Sql server T-SQL—跨两个日期的两个日期时间之间每小时的秒数

我有以下关于用户登录和注销时间的数据：

 | UserID | StartDate         |EndDate              |
 | 1033 | 06/24/2018 00:11:51 | 06/24/2018 01:03:38 |
 | 1033 | 06/24/2018 02:12:38 | 06/24/2018 02:15:51 |
 | 1033 | 06/24/2018 02:28:08 | 06/24/2018 02:36:31 |
 | 1033 | 06/24/2018 03:07:13 | 06/24/2018 06:02:05 |
 | 1033 | 06/24/2018 07:33:39 | 06/24/2018 07:33:40 |
 | 1033 | 06/24/2018 08:19:19 | 06/24/2018 12:20:03 |
 | 1033 | 06/24/2018 12:26:55 | 06/24/2018 13:30:17 |
 | 1033 | 06/24/2018 14:07:42 | 06/24/2018 14:53:03 |
 | 1033 | 06/24/2018 15:15:20 | 06/24/2018 15:33:01 |
 | 1033 | 06/24/2018 16:42:00 | 06/24/2018 16:58:13 |
 | 1033 | 06/24/2018 17:35:04 | 06/24/2018 17:49:01 |
 | 1033 | 06/24/2018 18:49:26 | 06/24/2018 19:26:18 |
 | 1033 | 06/24/2018 20:06:46 | 06/24/2018 21:00:07 |
 | 1033 | 06/24/2018 22:35:51 | 06/24/2018 22:43:57 |
 | 1033 | 06/24/2018 23:00:52 | 06/25/2018 01:24:53 |
 | 1033 | 06/25/2018 02:01:58 | 06/25/2018 02:03:47 |
 | 1033 | 06/25/2018 03:01:57 | 06/25/2018 03:45:59 |
 | 1033 | 06/25/2018 04:24:16 | 06/25/2018 04:43:52 |
 | 1033 | 06/25/2018 05:16:15 | 06/25/2018 07:39:28 |
 | 1033 | 06/25/2018 08:49:23 | 06/25/2018 09:12:06 |
 | 1033 | 06/25/2018 13:38:20 | 06/25/2018 15:16:25 |
 | 1033 | 06/25/2018 15:16:28 | 06/25/2018 16:54:34 |
 | 1033 | 06/25/2018 17:35:24 | 06/25/2018 18:25:38 |
 | 1033 | 06/25/2018 18:58:41 | 06/25/2018 19:20:56 |
 | 1033 | 06/25/2018 19:46:27 | 06/25/2018 19:47:33 |
 | 1033 | 06/25/2018 20:14:08 | 06/25/2018 20:40:20 |
 | 1033 | 06/25/2018 21:11:01 | 06/26/2018 00:36:56 |
 | 1033 | 06/26/2018 00:50:43 | 06/26/2018 09:43:53 |
 | 1033 | 06/26/2018 10:32:58 | 06/26/2018 10:33:38 |
 | 1033 | 06/26/2018 11:01:29 | 06/26/2018 11:41:24 |
 | 1033 | 06/26/2018 13:56:29 | 06/26/2018 14:52:08 |
 | 1033 | 06/26/2018 15:40:07 | 06/26/2018 16:38:18 |
 | 1033 | 06/26/2018 16:56:33 | 06/26/2018 17:19:14 |
 | 1033 | 06/26/2018 18:37:33 | 06/26/2018 19:10:44 |
 | 1033 | 06/26/2018 19:34:44 | 06/26/2018 21:30:06 |
 | 1033 | 06/26/2018 21:43:55 | 06/26/2018 21:47:51 |
 | 1033 | 06/26/2018 23:03:17 | 06/27/2018 04:26:50 |
 | 1033 | 06/27/2018 07:41:10 | 06/27/2018 07:41:11 |
 | 1033 | 06/27/2018 07:41:23 | 06/27/2018 09:56:05 |
 | 1033 | 06/27/2018 11:31:27 | 06/27/2018 12:05:42 |
 | 1033 | 06/27/2018 12:48:28 | 06/27/2018 12:49:12 |
 | 1033 | 06/27/2018 13:43:48 | 06/27/2018 14:13:04 |
 | 1033 | 06/27/2018 15:13:32 | 06/27/2018 15:46:44 |
 | 1033 | 06/27/2018 17:09:44 | 06/27/2018 17:16:15 |
 | 1033 | 06/27/2018 18:01:28 | 06/27/2018 18:35:04 |
 | 1033 | 06/27/2018 19:21:18 | 06/27/2018 19:33:47 |
 | 1033 | 06/27/2018 20:01:51 | 06/27/2018 20:04:29 |
 | 1033 | 06/27/2018 20:45:42 | 06/27/2018 22:13:48 |
 | 1033 | 06/27/2018 23:14:33 | 06/27/2018 23:28:31 |
 | 1033 | 06/27/2018 23:57:57 | 06/28/2018 04:16:47 |
 | 1033 | 06/28/2018 04:48:50 | 06/28/2018 04:50:12 |
 | 1033 | 06/28/2018 06:00:36 | 06/28/2018 08:14:20 |
 | 1033 | 06/28/2018 08:53:19 | 06/28/2018 09:09:52 |
 | 1033 | 06/28/2018 09:28:04 | 06/28/2018 10:07:02 |
 | 1033 | 06/28/2018 10:30:47 | 06/28/2018 11:07:06 |
 | 1033 | 06/28/2018 12:23:48 | 06/28/2018 12:26:52 |
 | 1033 | 06/28/2018 13:12:23 | 06/28/2018 13:24:10 |
 | 1033 | 06/28/2018 13:50:18 | 06/28/2018 13:59:04 |
 | 1033 | 06/28/2018 14:21:08 | 06/28/2018 14:56:30 |
 | 1033 | 06/28/2018 15:20:02 | 06/28/2018 15:46:18 |
 | 1033 | 06/28/2018 16:44:35 | 06/28/2018 17:09:43 |
 | 1033 | 06/28/2018 17:26:54 | 06/28/2018 17:35:20 |
 | 1033 | 06/28/2018 18:20:17 | 06/28/2018 18:42:42 |
 | 1033 | 06/28/2018 18:50:23 | 06/28/2018 19:07:15 |
 | 1033 | 06/28/2018 19:12:00 | 06/28/2018 20:06:46 |
 | 1033 | 06/28/2018 20:15:26 | 06/28/2018 20:46:14 |
 | 1033 | 06/28/2018 21:12:03 | 06/28/2018 21:12:29 |
 | 1033 | 06/28/2018 21:23:12 | 06/28/2018 21:27:14 |
 | 1033 | 06/28/2018 22:04:46 | 06/28/2018 22:17:00 |
 | 1033 | 06/28/2018 22:58:18 | 06/29/2018 01:21:10 |
 | 1033 | 06/29/2018 02:05:34 | 06/29/2018 02:10:05 |
 | 1033 | 06/29/2018 02:15:52 | 06/29/2018 07:07:20 |
 | 1033 | 06/29/2018 07:46:33 | 06/29/2018 08:06:29 |
 | 1033 | 06/29/2018 08:50:00 | 06/29/2018 08:54:24 |
 | 1033 | 06/29/2018 10:16:49 | 06/29/2018 12:47:49 |
 | 1033 | 06/29/2018 14:11:53 | 06/29/2018 15:02:08 |
 | 1033 | 06/29/2018 15:35:25 | 06/29/2018 16:46:58 |
 | 1033 | 06/29/2018 16:49:12 | 06/29/2018 16:55:00 |
 | 1033 | 06/29/2018 17:23:20 | 06/29/2018 17:50:58 |
 | 1033 | 06/29/2018 19:26:29 | 06/29/2018 19:40:41 |
 | 1033 | 06/29/2018 21:28:30 | 06/29/2018 22:00:50 |
 | 1033 | 06/29/2018 22:40:32 | 06/29/2018 22:41:46 |
 | 1033 | 06/29/2018 23:20:08 | 06/30/2018 01:24:54 |
 | 1033 | 06/30/2018 01:39:53 | 06/30/2018 06:21:02 |
 | 1033 | 06/30/2018 09:17:11 | 06/30/2018 09:17:12 |
 | 1033 | 06/30/2018 09:17:20 | 06/30/2018 09:45:50 |
 | 1033 | 06/30/2018 10:52:58 | 06/30/2018 11:46:47 |
 | 1033 | 06/30/2018 12:28:47 | 06/30/2018 14:05:42 |
 | 1033 | 06/30/2018 15:30:42 | 06/30/2018 15:37:32 |
 | 1033 | 06/30/2018 16:28:27 | 06/30/2018 16:39:04 |
 | 1033 | 06/30/2018 17:13:20 | 06/30/2018 18:09:44 |
 | 1033 | 06/30/2018 19:30:26 | 06/30/2018 20:25:35 |
 | 1033 | 06/30/2018 21:30:45 | 06/30/2018 22:25:15 |
 | 1033 | 06/30/2018 23:27:07 | 06/30/2018 23:27:35 |
 | 1033 | 06/30/2018 23:48:45 | 06/30/2018 23:50:08 |

我需要计算出每个唯一日期的每小时，用户登录的时间（即从StartDate到EndDate）

我发现这一条讨论了这一点，这是我到目前为止的查询，但它没有考虑跨越2个日期（6/24到6/25）的第1行的小时数

---

与以前稍有不同的策略

我已经创建了一个临时表-有关完整解决方案，请参见[SQLFIDLE]

我已经创建了一个Grp和StartDate_Plus列，如下所示

;WITH Numbers (Number) AS
(   SELECT ROW_NUMBER() OVER(ORDER BY N1.N) - 1
    FROM (VALUES (1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) N1(N)
    CROSS JOIN (VALUES (1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) N2 (N)
    CROSS JOIN (VALUES (1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) N3 (N)
    CROSS JOIN (VALUES (1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) N4 (N)
)
    SELECT
         D.UserId
        ,D.StartDate
        ,D.EndDate
        ,StartDate_Plus = DATEADD(HOUR, N.Number, D.StartDate) --Only for Ordering of ResultSet below
        ,N.Number
        ,Grp = MAX(N.Number)OVER(PARTITION BY UserId, StartDate)
    FROM
        dbo.T1  D
    INNER JOIN Numbers N ON N.Number <= DATEDIFF(HOUR, D.StartDate, D.EndDate)

StartDate_plus列只是将[小时数]添加到

StartDate

和

Grp

中，以便为同一事件提供多行的分组

添加此附加CTE后，您可以为事件超过一小时的每一小时显示虚拟

开始日期

和

结束日期

;WITH Numbers (Number) AS
(   SELECT ROW_NUMBER() OVER(ORDER BY N1.N) - 1
    FROM (VALUES (1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) N1(N)
    CROSS JOIN (VALUES (1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) N2 (N)
    CROSS JOIN (VALUES (1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) N3 (N)
    CROSS JOIN (VALUES (1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) N4 (N)
),cteStartDate_Plus
AS(
    SELECT
         D.UserId
        ,D.StartDate
        ,D.EndDate
        ,StartDate_Plus = DATEADD(HOUR, N.Number, D.StartDate) --Only for Ordering of ResultSet below
        ,N.Number
        ,Grp = MAX(N.Number)OVER(PARTITION BY UserId, StartDate)
    FROM
        dbo.T1  D
    INNER JOIN Numbers N ON N.Number <= DATEDIFF(HOUR, D.StartDate, D.EndDate)
)
    SELECT TOP 100 PERCENT
         UserId, StartDate, EndDate, Grp
        ,CS.StartDate_Plus
        ,CS.Number
        ,[StartDate_] = CASE --apply some rounding to the StartDate if required
                            WHEN Number = 0 THEN CS.StartDate
                            ELSE DATEADD(hour, DATEDIFF(HOUR, 0, CS.StartDate_Plus), 0)
                        END
        ,[EndDate_] =   CASE --apply some rounding to the EndDate if required
                            WHEN CS.Number = CS.Grp THEN CS.EndDate
                            WHEN CS.StartDate_Plus > CS.EndDate THEN CS.EndDate
                            WHEN CS.Number <> CS.Grp AND CS.StartDate_Plus <= CS.EndDate 
                                THEN DATEADD(HOUR, DATEDIFF(HOUR, 0, DATEADD(MINUTE, 30 + DATEPART(MINUTE, DATEADD(MINUTE, 30, CS.StartDate_Plus)),CS.StartDate_Plus)), 0) 
                        END
        ,[Hour] = CONVERT(TIME(0), DATEADD(HOUR, DATEPART(HOUR, CS.StartDate_Plus), 0))
    FROM
        cteStartDate_Plus CS
    ORDER BY
        UserId, CS.StartDate_Plus

输出

UserId  Date        Hour        Seconds_in
1033    2018-06-24  00:00:00    2889
1033    2018-06-24  01:00:00    218
1033    2018-06-24  02:00:00    193
1033    2018-06-24  02:00:00    503
1033    2018-06-24  03:00:00    3167
1033    2018-06-24  04:00:00    3600
1033    2018-06-24  05:00:00    3600
1033    2018-06-24  06:00:00    125
1033    2018-06-24  07:00:00    1
1033    2018-06-24  08:00:00    2441
1033    2018-06-24  09:00:00    3600

---

谢谢毕竟，这看起来很有希望！不幸的是，当我把这个应用到我的整个数据集时，我得到了3600秒的时间。我添加了更多数据来说明这一点。当我将这些值添加到您的查询中时，它将生成秒数>3600。再次感谢！这太棒了！你真棒！我现在在我的数据集中看到一些数据，由于某种原因，开始日期可能是背对背的（即用户连续登录两次，然后注销）。这给了我两次登录，一次注销，使用您的查询，给我的次数>3600。我绞尽脑汁想弄清楚如何排除这些异常值。本质上，我需要排除在注销前有2次或更多登录时间的数据。在SQL FIDLE中，如果您将值（1033，'2018-06-24 00:11:50，'2018-06-24 01:03:38'）添加为您将看到的第一个值。更改问题的性质或添加其他变体是不受欢迎的，尤其是当您已获得原始问题的答案时。如果这个回答回答了你的问题，那么接受它作为回答。打开一个新问题，用附加变量链接回此问题。

UserId  StartDate                   EndDate                     StartDate_Plus              Number  Grp
1033    2018-06-24 00:11:51.0000000 2018-06-24 01:03:38.0000000 2018-06-24 00:11:51.0000000 0   1
1033    2018-06-24 00:11:51.0000000 2018-06-24 01:03:38.0000000 2018-06-24 01:11:51.0000000 1   1
1033    2018-06-24 02:12:38.0000000 2018-06-24 02:15:51.0000000 2018-06-24 02:12:38.0000000 0   0
1033    2018-06-24 02:28:08.0000000 2018-06-24 02:36:31.0000000 2018-06-24 02:28:08.0000000 0   0
1033    2018-06-24 03:07:13.0000000 2018-06-24 06:02:05.0000000 2018-06-24 03:07:13.0000000 0   3
1033    2018-06-24 03:07:13.0000000 2018-06-24 06:02:05.0000000 2018-06-24 04:07:13.0000000 1   3
1033    2018-06-24 03:07:13.0000000 2018-06-24 06:02:05.0000000 2018-06-24 05:07:13.0000000 2   3
1033    2018-06-24 03:07:13.0000000 2018-06-24 06:02:05.0000000 2018-06-24 06:07:13.0000000 3   3

;WITH Numbers (Number) AS
(   SELECT ROW_NUMBER() OVER(ORDER BY N1.N) - 1
    FROM (VALUES (1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) N1(N)
    CROSS JOIN (VALUES (1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) N2 (N)
    CROSS JOIN (VALUES (1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) N3 (N)
    CROSS JOIN (VALUES (1),(1),(1),(1),(1),(1),(1),(1),(1),(1)) N4 (N)
),cteStartDate_Plus
AS(
    SELECT
         D.UserId
        ,D.StartDate
        ,D.EndDate
        ,StartDate_Plus = DATEADD(HOUR, N.Number, D.StartDate) --Only for Ordering of ResultSet below
        ,N.Number
        ,Grp = MAX(N.Number)OVER(PARTITION BY UserId, StartDate)
    FROM
        dbo.T1  D
    INNER JOIN Numbers N ON N.Number <= DATEDIFF(HOUR, D.StartDate, D.EndDate)
)
    SELECT TOP 100 PERCENT
         UserId, StartDate, EndDate, Grp
        ,CS.StartDate_Plus
        ,CS.Number
        ,[StartDate_] = CASE --apply some rounding to the StartDate if required
                            WHEN Number = 0 THEN CS.StartDate
                            ELSE DATEADD(hour, DATEDIFF(HOUR, 0, CS.StartDate_Plus), 0)
                        END
        ,[EndDate_] =   CASE --apply some rounding to the EndDate if required
                            WHEN CS.Number = CS.Grp THEN CS.EndDate
                            WHEN CS.StartDate_Plus > CS.EndDate THEN CS.EndDate
                            WHEN CS.Number <> CS.Grp AND CS.StartDate_Plus <= CS.EndDate 
                                THEN DATEADD(HOUR, DATEDIFF(HOUR, 0, DATEADD(MINUTE, 30 + DATEPART(MINUTE, DATEADD(MINUTE, 30, CS.StartDate_Plus)),CS.StartDate_Plus)), 0) 
                        END
        ,[Hour] = CONVERT(TIME(0), DATEADD(HOUR, DATEPART(HOUR, CS.StartDate_Plus), 0))
    FROM
        cteStartDate_Plus CS
    ORDER BY
        UserId, CS.StartDate_Plus

SELECT
      UserId
     ,[Date] = CONVERT(DATE, DD.StartDate_Plus)
     ,DD.[Hour]
    ,[Seconds_in] = DATEDIFF(SECOND, DD.StartDate_, DD.EndDate_)
FROM
    cteDummyDates DD
ORDER BY
    DD.UserId, DD.StartDate_

UserId  Date        Hour        Seconds_in
1033    2018-06-24  00:00:00    2889
1033    2018-06-24  01:00:00    218
1033    2018-06-24  02:00:00    193
1033    2018-06-24  02:00:00    503
1033    2018-06-24  03:00:00    3167
1033    2018-06-24  04:00:00    3600
1033    2018-06-24  05:00:00    3600
1033    2018-06-24  06:00:00    125
1033    2018-06-24  07:00:00    1
1033    2018-06-24  08:00:00    2441
1033    2018-06-24  09:00:00    3600