数据库环境:SQL SERVER 2005
现有一个产品销售实时表,表数据如下:
字段name是产品名称,字段type是销售类型,1表示售出,2表示退货,字段num是数量,字段ctime是操作时间。
要求:
在一行中统计24小时内所有货物的销售(售出,退货)数据,把日期考虑在内。
分析:
这实际上是行转列的一个应用,在进行行转列之前,需要补全24小时的所有数据。补全数据可以通过系统的数字辅助表
spt_values来实现,进行行转列时,根据type和处理后的ctime分组即可。
1.建表,导入数据
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CREATE TABLE snake ( name VARCHAR (10 ),type INT ,num INT , ctime DATETIME ) INSERT INTO snake VALUES ( ' 方便面' , 1,10 , '2015-08-10 16:20:05' ) INSERT INTO snake VALUES ( ' 香烟A ' , 2,2 , '2015-08-10 18:21:10' ) INSERT INTO snake VALUES ( ' 香烟A ' , 1,5 , '2015-08-10 20:21:10' ) INSERT INTO snake VALUES ( ' 香烟B' , 1,6 , '2015-08-10 20:21:10' ) INSERT INTO snake VALUES ( ' 香烟B' , 2,9 , '2015-08-10 20:21:10' ) INSERT INTO snake VALUES ( ' 香烟C' , 2,9 , '2015-08-10 20:21:10' ) |
2.补全24小时的数据
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/*枚举0-23自然数列*/ WITH x0 AS ( SELECT number AS h FROM master..spt_values WHERE type = 'P' AND number >= 0 AND number <= 23 ),/*找出表所有的日期*/ x1 AS ( SELECT DISTINCT CONVERT ( VARCHAR (100), ctime, 23) AS d FROM snake ),/*补全所有日期的24小时*/ x2 AS ( SELECT x1.d , x0.h FROM x1 CROSS JOIN x0 ), x3 AS ( SELECT name , type , num , DATEPART( hour , ctime) AS h FROM snake ),/*整理行转列需要用到的数据*/ x4 AS ( SELECT x2.d , x2.h , x3. name , x3.type , x3.num FROM x2 LEFT JOIN x3 ON x3.h = x2.h ) |
3.行转列
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SELECT ISNULL ([0], 0) AS [00] , ISNULL ([1], 0) AS [01] , ISNULL ([2], 0) AS [02] , ISNULL ([3], 0) AS [03] , ISNULL ([4], 0) AS [04] , ISNULL ([5], 0) AS [05] , ISNULL ([6], 0) AS [06] , ISNULL ([3], 7) AS [07] , ISNULL ([8], 0) AS [08] , ISNULL ([9], 0) AS [09] , ISNULL ([10], 0) AS [10] , ISNULL ([3], 11) AS [11] , ISNULL ([12], 0) AS [12] , ISNULL ([13], 0) AS [13] , ISNULL ([14], 0) AS [14] , ISNULL ([3], 15) AS [15] , ISNULL ([16], 0) AS [16] , ISNULL ([17], 0) AS [17] , ISNULL ([18], 0) AS [18] , ISNULL ([19], 15) AS [19] , ISNULL ([20], 0) AS [20] , ISNULL ([21], 0) AS [21] , ISNULL ([22], 0) AS [22] , ISNULL ([23], 15) AS [23] , type , d AS date FROM ( SELECT d , h , type , num FROM x4 ) t PIVOT( SUM (num) FOR h IN ( [0], [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23] ) ) t WHERE type IS NOT NULL |
来看一下最终效果,只有1天的数据,可能看起来不是很直观。
本文的技术点有2个:
1.利用数字辅助表补全缺失的记录
2.pivot行转列函数的使用
以上内容是如何统计全天各个时间段产品销量情况(sqlserver)的全部内容,希望大家喜欢。