若何統計全天各個時光段產物銷量情形(sqlserver)。本站提示廣大學習愛好者:(若何統計全天各個時光段產物銷量情形(sqlserver))文章只能為提供參考,不一定能成為您想要的結果。以下是若何統計全天各個時光段產物銷量情形(sqlserver)正文
數據庫情況:SQL SERVER 2005
現有一個產物發賣及時表,表數據以下:

字段name是產物稱號,字段type是發賣類型,1表現售出,2表現退貨,字段num是數目,字段ctime是操作時光。
請求:
在一行中統計24小時內一切貨色的發賣(售出,退貨)數據,把日期斟酌在內。
剖析:
這現實上是行轉列的一個運用,在停止行轉列之前,須要補全24小時的一切數據。補全數據可以經由過程體系的數字幫助表
spt_values來完成,停止行轉列時,依據type和處置後的ctime分組便可。
1.建表,導入數據
CREATE TABLE snake (name VARCHAR(10 ),type INT,num INT, ctime DATETIME )
INSERT INTO snake VALUES(' 便利面', 1,10 ,'2015-08-10 16:20:05')
INSERT INTO snake VALUES(' 噴鼻煙A ', 2,2 ,'2015-08-10 18:21:10')
INSERT INTO snake VALUES(' 噴鼻煙A ', 1,5 ,'2015-08-10 20:21:10')
INSERT INTO snake VALUES(' 噴鼻煙B', 1,6 ,'2015-08-10 20:21:10')
INSERT INTO snake VALUES(' 噴鼻煙B', 2,9 ,'2015-08-10 20:21:10')
INSERT INTO snake VALUES(' 噴鼻煙C', 2,9 ,'2015-08-10 20:21:10')
2.補全24小時的數據
/*列舉0-23天然數列*/
WITH x0
AS ( SELECT number AS h
FROM master..spt_values
WHERE type = 'P'
AND number >= 0
AND number <= 23
),/*找出表一切的日期*/
x1
AS ( SELECT DISTINCT
CONVERT(VARCHAR(100), ctime, 23) AS d
FROM snake
),/*補全一切日期的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
),/*整頓行轉列須要用到的數據*/
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
來看一下終究後果,只要1天的數據,能夠看起來不是很直不雅。

本文的技巧點有2個:
1.應用數字幫助表補全缺掉的記載
2.pivot行轉列函數的應用
以上內容是若何統計全天各個時光段產物銷量情形(sqlserver)的全體內容,願望年夜家愛好。