SELECT CASE WHEN grouping(fskgk) = 1 THEN '合计' ELSE fskgk END AS fskgk, SUM(fssjejn) AS fssjejn, SUM(fssjeqn) AS fssjeqn , SUM(fssjedqn) AS fssjedqn, SUM(fhsjn) AS fhsjn , SUM(fhsqn) AS fhsqn, SUM(fhsdqn) AS fhsdqn , round(decode(SUM(fssjeqn), 0, 0, (SUM(fssjejn) - SUM(fssjeqn)) / SUM(fssjeqn)) * 100, 2) AS fcsbjn , round(decode(SUM(fssjedqn), 0, 0, (SUM(fssjeqn) - SUM(fssjedqn)) / SUM(fssjedqn)) * 100, 2) AS fcsbqn , round(decode(SUM(fhsqn), 0, 0, (SUM(fhsjn) - SUM(fhsqn)) / SUM(fhsqn)) * 100, 2) AS hjbjn , round(decode(SUM(fhsdqn), 0, 0, (SUM(fhsqn) - SUM(fhsdqn)) / SUM(fhsdqn)) * 100, 2) AS hjbqn FROM ( SELECT fskgk , round(SUM(fssjejn) / 10000, 2) AS fssjejn , round(SUM(fssjeqn) / 10000, 2) AS fssjeqn , round(SUM(fssjedqn) / 10000, 2) AS fssjedqn , nvl(SUM(fhsjn), 0) AS fhsjn , nvl(SUM(fhsqn), 0) AS fhsqn , nvl(SUM(fhsdqn), 0) AS fhsdqn FROM ( SELECT substr(frkrq, 1, 4) AS fyears, fskgk , SUM(车船税) AS fssjejn, 0 AS fssjeqn, 0 AS fssjedqn FROM zhzs_srfx_ss_all WHERE substr(frkrq, 1, 4)='2023' GROUP BY fskgk, substr(frkrq, 1, 4) UNION ALL SELECT substr(frkrq, 1, 4)AS fyears, fskgk , 0 AS fssjejn, SUM(车船税) AS fssjeqn, 0 AS fssjedqn FROM zhzs_srfx_ss_all WHERE substr(frkrq, 1, 4)='2022' GROUP BY fskgk, substr(frkrq, 1, 4) UNION ALL SELECT substr(frkrq, 1, 4)AS fyears, fskgk , 0 AS fssjejn, 0 AS fssjeqn, SUM(车船税) AS fssjedqn FROM zhzs_srfx_ss_all WHERE substr(frkrq, 1, 4)='2021' GROUP BY fskgk, substr(frkrq, 1, 4) ) a left JOIN ( SELECT substr(fcldjsj, 1, 4) AS years, fssqx , fclspswl AS fhsjn, '0' AS fhsqn, '0' AS fhsdqn FROM zhzs_bill_clspdjxx WHERE substr(fcldjsj, 1, 4) = '2023' GROUP BY substr(fcldjsj, 1, 4), fssqx, fclspswl UNION ALL SELECT substr(fcldjsj, 1, 4) AS years, fssqx , '0' AS fhsjn, fclspswl AS fhsqn, '0' AS fhsdqn FROM zhzs_bill_clspdjxx WHERE substr(fcldjsj, 1, 4) = '2022' GROUP BY substr(fcldjsj, 1, 4), fssqx, fclspswl UNION ALL SELECT substr(fcldjsj, 1, 4) AS years, fssqx , '0' AS fhsjn, '0' AS fhsqn, fclspswl AS fhsdqn FROM zhzs_bill_clspdjxx WHERE substr(fcldjsj, 1, 4) = '2021' GROUP BY substr(fcldjsj, 1, 4), fssqx, fclspswl ) b ON a.fyears = b.years and a.fskgk = b.fssqx GROUP BY fskgk ) GROUP BY ROLLUP (fskgk) ORDER BY CASE WHEN fskgk = '合计' THEN 1 ELSE 2 END

这是一段 SQL 查询语句，作用是对一个数据表中的数据进行聚合计算，并且按照一定的规则排序后返回结果。该查询语句主要包括以下几个部分：

1. SELECT 子句：选择需要查询的列，以及对这些列进行聚合计算的函数。

2. FROM 子句：指定需要查询的数据表。

3. WHERE 子句：指定过滤数据的条件。

4. GROUP BY 子句：根据指定的列对数据进行分组。

5. UNION ALL：将多个 SELECT 语句的结果合并成一个结果集。

6. JOIN：将两个数据表进行连接。

7. ROLLUP：对 GROUP BY 的结果进行汇总。

8. ORDER BY：根据指定的规则对结果进行排序。

具体查询的意义需要根据数据表的结构和业务需求进行分析。

相关问题

优化成MYSQL 脚本SELECT 子品牌, 商品数字ID, COUNT(DISTINCT o.用户id) AS new_customer_num, SUM(o.商品实付金额) AS new_customer_商品实付金额 FROM 天猫官旗有效数据 o LEFT JOIN ( -- 找到22年10月30日前有购买行为的客户编号 SELECT 用户id FROM 天猫官旗有效数据 WHERE 支付日期 BETWEEN '2021-10-31' AND '2022-10-30' GROUP BY 用户id ) old_c ON o.用户id = old_c.用户id WHERE o.支付日期 >= '2022-10-31' AND o.支付日期 <= '2022-11-11' AND NOT EXISTS ( SELECT 1 FROM 天猫官旗有效数据 WHERE 用户id = o.用户id AND 支付日期 BETWEEN '2021-10-31' AND '2022-10-30') GROUP BY GROUPING SETS ((子品牌, 商品数字ID))

以下是优化后的MYSQL脚本：

SELECT
子品牌,
商品数字ID,
COUNT(DISTINCT CASE WHEN o.支付日期 >= '2022-10-31' AND o.支付日期 <= '2022-11-11' AND old_c.用户id IS NULL THEN o.用户id ELSE NULL END) AS new_customer_num,
SUM(CASE WHEN o.支付日期 >= '2022-10-31' AND o.支付日期 <= '2022-11-11' AND old_c.用户id IS NULL THEN o.商品实付金额 ELSE 0 END) AS new_customer_商品实付金额
FROM 天猫官旗有效数据 o
LEFT JOIN (
SELECT 用户id
FROM 天猫官旗有效数据
WHERE 支付日期 BETWEEN '2021-10-31' AND '2022-10-30'
GROUP BY 用户id
) old_c ON o.用户id = old_c.用户id
WHERE o.支付日期 >= '2022-10-31' AND o.支付日期 <= '2022-11-11'
GROUP BY 子品牌, 商品数字ID;

这里进行了以下优化：
1. CASE语句替代NOT EXISTS子查询，提高查询效率。
2. 将GROUPING SETS修改为普通的GROUP BY语句，简化查询语句。
3. 将条件判断移动到CASE语句中，减少不必要的计算。

mysql简单的行转列

MySQL中行转列操作可以使用PIVOT函数或者CASE WHEN语句来实现。具体实现方法如下：

1. PIVOT函数

PIVOT函数可以将一列数据转换成多列，使用方法如下：

SELECT 
    [Grouping Column], 
    [Pivot Column 1], [Pivot Column 2],..., [Pivot Column N]
FROM
    [Source Table]
PIVOT
(
    [Aggregation Function]([Value Column])
    FOR [Pivot Column] IN ([Pivot Column 1], [Pivot Column 2],..., [Pivot Column N])
) AS [Pivot Table];

其中，[Grouping Column]是需要分组的列名，[Pivot Column 1], [Pivot Column 2],..., [Pivot Column N]是需要转换的列名，[Aggregation Function]是聚合函数（如SUM、AVG等），[Value Column]是需要聚合的值列名，[Source Table]是源数据表名，[Pivot Table]是输出的表名。

例如，将学生的成绩按科目进行转换：

SELECT 
    name,
    MAX(CASE WHEN subject = 'Math' THEN score ELSE NULL END) AS Math,
    MAX(CASE WHEN subject = 'English' THEN score ELSE NULL END) AS English,
    MAX(CASE WHEN subject = 'Science' THEN score ELSE NULL END) AS Science
FROM 
    scores
GROUP BY 
    name;

2. CASE WHEN语句

使用CASE WHEN语句可以将多个行转换成一行，使用方法如下：

SELECT 
    [Grouping Column],
    MAX(CASE WHEN [Condition 1] THEN [Value 1] ELSE NULL END) AS [Pivot Column 1],
    MAX(CASE WHEN [Condition 2] THEN [Value 2] ELSE NULL END) AS [Pivot Column 2],
    ...,
    MAX(CASE WHEN [Condition N] THEN [Value N] ELSE NULL END) AS [Pivot Column N]
FROM 
    [Source Table]
GROUP BY 
    [Grouping Column];

其中，[Grouping Column]是需要分组的列名，[Condition 1], [Condition 2],..., [Condition N]是条件语句，[Value 1], [Value 2],..., [Value N]是需要转换的列名，[Source Table]是源数据表名。

例如，将学生的成绩进行转换：

SELECT 
    name,
    MAX(CASE WHEN subject = 'Math' THEN score ELSE NULL END) AS Math,
    MAX(CASE WHEN subject = 'English' THEN score ELSE NULL END) AS English,
    MAX(CASE WHEN subject = 'Science' THEN score ELSE NULL END) AS Science
FROM 
    scores
GROUP BY 
    name;