你的位置:首页 > 数据库

[数据库]全天各个时间段产品销量情况统计


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

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')

View Code

2.补全24小时的数据

/*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       )

View Code

3.行转列

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

View Code

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