术要点解析等,有什么问题可以随时留言,小编会及时回复大家的。感谢各位对本站的支持!

一句话新闻

微软与英特尔等合作伙伴联合定义“AI PC”:键盘需配有Copilot物理按键
几个月来,英特尔、微软、AMD和其它厂商都在共同推动“AI PC”的想法,朝着更多的AI功能迈进。在近日,英特尔在台北举行的开发者活动中,也宣布了关于AI PC加速计划、新的PC开发者计划和独立硬件供应商计划。
在此次发布会上,英特尔还发布了全新的全新的酷睿Ultra Meteor Lake NUC开发套件,以及联合微软等合作伙伴联合定义“AI PC”的定义标准。