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‘)

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
             )

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

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