使用SQL Server生成15分鍾插槽的數據平均值

Question

我有一個SQL Server表，如下所示。

CREATE TABLE [dbo].[ChannelData](
[Id] [int] IDENTITY(1,1) NOT NULL,
[ChannelId] [int] NOT NULL,
[ChannelValue] [decimal](10, 2) NULL,
[ChannelDataLogTime] [datetime] NOT NULL,
[Active] [bit] NULL,CONSTRAINT [PK_ChannelData] PRIMARY KEY CLUSTERED ( [Id] ASC )WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY]) ON [PRIMARY] 

示例數據如下：::

+----+-----------+--------------+-------------------------+--------+
| Id | ChannelId | ChannelValue |   ChannelDataLogTime    | Active |
+----+-----------+--------------+-------------------------+--------+
|  1 |         9 |         5.46 | 2015-06-09 14:00:11.463 |      1 |
|  2 |         9 |         8.46 | 2015-06-09 14:01:11.503 |      1 |
|  3 |         9 |         3.46 | 2015-06-09 14:02:27.747 |      1 |
|  4 |         9 |         6.46 | 2015-06-09 14:03:11.503 |      1 |
|  5 |         9 |         1.46 | 2015-06-09 14:04:11.530 |      1 |
|  6 |         9 |         4.46 | 2015-06-09 14:05:11.537 |      1 |
|  7 |         9 |         7.46 | 2015-06-09 14:06:11.547 |      1 |
|  8 |         9 |         2.46 | 2015-06-09 14:07:33.983 |      1 |
|  9 |         9 |         5.46 | 2015-06-09 14:08:11.570 |      1 |
| 10 |         9 |         8.46 | 2015-06-09 14:09:11.603 |      1 |
| 11 |         9 |         3.46 | 2015-06-09 14:10:11.613 |      1 |
| 12 |         9 |         6.47 | 2015-06-09 14:11:11.623 |      1 |
| 13 |         9 |         1.47 | 2015-06-09 14:12:24.497 |      1 |
| 14 |         9 |         4.47 | 2015-06-09 14:13:11.623 |      1 |
| 15 |         9 |         7.47 | 2015-06-09 14:14:11.650 |      1 |
| 16 |         9 |         2.47 | 2015-06-09 14:15:11.707 |      1 |
| 17 |         9 |         5.47 | 2015-06-09 14:16:11.707 |      1 |
| 18 |         9 |         8.47 | 2015-06-09 14:17:25.647 |      1 |
| 19 |         9 |         3.47 | 2015-06-09 14:18:11.707 |      1 |
| 20 |         9 |         6.47 | 2015-06-09 14:19:11.753 |      1 |
| 21 |         9 |         1.47 | 2015-06-09 14:20:11.760 |      1 |
| 22 |         9 |         4.47 | 2015-06-09 14:21:11.790 |      1 |
| 23 |         9 |         7.47 | 2015-06-09 14:22:29.500 |      1 |
| 24 |         9 |         2.47 | 2015-06-09 14:23:11.907 |      1 |
| 25 |         9 |         5.47 | 2015-06-09 14:24:12.057 |      1 |
| 26 |         9 |         8.47 | 2015-06-09 14:25:11.817 |      1 |
| 27 |         9 |         3.47 | 2015-06-09 14:26:11.837 |      1 |
| 28 |         9 |         6.47 | 2015-06-09 14:27:32.253 |      1 |
| 29 |         9 |         1.47 | 2015-06-09 14:28:11.870 |      1 |
| 30 |         9 |         4.47 | 2015-06-09 14:29:11.870 |      1 |
| 31 |         9 |         7.50 | 2015-06-09 16:00:13.313 |      1 |
| 32 |         9 |         2.50 | 2015-06-09 16:01:13.260 |      1 |
| 33 |         9 |         5.50 | 2015-06-09 16:02:13.290 |      1 |
| 34 |         9 |         8.50 | 2015-06-09 16:03:13.270 |      1 |
| 35 |         9 |         3.50 | 2015-06-09 16:04:32.827 |      1 |
| 36 |         9 |         6.50 | 2015-06-09 16:05:13.323 |      1 |
| 37 |         9 |         1.50 | 2015-06-09 16:06:13.330 |      1 |
| 38 |         9 |         4.50 | 2015-06-09 16:07:13.337 |      1 |
| 39 |         9 |         7.50 | 2015-06-09 16:08:13.313 |      1 |
| 40 |         9 |         2.50 | 2015-06-09 16:09:28.497 |      1 |
| 41 |         9 |         5.50 | 2015-06-09 16:10:13.370 |      1 |
| 42 |         9 |         8.50 | 2015-06-09 16:11:13.417 |      1 |
| 43 |         9 |         3.50 | 2015-06-09 16:12:13.540 |      1 |
| 44 |         9 |         6.50 | 2015-06-09 16:13:13.577 |      1 |
| 45 |         9 |         1.50 | 2015-06-09 16:14:33.880 |      1 |
| 46 |         9 |         4.50 | 2015-06-09 16:15:13.453 |      1 |
| 47 |         9 |         7.50 | 2015-06-09 16:16:13.500 |      1 |
| 48 |         9 |         2.50 | 2015-06-09 16:17:13.497 |      1 |
| 49 |         9 |         5.50 | 2015-06-09 16:18:13.503 |      1 |
| 50 |         9 |         8.50 | 2015-06-09 16:19:38.717 |      1 |
| 51 |         9 |         3.50 | 2015-06-09 16:21:13.567 |      1 |
| 52 |         9 |         6.50 | 2015-06-09 16:22:13.557 |      1 |
| 53 |         9 |         1.50 | 2015-06-09 16:23:14.163 |      1 |
| 54 |         9 |         4.50 | 2015-06-09 16:24:13.607 |      1 |
| 55 |         9 |         7.50 | 2015-06-09 16:25:38.783 |      1 |
| 56 |         9 |         2.50 | 2015-06-09 16:27:13.660 |      1 |
| 57 |         9 |         5.51 | 2015-06-09 16:28:13.710 |      1 |
| 58 |         9 |         8.51 | 2015-06-09 16:29:13.703 |      1 |
| 59 |         9 |         3.51 | 2015-06-09 16:30:13.713 |      1 |
+----+-----------+--------------+-------------------------+--------+

現在，我將在一段時間內生成15分鍾的平均數據，包括開始日期和結束日期。 可以很好地解決任何問題。

我遇到的情況是數據會丟失一段時間。 由於缺少15分鍾時隙的數據，因此又錯過了15分鍾時隙。 我需要的是列出15分鍾的時間段，即使使用SQL查詢在該時間段內數據不可用。

SELECT
                            Avg(chnldata.ChannelValue)  AS ChannelValue,
                            DATEADD(minute,FLOOR(DATEDIFF(minute,0,ChannelDataLogTime)/15)*15,0) as HourlyDateTime,
                           chnldata.ChannelId as Id
                    FROM ChannelData as chnldata
                    WHERE  chnldata.ChannelId in (9) AND chnldata.ChannelDataLogTime >= '06/09/2015'  AND chnldata.ChannelDataLogTime < '06/11/2015 23:59:50' 
                     GROUP BY chnldata.ChannelId, DATEADD(minute,FLOOR(DATEDIFF(minute,0,ChannelDataLogTime)/15)*15,0) 

這是現有的15分鍾平均查詢。 但是它不會顯示缺少15分鍾的廣告位。 當前輸出為：

+--------------+-------------------------+----+
| ChannelValue |     HourlyDateTime      | Id |
+--------------+-------------------------+----+
|     5.129333 | 2015-06-09 14:00:00.000 |  9 |
|     4.803333 | 2015-06-09 14:15:00.000 |  9 |
|     5.033333 | 2015-06-09 16:00:00.000 |  9 |
|     5.270769 | 2015-06-09 16:15:00.000 |  9 |
|     3.510000 | 2015-06-09 16:30:00.000 |  9 |
+--------------+-------------------------+----+

所需的輸出是：::

+--------------+-------------------------+----+
| ChannelValue |     HourlyDateTime      | Id |
+--------------+-------------------------+----+
| 5.129333     | 2015-06-09 14:00:00.000 |  9 |
| 4.803333     | 2015-06-09 14:15:00.000 |  9 |
| NULL         | 2015-06-09 14:30:00.000 |  9 |
| NULL         | 2015-06-09 14:45:00.000 |  9 |
| NULL         | 2015-06-09 15:00:00.000 |  9 |
| NULL         | 2015-06-09 15:15:00.000 |  9 |
| NULL         | 2015-06-09 15:30:00.000 |  9 |
| NULL         | 2015-06-09 15:45:00.000 |  9 |
| 5.033333     | 2015-06-09 16:00:00.000 |  9 |
| 5.270769     | 2015-06-09 16:15:00.000 |  9 |
| 3.510000     | 2015-06-09 16:30:00.000 |  9 |
+--------------+-------------------------+----+

Answer 1

正確加入CTE，該CTE在您的時間范圍內具有所有可能的15分鍾間隔。

Answer 2

建立時間范圍的CTE，可以通過多種方式完成，但是笛卡爾乘積法可能比許多方法要快，如果您想提高速度，最好建立一個靜態日期表，也許還有一個日期和時間表

;WITH mins as (SELECT 0 as q union select 15 union select 30 union select 45),
      dats as (SELECT MIN(ChannelDataLogTime) as t1, max(ChannelDataLogTime) as t2 from channeldata),
      ranges as (SELECT CAST(t1 as date) s1 FROM dats
                union all
                SELECT dateadd(day,1,r.s1) from ranges r where r.s1< (select t2 from dats)
                ),
      hrs as (select 0 h union all select  h + 1 from hrs where h < 23),    --hours 0 to 23
      slots as (select dateadd(MINUTE,mins.q,dateadd(hour,hrs.h,cast(ranges.s1 as datetime2))) as strt from mins,ranges,hrs      ),
      ids as (SELECT distinct  ChannelId from  ChannelData),
      allslot as (select channelid, strt from slots,ids)
        SELECT    count(0) as x,
                            coalesce(Avg(chnldata.ChannelValue)   , 0) AS ChannelValue,
                            s.strt HourlyDateTime,
                           s.ChannelId as Id
                    FROM ChannelData as chnldata
                    RIGHT JOIN  allslot s on s.strt <= ChannelDataLogTime and ChannelDataLogTime < dateadd(minute,15,s.strt) and s.ChannelId = chnldata.ChannelId 
                    WHERE  chnldata.ChannelId is null or chnldata.ChannelId in (9) AND chnldata.ChannelDataLogTime >= '20150906'  AND chnldata.ChannelDataLogTime < '20151123' 
                     GROUP BY s.ChannelId, s.strt

Answer 3

考慮maxrecursion選項的局限性。

DECLARE @StartDT DATETIME = '2015-06-09';
DECLARE @EndDT DATETIME = '2015-06-12'; -- moved to the next day to use >= and < operators correctly

;WITH
[Interval]
AS
(
    SELECT
         [Start] = @StartDT
        ,[End] = DATEADD(MINUTE, 15, @StartDT)

    UNION ALL

    SELECT
         [Start] = [End]
        ,[End] = DATEADD(MINUTE, 15, [End])
    FROM [Interval]
    WHERE (1 = 1)
        AND ([End] < @EndDT)
),
[Available]
AS
(
    SELECT
         [Start] = CONVERT(SMALLDATETIME, MIN([CD].[ChannelDataLogTime]))
        ,[End] = CONVERT(SMALLDATETIME, MAX([CD].[ChannelDataLogTime]))
    FROM [dbo].[ChannelData] AS [CD]
    WHERE (1 = 1)
        AND (@StartDT <= [CD].[ChannelDataLogTime] AND [CD].[ChannelDataLogTime] < @EndDT)
)
SELECT
     [ChannelValue] = AVG([CD].[ChannelValue])
    ,[HourlyDateTime] = [I].[Start]
    ,[Id] = [CD].[ChannelId]
FROM [Available] AS [A]
INNER JOIN [Interval] AS [I]
    ON ([A].[Start] <= [I].[Start] AND [I].[Start] <= [A].[End])
LEFT OUTER JOIN [dbo].[ChannelData] AS [CD]
    ON
    (
            ([CD].[ChannelId] IN (9))
        AND ([I].[Start] <= [CD].[ChannelDataLogTime] AND [CD].[ChannelDataLogTime] < [I].[End])
    )
GROUP BY
     [I].[Start]
    ,[CD].[ChannelId]
ORDER BY
     [I].[Start]
OPTION (MAXRECURSION 32767);