如何統計全天各個時間段產品銷量情況（sqlserver）

數據庫環境：SQL SERVER 2005

現有一個產品銷售實時表，表數據如下：

字段name是產品名稱，字段type是銷售類型，1表示售出，2表示退貨，字段num是數量，字段ctime是操作時間。

要求：

　　在一行中統計24小時內所有貨物的銷售（售出，退貨）數據，把日期考慮在內。

分析：

　　這實際上是行轉列的一個應用，在進行行轉列之前，需要補全24小時的所有數據。補全數據可以通過系統的數字輔助表

spt_values來實現，進行行轉列時，根據type和處理後的ctime分組即可。

1.建表，導入數據

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(' 香煙A ', 2,2 ,'2015-08-10 18:21:10')
INSERT INTO snake VALUES(' 香煙A ', 1,5 ,'2015-08-10 20:21:10')
INSERT INTO snake VALUES(' 香煙B', 1,6 ,'2015-08-10 20:21:10')
INSERT INTO snake VALUES(' 香煙B', 2,9 ,'2015-08-10 20:21:10')
INSERT INTO snake VALUES(' 香煙C', 2,9 ,'2015-08-10 20:21:10')

2.補全24小時的數據

/*枚舉0-23自然數列*/
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
       ),/*補全所有日期的24小時*/
    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
       ),/*整理行轉列需要用到的數據*/
    x4
     AS ( SELECT  x2.d ,
            x2.h ,
            x3.name ,
            x3.type ,
            x3.num
        FROM   x2
            LEFT JOIN x3 ON x3.h = x2.h
       )

3.行轉列

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

來看一下最終效果，只有1天的數據，可能看起來不是很直觀。

本文的技術點有2個：

　　1.利用數字輔助表補全缺失的記錄

　　2.pivot行轉列函數的使用

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