Calculating a rolling count over a specified window
Question
The sample data may help explain what I'm trying to do more than explaining it, so I'll begin with that.
Here's the data I'm currently working with:
+-------------------------+--------------+
| CallStart | CallDuration |
+-------------------------+--------------+
| 2017-09-15 09:15:15.313 | 00:01:28 |
| 2017-09-15 09:15:15.317 | 00:01:45 |
| 2017-09-15 09:16:45.603 | 00:01:31 |
| 2017-09-15 09:17:00.637 | 00:01:24 |
| 2017-09-15 09:18:20.853 | 00:01:42 |
| 2017-09-15 09:18:25.870 | 00:01:24 |
| 2017-09-15 11:27:05.117 | 00:00:59 |
| 2017-09-15 11:31:16.053 | 00:01:18 |
| 2017-09-15 11:34:41.627 | 00:01:00 |
| 2017-09-15 12:16:45.413 | 00:01:01 |
| 2017-09-15 12:18:15.820 | 00:01:05 |
| 2017-09-15 12:30:43.607 | 00:01:04 |
| 2017-09-15 12:31:48.817 | 00:00:55 |
| 2017-09-15 12:35:14.563 | 00:00:59 |
| 2017-09-15 12:42:10.947 | 00:00:43 |
| 2017-09-15 12:56:28.807 | 00:01:14 |
| 2017-09-15 13:05:10.643 | 00:00:37 |
| 2017-09-15 13:20:08.400 | 00:00:37 |
| 2017-09-15 14:30:12.607 | 00:00:59 |
| 2017-09-15 14:31:22.807 | 00:00:49 |
| 2017-09-15 15:19:47.240 | 00:01:07 |
| 2017-09-15 16:04:47.753 | 00:00:55 |
| 2017-09-15 16:58:08.080 | 00:00:55 |
| 2017-09-15 17:05:04.557 | 00:00:50 |
| 2017-09-15 17:20:42.753 | 00:00:58 |
| 2017-09-15 17:28:09.140 | 00:01:05 |
| 2017-09-15 17:39:46.690 | 00:00:38 |
| 2017-09-15 17:40:21.957 | 00:01:05 |
| 2017-09-15 17:43:47.570 | 00:01:08 |
| 2017-09-15 17:47:23.390 | 00:01:05 |
| 2017-09-15 17:47:28.410 | 00:00:56 |
| 2017-09-15 17:51:59.380 | 00:01:04 |
+-------------------------+--------------+
I am trying to get a rolling COUNT(*) for the number of occurrences in this data over a 15-minute timeframe. The expected result for this data would be the following:
+-------------------------+--------------+------------------+
| CallStart | CallDuration | DropsIn15Minutes |
+-------------------------+--------------+------------------+
| 2017-09-15 09:15:15.313 | 00:01:28 | 1 |
| 2017-09-15 09:15:15.317 | 00:01:45 | 2 |
| 2017-09-15 09:16:45.603 | 00:01:31 | 3 |
| 2017-09-15 09:17:00.637 | 00:01:24 | 4 |
| 2017-09-15 09:18:20.853 | 00:01:42 | 5 |
| 2017-09-15 09:18:25.870 | 00:01:24 | 6 |
| 2017-09-15 11:27:05.117 | 00:00:59 | 1 |
| 2017-09-15 11:31:16.053 | 00:01:18 | 2 |
| 2017-09-15 11:34:41.627 | 00:01:00 | 3 |
| 2017-09-15 12:16:45.413 | 00:01:01 | 1 |
| 2017-09-15 12:18:15.820 | 00:01:05 | 2 |
| 2017-09-15 12:30:43.607 | 00:01:04 | 3 |
| 2017-09-15 12:31:48.817 | 00:00:55 | 3 |
| 2017-09-15 12:35:14.563 | 00:00:59 | 3 |
| 2017-09-15 12:42:10.947 | 00:00:43 | 4 |
| 2017-09-15 12:56:28.807 | 00:01:14 | 2 |
| 2017-09-15 13:05:10.643 | 00:00:37 | 2 |
| 2017-09-15 13:20:08.400 | 00:00:37 | 2 |
| 2017-09-15 14:30:12.607 | 00:00:59 | 1 |
| 2017-09-15 14:31:22.807 | 00:00:49 | 2 |
| 2017-09-15 15:19:47.240 | 00:01:07 | 1 |
| 2017-09-15 16:04:47.753 | 00:00:55 | 1 |
| 2017-09-15 16:58:08.080 | 00:00:55 | 1 |
| 2017-09-15 17:05:04.557 | 00:00:50 | 2 |
| 2017-09-15 17:20:42.753 | 00:00:58 | 1 |
| 2017-09-15 17:28:09.140 | 00:01:05 | 2 |
| 2017-09-15 17:39:46.690 | 00:00:38 | 2 |
| 2017-09-15 17:40:21.957 | 00:01:05 | 3 |
| 2017-09-15 17:43:47.570 | 00:01:08 | 3 |
| 2017-09-15 17:47:23.390 | 00:01:05 | 4 |
| 2017-09-15 17:47:28.410 | 00:00:56 | 5 |
| 2017-09-15 17:51:59.380 | 00:01:04 | 6 |
+-------------------------+--------------+------------------+
Sample data:
Create Table #Calls
(
CallStart DateTime,
CallDuration Time(0)
);
Insert Into #Calls
Values (N'2017-09-15T09:15:15.313', N'00:01:28'),
(N'2017-09-15T09:15:15.317', N'00:01:45'),
(N'2017-09-15T09:16:45.603', N'00:01:31'),
(N'2017-09-15T09:17:00.637', N'00:01:24'),
(N'2017-09-15T09:18:20.853', N'00:01:42'),
(N'2017-09-15T09:18:25.87', N'00:01:24'),
(N'2017-09-15T11:27:05.117', N'00:00:59'),
(N'2017-09-15T11:31:16.053', N'00:01:18'),
(N'2017-09-15T11:34:41.627', N'00:01:00'),
(N'2017-09-15T12:16:45.413', N'00:01:01'),
(N'2017-09-15T12:18:15.82', N'00:01:05'),
(N'2017-09-15T12:30:43.607', N'00:01:04'),
(N'2017-09-15T12:31:48.817', N'00:00:55'),
(N'2017-09-15T12:35:14.563', N'00:00:59'),
(N'2017-09-15T12:42:10.947', N'00:00:43'),
(N'2017-09-15T12:56:28.807', N'00:01:14'),
(N'2017-09-15T13:05:10.643', N'00:00:37'),
(N'2017-09-15T13:20:08.4', N'00:00:37'),
(N'2017-09-15T14:30:12.607', N'00:00:59'),
(N'2017-09-15T14:31:22.807', N'00:00:49'),
(N'2017-09-15T15:19:47.24', N'00:01:07'),
(N'2017-09-15T16:04:47.753', N'00:00:55'),
(N'2017-09-15T16:58:08.08', N'00:00:55'),
(N'2017-09-15T17:05:04.557', N'00:00:50'),
(N'2017-09-15T17:20:42.753', N'00:00:58'),
(N'2017-09-15T17:28:09.14', N'00:01:05'),
(N'2017-09-15T17:39:46.69', N'00:00:38'),
(N'2017-09-15T17:40:21.957', N'00:01:05'),
(N'2017-09-15T17:43:47.57', N'00:01:08'),
(N'2017-09-15T17:47:23.39', N'00:01:05'),
(N'2017-09-15T17:47:28.41', N'00:00:56'),
(N'2017-09-15T17:51:59.38', N'00:01:04');
I can somewhat get this to work via the following:
Select CallStart,
CallDuration,
DropsIn15Minutes =
(
Select Count(*)
From #Calls C2
Where C2.CallStart Between DateAdd(Minute, -15, C1.CallStart)
And C1.CallStart
)
From #Calls C1
But, I would like to avoid the sub-query, in favor of a COUNT(*) OVER () (or any other solution if possible) solution.
Is this possible to do? Or is the sub-query the right solution for this?
3 answers
solution1
2 2017-09-20 19:38:58
Two other options:
using cross apply() :
select
CallStart
, CallDuration
, DropsIn15Minutes
from calls c
outer apply (
select DropsIn15Minutes = count(*)
from calls i
where i.callstart >= dateadd(minute,-15,c.CallStart)
and i.callstart <= c.CallStart
) x
order by c.CallStart
using an inner join :
select
c.CallStart
, c.CallDuration
, DropsIn15Minutes = count(i.CallStart)
from calls c
inner join calls i
on i.callstart >= dateadd(minute,-15,c.CallStart)
and i.callstart <= c.CallStart
group by c.CallStart, c.CallDuration
order by c.CallStart
rextester demo: http://rextester.com/PFCE43712
compare execution plans for all 3 (including yours): dbfiddle.uk demo
solution2
2 ACCPTED 2017-09-20 20:50:53
One way - which may perform better than a nested loops join on a range if the table is big - would be to first create a numbers table...
CREATE TABLE dbo.Numbers
(
N INT PRIMARY KEY
);
WITH E1(N) AS
(
SELECT 1 UNION ALL SELECT 1 UNION ALL SELECT 1 UNION ALL
SELECT 1 UNION ALL SELECT 1 UNION ALL SELECT 1 UNION ALL
SELECT 1 UNION ALL SELECT 1 UNION ALL SELECT 1 UNION ALL SELECT 1
) -- 1*10^1 or 10 rows
, E2(N) AS (SELECT 1 FROM E1 a, E1 b) -- 1*10^2 or 100 rows
, E4(N) AS (SELECT 1 FROM E2 a, E2 b) -- 1*10^4 or 10,000 rows
, E8(N) AS (SELECT 1 FROM E4 a, E4 b) -- 1*10^8 or 100,000,000 rows
INSERT INTO dbo.Numbers
SELECT TOP (60*60*24) -1 + ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) AS N FROM E8;
And then use something along the following lines.
WITH Calls
AS (SELECT *,
--pre-truncate all call starts to second precision
CallStart_sec = DATEADD(SECOND, DATEDIFF(SECOND, '20000101', CallStart), '20000101')
FROM #Calls),
PreAgg
AS (SELECT CallStart_sec,
COUNT(*) AS Cnt
FROM Calls
GROUP BY CallStart_sec),
Dates(D)
--Todo - something else other than hardcoding the dates
AS (SELECT CAST('2017-09-15' AS DATETIME2)),
RT
AS (SELECT *,
Cume = SUM(Cnt) OVER (ORDER BY DATEADD(SECOND, N.N, Dates.D)
ROWS BETWEEN 900 PRECEDING AND CURRENT ROW)
FROM Dates
INNER JOIN dbo.Numbers N
ON N.N BETWEEN 0 AND 86399
LEFT JOIN PreAgg P
ON P.CallStart_sec = DATEADD(SECOND, N.N, Dates.D))
SELECT C.CallStart_sec AS CallStart,
CallDuration,
DropsIn15Minutes = Cume
FROM Calls C
JOIN RT
ON RT.CallStart_sec = C.CallStart_sec
solution3
0 2017-09-20 19:49:44
Select CallStart,
CallDuration,
COUNT(*) OVER (PARTITION BY trunc(CallStart,'mi') -
numtodsinterval(mod(to_char(CallStart,'mi'),15),'minute'))
as DropsIn15Minutes
From #Calls C1
Lets try this out and see how it works.
Ted
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