如何在几列的最大值中每行返回1个值:

的表

[Number, Date1, Date2, Date3, Cost]

我需要返回这样的东西:

[Number, Most_Recent_Date, Cost]

查询?


当前回答

下面是使用T-SQL和SQL Server实现Max功能的另一个很好的解决方案

SELECT [Other Fields],
  (SELECT Max(v) 
   FROM (VALUES (date1), (date2), (date3),...) AS value(v)) as [MaxDate]
FROM [YourTableName]

Values是表值构造函数。

"指定要构造到表中的一组行值表达式。Transact-SQL表值构造函数允许在单个DML语句中指定多行数据。表值构造函数可以指定为INSERT…VALUES语句,或者作为MERGE语句的USING子句或FROM子句中的派生表。

其他回答

Scalar Function cause all sorts of performance issues, so its better to wrap the logic into an Inline Table Valued Function if possible. This is the function I used to replace some User Defined Functions which selected the Min/Max dates from a list of upto ten dates. When tested on my dataset of 1 Million rows the Scalar Function took over 15 minutes before I killed the query the Inline TVF took 1 minute which is the same amount of time as selecting the resultset into a temporary table. To use this call the function from either a subquery in the the SELECT or a CROSS APPLY.

CREATE FUNCTION dbo.Get_Min_Max_Date
(
    @Date1  datetime,
    @Date2  datetime,
    @Date3  datetime,
    @Date4  datetime,
    @Date5  datetime,
    @Date6  datetime,
    @Date7  datetime,
    @Date8  datetime,
    @Date9  datetime,
    @Date10 datetime
)
RETURNS TABLE
AS
RETURN
(
    SELECT      Max(DateValue)  Max_Date,
                Min(DateValue)  Min_Date
    FROM        (
                    VALUES  (@Date1),
                            (@Date2),
                            (@Date3),
                            (@Date4),
                            (@Date5),
                            (@Date6),
                            (@Date7),
                            (@Date8),
                            (@Date9),
                            (@Date10)
                )   AS Dates(DateValue)
)

不幸的是,拉斯的答案虽然看似显而易见,但却有一个关键的缺陷。它不能处理NULL值。任何一个NULL值都会返回Date1。不幸的是,任何试图解决这个问题的尝试往往会变得非常混乱,并且不能很好地扩展到4或更多的值。

Databyss的第一个答案看起来(现在也是)不错。但是,不清楚答案是否可以轻易地从多表连接中推断出3个值,而不是从单个表中推断出3个值。我想避免将这样的查询变成子查询,只是为了得到最多3列,而且我非常确定databyss的优秀想法可以被清理一点。

废话不多说,下面是我的解决方案(源自databyss的想法)。 它使用交叉连接选择常量来模拟多表连接的效果。需要注意的重要一点是,所有必要的别名都可以正确地执行(并非总是如此),这使得模式非常简单,并且可以通过额外的列进行相当的可伸缩性。

DECLARE @v1 INT ,
        @v2 INT ,
        @v3 INT
--SET @v1 = 1 --Comment out SET statements to experiment with 
              --various combinations of NULL values
SET @v2 = 2
SET @v3 = 3

SELECT  ( SELECT    MAX(Vals)
          FROM      ( SELECT    v1 AS Vals
                      UNION
                      SELECT    v2
                      UNION
                      SELECT    v3
                    ) tmp
          WHERE     Vals IS NOT NULL -- This eliminates NULL warning

        ) AS MaxVal
FROM    ( SELECT    @v1 AS v1
        ) t1
        CROSS JOIN ( SELECT @v2 AS v2
                   ) t2
        CROSS JOIN ( SELECT @v3 AS v3
                   ) t3

请尝试使用UNPIVOT:

SELECT MAX(MaxDt) MaxDt
   FROM tbl 
UNPIVOT
   (MaxDt FOR E IN 
      (Date1, Date2, Date3)
)AS unpvt;

我更喜欢基于case-when的解决方案,我的假设是,与其他可能的解决方案(如交叉应用、values()、自定义函数等)相比,它对可能的性能下降的影响应该最小。

下面是case-when版本,它在大多数可能的测试用例中处理空值:

SELECT
    CASE 
        WHEN Date1 > coalesce(Date2,'0001-01-01') AND Date1 > coalesce(Date3,'0001-01-01') THEN Date1 
        WHEN Date2 > coalesce(Date3,'0001-01-01') THEN Date2 
        ELSE Date3
    END AS MostRecentDate
    , *
from 
(values
     (  1, cast('2001-01-01' as Date), cast('2002-01-01' as Date), cast('2003-01-01' as Date))
    ,(  2, cast('2001-01-01' as Date), cast('2003-01-01' as Date), cast('2002-01-01' as Date))
    ,(  3, cast('2002-01-01' as Date), cast('2001-01-01' as Date), cast('2003-01-01' as Date))
    ,(  4, cast('2002-01-01' as Date), cast('2003-01-01' as Date), cast('2001-01-01' as Date))
    ,(  5, cast('2003-01-01' as Date), cast('2001-01-01' as Date), cast('2002-01-01' as Date))
    ,(  6, cast('2003-01-01' as Date), cast('2002-01-01' as Date), cast('2001-01-01' as Date))
    ,( 11, cast(NULL         as Date), cast('2002-01-01' as Date), cast('2003-01-01' as Date))
    ,( 12, cast(NULL         as Date), cast('2003-01-01' as Date), cast('2002-01-01' as Date))
    ,( 13, cast('2003-01-01' as Date), cast(NULL         as Date), cast('2002-01-01' as Date))
    ,( 14, cast('2002-01-01' as Date), cast(NULL         as Date), cast('2003-01-01' as Date))
    ,( 15, cast('2003-01-01' as Date), cast('2002-01-01' as Date), cast(NULL         as Date))
    ,( 16, cast('2002-01-01' as Date), cast('2003-01-01' as Date), cast(NULL         as Date))
    ,( 21, cast('2003-01-01' as Date), cast(NULL         as Date), cast(NULL         as Date))
    ,( 22, cast(NULL         as Date), cast('2003-01-01' as Date), cast(NULL         as Date))
    ,( 23, cast(NULL         as Date), cast(NULL         as Date), cast('2003-01-01' as Date))
    ,( 31, cast(NULL         as Date), cast(NULL         as Date), cast(NULL         as Date))

) as demoValues(id, Date1,Date2,Date3)
order by id
;

结果是:

MostRecent    id   Date1      Date2      Date3
2003-01-01    1    2001-01-01 2002-01-01 2003-01-01
2003-01-01    2    2001-01-01 2003-01-01 2002-01-01
2003-01-01    3    2002-01-01 2001-01-01 2002-01-01
2003-01-01    4    2002-01-01 2003-01-01 2001-01-01
2003-01-01    5    2003-01-01 2001-01-01 2002-01-01
2003-01-01    6    2003-01-01 2002-01-01 2001-01-01
2003-01-01    11   NULL       2002-01-01 2003-01-01
2003-01-01    12   NULL       2003-01-01 2002-01-01
2003-01-01    13   2003-01-01 NULL       2002-01-01
2003-01-01    14   2002-01-01 NULL       2003-01-01
2003-01-01    15   2003-01-01 2002-01-01 NULL
2003-01-01    16   2002-01-01 2003-01-01 NULL
2003-01-01    21   2003-01-01 NULL       NULL
2003-01-01    22   NULL       2003-01-01 NULL
2003-01-01    23   NULL       NULL       2003-01-01
NULL          31   NULL       NULL       NULL

这里有一个很好的解决方案:

CREATE function [dbo].[inLineMax] (@v1 float,@v2 float,@v3 float,@v4 float)
returns float
as
begin
declare @val float
set @val = 0 
declare @TableVal table
(value float )
insert into @TableVal select @v1
insert into @TableVal select @v2
insert into @TableVal select @v3
insert into @TableVal select @v4

select @val= max(value) from @TableVal

return @val
end