对于SQL Server，我希望通过在给定的时间间隔内求平均值来汇总数据
数据如下：对于SQL Server，我希望通过在给定的时间间隔内求平均值来汇总数据,sql,sql-server,time,intervals,Sql,Sql Server,Time,Intervals,数据如下： Time_Stamp(Datetime) Value (real) --------- ----- 12:01 1.3 12:02 1.7 12:04 2.0 12:08 1.8 12:11 1.1 12:12
Time_Stamp(Datetime) Value (real)
--------- -----
12:01 1.3
12:02 1.7
12:04 2.0
12:08 1.8
12:11 1.1
12:12 2.0
Timestamp Value
--------- ------
12:00 1.66
12:05 1.8
12:10 1.55
关于我经常使用TVF创建动态日期/时间范围。理货台也可以做到这一点。UDF比递归cte更快，并提供更多的功能，即定义日期范围、日期部分和增量
SELECT Timestamp,
AVG( VALUE ) AS Value
FROM
(
SELECT CASE WHEN Timestamp BETWEEN 12:00 AND 12:05 THEN 12:00
WHEN Timestamp BETWEEN 12:05 AND 12:10 THEN 12:05
WHEN Timestamp BETWEEN 12:10 AND 12:15 THEN 12:10
END AS Timestamp,
VALUE
FROM data
)
GROUP BY Timestamp;
Declare @YourTable table (Timestamp time,Value money)
Insert Into @YourTable values
('12:01',1.3),
('12:02',1.7),
('12:04',2.0),
('12:08',1.8),
('12:11',1.1),
('12:12',2.0)
Select TimeStamp=R1
,Average=Avg(Value)
From (Select RetSeq,R1=cast(RetVal as Time),R2=cast(DateAdd(MI,5,RetVal) as Time) from [dbo].[udf-Range-Date]('1900-01-01','1900-01-02','MI',5)) A
Join @YourTable B on B.TimeStamp>=A.R1 and B.TimeStamp<A.R2
Group By R1
Order By R1
CREATE FUNCTION [dbo].[udf-Range-Date] (@R1 datetime,@R2 datetime,@Part varchar(10),@Incr int)
Returns Table
Return (
with cte0(M) As (Select 1+Case @Part When 'YY' then DateDiff(YY,@R1,@R2)/@Incr When 'QQ' then DateDiff(QQ,@R1,@R2)/@Incr When 'MM' then DateDiff(MM,@R1,@R2)/@Incr When 'WK' then DateDiff(WK,@R1,@R2)/@Incr When 'DD' then DateDiff(DD,@R1,@R2)/@Incr When 'HH' then DateDiff(HH,@R1,@R2)/@Incr When 'MI' then DateDiff(MI,@R1,@R2)/@Incr When 'SS' then DateDiff(SS,@R1,@R2)/@Incr End),
cte1(N) As (Select 1 From (Values(1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) N(N)),
cte2(N) As (Select Top (Select M from cte0) Row_Number() over (Order By (Select NULL)) From cte1 a, cte1 b, cte1 c, cte1 d, cte1 e, cte1 f, cte1 g, cte1 h ),
cte3(N,D) As (Select 0,@R1 Union All Select N,Case @Part When 'YY' then DateAdd(YY, N*@Incr, @R1) When 'QQ' then DateAdd(QQ, N*@Incr, @R1) When 'MM' then DateAdd(MM, N*@Incr, @R1) When 'WK' then DateAdd(WK, N*@Incr, @R1) When 'DD' then DateAdd(DD, N*@Incr, @R1) When 'HH' then DateAdd(HH, N*@Incr, @R1) When 'MI' then DateAdd(MI, N*@Incr, @R1) When 'SS' then DateAdd(SS, N*@Incr, @R1) End From cte2 )
Select RetSeq = N+1
,RetVal = D
From cte3,cte0
Where D<=@R2
)
/*
Max 100 million observations -- Date Parts YY QQ MM WK DD HH MI SS
Syntax:
Select * from [dbo].[udf-Range-Date]('2016-10-01','2020-10-01','YY',1)
Select * from [dbo].[udf-Range-Date]('2016-01-01','2017-01-01','MM',1)
我经常使用TVF创建动态日期/时间范围。理货台也可以做到这一点。UDF比递归cte更快，并提供更多的功能，即定义日期范围、日期部分和增量
Declare @YourTable table (Timestamp time,Value money)
Insert Into @YourTable values
('12:01',1.3),
('12:02',1.7),
('12:04',2.0),
('12:08',1.8),
('12:11',1.1),
('12:12',2.0)
Select TimeStamp=R1
,Average=Avg(Value)
From (Select RetSeq,R1=cast(RetVal as Time),R2=cast(DateAdd(MI,5,RetVal) as Time) from [dbo].[udf-Range-Date]('1900-01-01','1900-01-02','MI',5)) A
Join @YourTable B on B.TimeStamp>=A.R1 and B.TimeStamp<A.R2
Group By R1
Order By R1
CREATE FUNCTION [dbo].[udf-Range-Date] (@R1 datetime,@R2 datetime,@Part varchar(10),@Incr int)
Returns Table
Return (
with cte0(M) As (Select 1+Case @Part When 'YY' then DateDiff(YY,@R1,@R2)/@Incr When 'QQ' then DateDiff(QQ,@R1,@R2)/@Incr When 'MM' then DateDiff(MM,@R1,@R2)/@Incr When 'WK' then DateDiff(WK,@R1,@R2)/@Incr When 'DD' then DateDiff(DD,@R1,@R2)/@Incr When 'HH' then DateDiff(HH,@R1,@R2)/@Incr When 'MI' then DateDiff(MI,@R1,@R2)/@Incr When 'SS' then DateDiff(SS,@R1,@R2)/@Incr End),
cte1(N) As (Select 1 From (Values(1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) N(N)),
cte2(N) As (Select Top (Select M from cte0) Row_Number() over (Order By (Select NULL)) From cte1 a, cte1 b, cte1 c, cte1 d, cte1 e, cte1 f, cte1 g, cte1 h ),
cte3(N,D) As (Select 0,@R1 Union All Select N,Case @Part When 'YY' then DateAdd(YY, N*@Incr, @R1) When 'QQ' then DateAdd(QQ, N*@Incr, @R1) When 'MM' then DateAdd(MM, N*@Incr, @R1) When 'WK' then DateAdd(WK, N*@Incr, @R1) When 'DD' then DateAdd(DD, N*@Incr, @R1) When 'HH' then DateAdd(HH, N*@Incr, @R1) When 'MI' then DateAdd(MI, N*@Incr, @R1) When 'SS' then DateAdd(SS, N*@Incr, @R1) End From cte2 )
Select RetSeq = N+1
,RetVal = D
From cte3,cte0
Where D<=@R2
)
/*
Max 100 million observations -- Date Parts YY QQ MM WK DD HH MI SS
Syntax:
Select * from [dbo].[udf-Range-Date]('2016-10-01','2020-10-01','YY',1)
Select * from [dbo].[udf-Range-Date]('2016-01-01','2017-01-01','MM',1)
一种技术是创建一个。您可以将所需的任何字段添加到此表中，从而为分组提供依据 此示例用于返回一个简单的时间表，以便于说明。在您的数据库中，我建议您创建一个适当的表
-- Sample time table.
WITH DimTime AS
(
-- Returns one record for each minute of the day.
SELECT
CAST('00:00:00' AS TIME(0)) AS TimeKey,
0 AS [Hour],
1 AS AM
UNION ALL
SELECT
c.NextMinute AS TimeKey,
DATEPART(HOUR, c.NextMinute) AS [Hour],
CASE WHEN DATEPART(HOUR, c.NextMinute) < 12 THEN 1 ELSE 0 END AS AM
FROM
DimTime AS t
CROSS APPLY
(
VALUES
(DATEADD(MINUTE, 1, TimeKey))
) AS c(NextMinute)
WHERE
t.TimeKey < CAST('23:59:00' AS TIME(0))
)
SELECT
*
FROM
DimTime
OPTION
(MAXRECURSION 1440)
;
添加一个按五分钟间隔调用内容的列将简化您的最终查询。一种技术是创建一个。您可以将所需的任何字段添加到此表中，从而为分组提供依据 此示例用于返回一个简单的时间表，以便于说明。在您的数据库中，我建议您创建一个适当的表
-- Sample time table.
WITH DimTime AS
(
-- Returns one record for each minute of the day.
SELECT
CAST('00:00:00' AS TIME(0)) AS TimeKey,
0 AS [Hour],
1 AS AM
UNION ALL
SELECT
c.NextMinute AS TimeKey,
DATEPART(HOUR, c.NextMinute) AS [Hour],
CASE WHEN DATEPART(HOUR, c.NextMinute) < 12 THEN 1 ELSE 0 END AS AM
FROM
DimTime AS t
CROSS APPLY
(
VALUES
(DATEADD(MINUTE, 1, TimeKey))
) AS c(NextMinute)
WHERE
t.TimeKey < CAST('23:59:00' AS TIME(0))
)
SELECT
*
FROM
DimTime
OPTION
(MAXRECURSION 1440)
;
添加一个按FiuMeUnTealStudio调用某个列的列将简化您最后的查询。
时间戳列的数据类型是什么？TimeyType是DatetimeYou真正应该考虑使用与时间戳不同的名称。这是完全不明确的意思。日期是否已创建、更新？也许是截止日期？当然，时间戳是SQL Server中与时间无关的数据类型。选择RealtDeaTePMI、时间戳、1 +情况时，RealDATePARTMI、时间戳、TimeType列的数据类型是什么？TimeType是DatetimeYou真正应该考虑使用与时间戳不同的名称。这是完全不明确的意思。日期是否已创建、更新？也许是截止日期？当然，时间戳是sql server中与时间无关的数据类型。选择leftdatepartmi，timestamp，1+case，当选择rightdatepartmi，timestamp，1此解决方案特定于示例中的数据集，对任何试图以常规方式实现此功能的人都没有用处。谢谢@Teja我感谢您的输入。此解决方案特定于示例中的数据集，对任何试图以常规方式实现此功能的人都没有用处。谢谢@Teja我感谢您的输入。谢谢@JohnCappelleti你的答案我会在小调整后使用。谢谢@John Cappelleti你的答案我会在小调整后使用。