如何统计全天各个时间段产品销量情况（sqlserver）

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

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