Related
I have a table containing a time series with following information. Each record represents the event of "changing the mode".
Timestamp | Mode
------------------+------
2018-01-01 12:00 | 1
2018-01-01 18:00 | 2
2018-01-02 01:00 | 1
2018-01-02 02:00 | 2
2018-01-04 04:00 | 1
By using the LEAD function, I can create a query with the following result. Now each record contains the information, when and how long the "mode was active".
Please check the 2nd and the 4th record. They "belong" to multiple days.
StartDT | EndDT | Mode | Duration
------------------+------------------+------+----------
2018-01-01 12:00 | 2018-01-01 18:00 | 1 | 6:00
2018-01-01 18:00 | 2018-01-02 01:00 | 2 | 7:00
2018-01-02 01:00 | 2018-01-02 02:00 | 1 | 1:00
2018-01-02 02:00 | 2018-01-04 04:00 | 2 | 50:00
2018-01-04 04:00 | (NULL) | 1 | (NULL)
Now I would like to have a query that groups the data by day and mode and aggregates the duration.
This result table is needed:
Date | Mode | Total
------------+------+-------
2018-01-01 | 1 | 6:00
2018-01-01 | 2 | 6:00
2018-01-02 | 1 | 1:00
2018-01-02 | 2 | 23:00
2018-01-03 | 2 | 24:00
2018-01-04 | 2 | 04:00
I didn't known how to handle the records that "belongs" to multiple days. Any ideas?
create table ChangeMode ( ModeStart datetime2(7), Mode int )
insert into ChangeMode ( ModeStart, Mode ) values
( '2018-11-15T21:00:00.0000000', 1 ),
( '2018-11-16T17:18:19.1231234', 2 ),
( '2018-11-16T18:00:00.5555555', 1 ),
( '2018-11-16T18:00:01.1234567', 2 ),
( '2018-11-16T19:02:22.8888888', 1 ),
( '2018-11-16T20:00:00.9876543', 2 ),
( '2018-11-17T09:00:00.0000000', 1 ),
( '2018-11-17T23:23:23.0230450', 2 ),
( '2018-11-19T17:00:00.0172839', 1 ),
( '2018-11-20T03:07:00.7033077', 2 )
;
with
-- Determine the earliest and latest dates.
-- Cast to date to remove the time portion.
-- Cast results back to datetime because we're going to add hours later.
MinMaxDates
as
(select cast(min(cast(ModeStart as date))as datetime) as MinDate,
cast(max(cast(ModeStart as date))as datetime) as MaxDate from ChangeMode),
-- How many days have passed during that period
Dur
as
(select datediff(day,MinDate,MaxDate) as Duration from MinMaxDates),
-- Create a list of numbers.
-- These will be added to MinDate to get a list of dates.
NumList
as
( select 0 as Num
union all
select Num+1 from NumList,Dur where Num<Duration ),
-- Create a list of dates by adding those numbers to MinDate
DayList
as
( select dateadd(day,Num,MinDate)as ModeDate from NumList, MinMaxDates ),
-- Create a list of day periods
PeriodList
as
( select ModeDate as StartTime,
dateadd(day,1,ModeDate) as EndTime
from DayList ),
-- Use LEAD to get periods for each record
-- Final record would return NULL for ModeEnd
-- We replace that with end of last day
ModePeriodList
as
( select ModeStart,
coalesce( lead(ModeStart)over(order by ModeStart),
dateadd(day,1,MaxDate) ) as ModeEnd,
Mode from ChangeMode, MinMaxDates ),
ModeDayList
as
( select * from ModePeriodList, PeriodList
where ModeStart<=EndTime and ModeEnd>=StartTime
),
-- Keep the later of the mode start time, and the day start time
-- Keep the earlier of the mode end time, and the day end time
ModeDayPeriod
as
( select case when ModeStart>=StartTime then ModeStart else StartTime end as StartTime,
case when ModeEnd<=EndTime then ModeEnd else EndTime end as EndTime,
Mode from ModeDayList ),
SumDurations
as
( select cast(StartTime as date) as ModeDate,
Mode,
DateDiff_Big(nanosecond,StartTime,EndTime)
/3600000000000
as DurationHours from ModeDayPeriod )
-- List the results in order
-- Use MaxRecursion option in case there are more than 100 days
select ModeDate as [Date], Mode, sum(DurationHours) as [Total Duration Hours]
from SumDurations
group by ModeDate, Mode
order by ModeDate, Mode
option (maxrecursion 0)
Result is:
Date Mode Total Duration Hours
---------- ----------- ---------------------------------------
2018-11-15 1 3.00000000000000
2018-11-16 1 18.26605271947221
2018-11-16 2 5.73394728052777
2018-11-17 1 14.38972862361111
2018-11-17 2 9.61027137638888
2018-11-18 2 24.00000000000000
2018-11-19 1 6.99999519891666
2018-11-19 2 17.00000480108333
2018-11-20 1 3.11686202991666
2018-11-20 2 20.88313797008333
you could use a CTE to create a table of days then join the time slots to it
DECLARE #MAX as datetime2 = (SELECT MAX(CAST(Timestamp as date)) MX FROM process);
WITH StartEnd AS (select p1.Timestamp StartDT,
P2.Timestamp EndDT ,
p1.mode
from process p1
outer apply
(SELECT TOP 1 pOP.* FROM
process pOP
where pOP.Timestamp > p1.Timestamp
order by pOP.Timestamp asc) P2
),
CAL AS (SELECT (SELECT MIN(cast(StartDT as date)) MN FROM StartEnd) DT
UNION ALL
SELECT DATEADD(day,1,DT) DT FROM CAL WHERE CAL.DT < #MAX
),
TMS AS
(SELECT CASE WHEN S.StartDT > C.DT THEN S.StartDT ELSE C.DT END AS STP,
CASE WHEN S.EndDT < DATEADD(day,1,C.DT) THEN S.ENDDT ELSE DATEADD(day,1,C.DT) END AS STE
FROM StartEnd S JOIN CAL C ON NOT(S.EndDT <= C.DT OR S.StartDT>= DATEADD(day,1,C.dt))
)
SELECT *,datediff(MI ,TMS.STP, TMS.ste) as x from TMS
The following uses recursive CTE to build a list of dates (a calendar or number table works equally well). It then intersect the dates with date times so that missing dates are populated with matching data. The important bit is that for each row, if start datetime belongs to previous day then it is clamped to 00:00. Likewise for end datetime.
DECLARE #t TABLE (timestamp DATETIME, mode INT);
INSERT INTO #t VALUES
('2018-01-01 12:00', 1),
('2018-01-01 18:00', 2),
('2018-01-02 01:00', 1),
('2018-01-02 02:00', 2),
('2018-01-04 04:00', 1);
WITH cte1 AS (
-- the min and max dates in your data
SELECT
CAST(MIN(timestamp) AS DATE) AS mindate,
CAST(MAX(timestamp) AS DATE) AS maxdate
FROM #t
), cte2 AS (
-- build all dates between min and max dates using recursive cte
SELECT mindate AS day_start, DATEADD(DAY, 1, mindate) AS day_end, maxdate
FROM cte1
UNION ALL
SELECT DATEADD(DAY, 1, day_start), DATEADD(DAY, 2, day_start), maxdate
FROM cte2
WHERE day_start < maxdate
), cte3 AS (
-- pull end datetime from next row into current
SELECT
timestamp AS dt_start,
LEAD(timestamp) OVER (ORDER BY timestamp) AS dt_end,
mode
FROM #t
), cte4 AS (
-- join datetime with date using date overlap query
-- then clamp start datetime to 00:00 of the date
-- and clamp end datetime to 00:00 of next date
SELECT
IIF(dt_start < day_start, day_start, dt_start) AS dt_start_fix,
IIF(dt_end > day_end, day_end, dt_end) AS dt_end_fix,
mode
FROM cte2
INNER JOIN cte3 ON day_end > dt_start AND dt_end > day_start
)
SELECT dt_start_fix, dt_end_fix, mode, datediff(minute, dt_start_fix, dt_end_fix) / 60.0 AS total
FROM cte4
DB Fiddle
Thanks everybody!
The answer from Cato put me on the right track. Here my final solution:
DECLARE #Start AS datetime;
DECLARE #End AS datetime;
DECLARE #Interval AS int;
SET #Start = '2018-01-01';
SET #End = '2018-01-05';
SET #Interval = 24 * 60 * 60;
WITH
cteDurations AS
(SELECT [Timestamp] AS StartDT,
LEAD ([Timestamp]) OVER (ORDER BY [Timestamp]) AS EndDT,
Mode
FROM tblLog
WHERE [Timestamp] BETWEEN #Start AND #End
),
cteTimeslots AS
(SELECT #Start AS StartDT,
DATEADD(SECOND, #Interval, #Start) AS EndDT
UNION ALL
SELECT EndDT,
DATEADD(SECOND, #Interval, EndDT)
FROM cteTimeSlots WHERE StartDT < #End
),
cteDurationsPerTimesplot AS
(SELECT CASE WHEN S.StartDT > C.StartDT THEN S.StartDT ELSE C.StartDT END AS StartDT,
CASE WHEN S.EndDT < C.EndDT THEN S.EndDT ELSE C.EndDT END AS EndDT,
C.StartDT AS Slot,
S.Mode
FROM cteDurations S
JOIN cteTimeslots C ON NOT(S.EndDT <= C.StartDT OR S.StartDT >= C.EndDT)
)
SELECT Slot,
Mode,
SUM(DATEDIFF(SECOND, StartDT, EndDT)) AS Duration
FROM cteDurationsPerTimesplot
GROUP BY Slot, Mode
ORDER BY Slot, Mode;
With the variable #Interval you are able to define the size of the timeslots.
The CTE cteDurations creates a subresult with the durations of all necessary entries by using the TSQL function LEAD (available in MSSQL >= 2012). This will be a lot faster than an OUTER APPLY.
The CTE cteTimeslots generates a list of timeslots with start time and end time.
The CTE cteDurationsPerTimesplot is a subresult with a JOIN between cteDurations and cteTimeslots. This this the magic JOIN statement from Cato!
And finally the SELECT statement will do the grouping and sum calculation per Slot and Mode.
Once again: Thanks a lot to everybody! Especially to Cato! You saved my weekend!
Regards
Oliver
I have a dataset with id ,Status and date range of employees.
The input dataset given below are the details of one employee.
The date ranges in the records are continuous(in exact order) such that startdate of second row will be the next date of enddate of first row.
If an employee takes leave continuously for different months, then the table is storing the info with date range as separated for different months.
For example: In the input set, the employee has taken Sick leave from '16-10-2016' to '31-12-2016' and joined back on '1-1-2017'.
So there are 3 records for this item but the dates are continuous.
In the output I need this as one record as shown in the expected output dataset.
INPUT
Id Status StartDate EndDate
1 Active 1-9-2007 15-10-2016
1 Sick 16-10-2016 31-10-2016
1 Sick 1-11-2016 30-11-2016
1 Sick 1-12-2016 31-12-2016
1 Active 1-1-2017 4-2-2017
1 Unpaid 5-2-2017 9-2-2017
1 Active 10-2-2017 11-2-2017
1 Unpaid 12-2-2017 28-2-2017
1 Unpaid 1-3-2017 31-3-2017
1 Unpaid 1-4-2017 30-4-2017
1 Active 1-5-2017 13-10-2017
1 Sick 14-10-2017 11-11-2017
1 Active 12-11-2017 NULL
EXPECTED OUTPUT
Id Status StartDate EndDate
1 Active 1-9-2007 15-10-2016
1 Sick 16-10-2016 31-12-2016
1 Active 1-1-2017 4-2-2017
1 Unpaid 5-2-2017 9-2-2017
1 Active 10-2-2017 11-2-2017
1 Unpaid 12-2-2017 30-4-2017
1 Active 1-5-2017 13-10-2017
1 Sick 14-10-2017 11-11-2017
1 Active 12-11-2017 NULL
I can't take min(startdate) and max(EndDate) group by id,status because if the same employee has taken another Sick leave then that end date ('11-11-2017' in the example) will come as the End date.
can anyone help me with the query in SQL server 2014?
It suddenly hit me that this is basically a gaps and islands problem - so I've completely changed my solution.
For this solution to work, the dates does not have to be consecutive.
First, create and populate sample table (Please save us this step in your future questions):
DECLARE #T AS TABLE
(
Id int,
Status varchar(10),
StartDate date,
EndDate date
);
SET DATEFORMAT DMY; -- This is needed because how you specified your dates.
INSERT INTO #T (Id, Status, StartDate, EndDate) VALUES
(1, 'Active', '1-9-2007', '15-10-2016'),
(1, 'Sick', '16-10-2016', '31-10-2016'),
(1, 'Sick', '1-11-2016', '30-11-2016'),
(1, 'Sick', '1-12-2016', '31-12-2016'),
(1, 'Active', '1-1-2017', '4-2-2017'),
(1, 'Unpaid', '5-2-2017', '9-2-2017'),
(1, 'Active', '10-2-2017', '11-2-2017'),
(1, 'Unpaid', '12-2-2017', '28-2-2017'),
(1, 'Unpaid', '1-3-2017', '31-3-2017'),
(1, 'Unpaid', '1-4-2017', '30-4-2017'),
(1, 'Active', '1-5-2017', '13-10-2017'),
(1, 'Sick', '14-10-2017', '11-11-2017'),
(1, 'Active', '12-11-2017', NULL);
The (new) common table expression:
;WITH CTE AS
(
SELECT Id,
Status,
StartDate,
EndDate,
ROW_NUMBER() OVER(PARTITION BY Id ORDER BY StartDate)
- ROW_NUMBER() OVER(PARTITION BY Id, Status ORDER BY StartDate) As IslandId,
ROW_NUMBER() OVER(PARTITION BY Id ORDER BY StartDate DESC)
- ROW_NUMBER() OVER(PARTITION BY Id, Status ORDER BY StartDate DESC) As ReverseIslandId
FROM #T
)
The (new) query:
SELECT DISTINCT Id,
Status,
MIN(StartDate) OVER(PARTITION BY IslandId, ReverseIslandId) As StartDate,
NULLIF(MAX(ISNULL(EndDate, '9999-12-31')) OVER(PARTITION BY IslandId, ReverseIslandId), '9999-12-31') As EndDate
FROM CTE
ORDER BY StartDate
(new) Results:
Id Status StartDate EndDate
1 Active 01.09.2007 15.10.2016
1 Sick 16.10.2016 31.12.2016
1 Active 01.01.2017 04.02.2017
1 Unpaid 05.02.2017 09.02.2017
1 Active 10.02.2017 11.02.2017
1 Unpaid 12.02.2017 30.04.2017
1 Active 01.05.2017 13.10.2017
1 Sick 14.10.2017 11.11.2017
1 Active 12.11.2017 NULL
You can see a live demo on rextester.
Please note that string representation of dates in SQL should be acccording to ISO 8601 - meaning either yyyy-MM-dd or yyyyMMdd as it's unambiguous and will always be interpreted correctly by SQL Server.
It's an example of GROUPING AND WINDOW.
First you set a reset point for each Status
Sum to set a group
Then get max/min dates of each group.
;with x as
(
select Id, Status, StartDate, EndDate,
iif (lag(Status) over (order by Id, StartDate) = Status, null, 1) rst
from emp
), y as
(
select Id, Status, StartDate, EndDate,
sum(rst) over (order by Id, StartDate) grp
from x
)
select Id,
MIN(Status) as Status,
MIN(StartDate) StartDate,
MAX(EndDate) EndDate
from y
group by Id, grp
order by Id, grp
GO
Id | Status | StartDate | EndDate
-: | :----- | :------------------ | :------------------
1 | Active | 01/09/2007 00:00:00 | 15/10/2016 00:00:00
1 | Sick | 16/10/2016 00:00:00 | 31/12/2016 00:00:00
1 | Active | 01/01/2017 00:00:00 | 04/02/2017 00:00:00
1 | Unpaid | 05/02/2017 00:00:00 | 09/02/2017 00:00:00
1 | Active | 10/02/2017 00:00:00 | 11/02/2017 00:00:00
1 | Unpaid | 12/02/2017 00:00:00 | 30/04/2017 00:00:00
1 | Active | 01/05/2017 00:00:00 | 13/10/2017 00:00:00
1 | Sick | 14/10/2017 00:00:00 | 11/11/2017 00:00:00
1 | Active | 12/11/2017 00:00:00 | null
dbfiddle here
Here's an alternative answer that doesn't use LAG.
First I need to take a copy of your test data:
DECLARE #table TABLE (Id INT, [Status] VARCHAR(50), StartDate DATE, EndDate DATE);
INSERT INTO #table SELECT 1, 'Active', '20070901', '20161015';
INSERT INTO #table SELECT 1, 'Sick', '20161016', '20161031';
INSERT INTO #table SELECT 1, 'Sick', '20161101', '20161130';
INSERT INTO #table SELECT 1, 'Sick', '20161201', '20161231';
INSERT INTO #table SELECT 1, 'Active', '20170101', '20170204';
INSERT INTO #table SELECT 1, 'Unpaid', '20170205', '20170209';
INSERT INTO #table SELECT 1, 'Active', '20170210', '20170211';
INSERT INTO #table SELECT 1, 'Unpaid', '20170212', '20170228';
INSERT INTO #table SELECT 1, 'Unpaid', '20170301', '20170331';
INSERT INTO #table SELECT 1, 'Unpaid', '20170401', '20170430';
INSERT INTO #table SELECT 1, 'Active', '20170501', '20171013';
INSERT INTO #table SELECT 1, 'Sick', '20171014', '20171111';
INSERT INTO #table SELECT 1, 'Active', '20171112', NULL;
Then the query is:
WITH add_order AS (
SELECT
*,
ROW_NUMBER() OVER (ORDER BY StartDate) AS order_id
FROM
#table),
links AS (
SELECT
a1.Id,
a1.[Status],
a1.order_id,
MIN(a1.order_id) AS start_order_id,
MAX(ISNULL(a2.order_id, a1.order_id)) AS end_order_id,
MIN(a1.StartDate) AS StartDate,
MAX(ISNULL(a2.EndDate, a1.EndDate)) AS EndDate
FROM
add_order a1
LEFT JOIN add_order a2 ON a2.Id = a1.Id AND a2.[Status] = a1.[Status] AND a2.order_id = a1.order_id + 1 AND a2.StartDate = DATEADD(DAY, 1, a1.EndDate)
GROUP BY
a1.Id,
a1.[Status],
a1.order_id),
merged AS (
SELECT
l1.Id,
l1.[Status],
l1.[StartDate],
ISNULL(l2.EndDate, l1.EndDate) AS EndDate,
ROW_NUMBER() OVER (PARTITION BY l1.Id, l1.[Status], ISNULL(l2.EndDate, l1.EndDate) ORDER BY l1.order_id) AS link_id
FROM
links l1
LEFT JOIN links l2 ON l2.order_id = l1.end_order_id)
SELECT
Id,
[Status],
StartDate,
EndDate
FROM
merged
WHERE
link_id = 1
ORDER BY
StartDate;
Results are:
Id Status StartDate EndDate
1 Active 2007-09-01 2016-10-15
1 Sick 2016-10-16 2016-12-31
1 Active 2017-01-01 2017-02-04
1 Unpaid 2017-02-05 2017-02-09
1 Active 2017-02-10 2017-02-11
1 Unpaid 2017-02-12 2017-04-30
1 Active 2017-05-01 2017-10-13
1 Sick 2017-10-14 2017-11-11
1 Active 2017-11-12 NULL
How does it work? First I add a sequence number, to assist with merging contiguous rows together. Then I determine the rows that can be merged together, add a number to identify the first row in each set that can be merged, and finally pick the first rows out of the final CTE. Note that I also have to handle rows that can't be merged, hence the LEFT JOINs and ISNULL statements.
Just for interest, this is what the output from the final CTE looks like, before I filter out all but the rows with a link_id of 1:
Id Status StartDate EndDate link_id
1 Active 2007-09-01 2016-10-15 1
1 Sick 2016-10-16 2016-12-31 1
1 Sick 2016-11-01 2016-12-31 2
1 Sick 2016-12-01 2016-12-31 3
1 Active 2017-01-01 2017-02-04 1
1 Unpaid 2017-02-05 2017-02-09 1
1 Active 2017-02-10 2017-02-11 1
1 Unpaid 2017-02-12 2017-04-30 1
1 Unpaid 2017-03-01 2017-04-30 2
1 Unpaid 2017-04-01 2017-04-30 3
1 Active 2017-05-01 2017-10-13 1
1 Sick 2017-10-14 2017-11-11 1
1 Active 2017-11-12 NULL 1
You could use lag() and lead() function together to check the previous and next status
WITH CTE AS
(
select *,
COALESCE(LEAD(status) OVER(ORDER BY (select 1)), '0') Nstatus,
COALESCE(LAG(status) OVER(ORDER BY (select 1)), '0') Pstatus
from table
)
SELECT * FROM CTE
WHERE (status <> Nstatus AND status <> Pstatus) OR
(status <> Pstatus)
I’m using MS-SQL-2008 R2 trying to write a script that calculates the Number of Hospital Beds occupied on any given day, at 2 census points: midnight, and 09:00.
I’m working from a data set of patient Ward Stays. Basically, each row in the table is a record of an individual patient's stay on a single ward, and records the date/time the patient is admitted onto the ward, and the date/time the patient leaves the ward.
A sample of this table is below:
Ward_Stay_Primary_Key | Ward_Start_Date_Time | Ward_End_Date_Time
1 | 2017-09-03 15:04:00.000 | 2017-09-27 16:55:00.000
2 | 2017-09-04 18:08:00.000 | 2017-09-06 18:00:00.000
3 | 2017-09-04 13:00:00.000 | 2017-09-04 22:00:00.000
4 | 2017-09-04 20:54:00.000 | 2017-09-08 14:30:00.000
5 | 2017-09-04 20:52:00.000 | 2017-09-13 11:50:00.000
6 | 2017-09-05 13:32:00.000 | 2017-09-11 14:49:00.000
7 | 2017-09-05 13:17:00.000 | 2017-09-12 21:00:00.000
8 | 2017-09-05 23:11:00.000 | 2017-09-06 17:38:00.000
9 | 2017-09-05 11:35:00.000 | 2017-09-14 16:12:00.000
10 | 2017-09-05 14:05:00.000 | 2017-09-11 16:30:00.000
The key thing to note here is that a patient’s Ward Stay can span any length of time, from a few hours to many days.
The following code enables me to calculate the number of beds at both census points for any given day, by specifying the date in the case statement:
SELECT
'05/09/2017' [Date]
,SUM(case when Ward_Start_Date_Time <= '05/09/2017 00:00:00.000' AND (Ward_End_Date_Time >= '05/09/2017 00:00:00.000' OR Ward_End_Date_Time IS NULL)then 1 else 0 end)[No. Beds Occupied at 00:00]
,SUM(case when Ward_Start_Date_Time <= '05/09/2017 09:00:00.000' AND (Ward_End_Date_Time >= '05/09/2017 09:00:00.000' OR Ward_End_Date_Time IS NULL)then 1 else 0 end)[No. Beds Occupied at 09:00]
FROM
WardStaysTable
And, based on the sample 10 records above, generates this output:
Date | No. Beds Occupied at 00:00 | No. Beds Occupied at 09:00
05/09/2017 | 4 | 4
To perform this for any number of days is obviously onerous, so what I’m looking to create is a query where I can specify a start/end date parameter (e.g. 1st-5th Sept), and for the query to then evaluate the Ward_Start_Date_Time and Ward_End_Date_Time variables for each record, and – grouping by the dates defined in the date parameter – count each time the 00:00:00.000 and 09:00:00.000 census points fall between these 2 variables, to give an output something along these lines (based on the above 10 records):
Date | No. Beds Occupied at 00:00 | No. Beds Occupied at 09:00
01/09/2017 | 0 | 0
02/09/2017 | 0 | 0
03/09/2017 | 0 | 0
04/09/2017 | 1 | 1
05/09/2017 | 4 | 4
I’ve approached this (perhaps naively) thinking that if I use a cte to create a table of dates (defined by the input parameters), along with associated midnight and 9am census date/time points, then I could use these variables to group and evaluate the dataset.
So, this code generates the grouping dates and census date/time points:
DECLARE
#StartDate DATE = '01/09/2017'
,#EndDate DATE = '05/09/2017'
,#0900 INT = 540
SELECT
DATEADD(DAY, nbr - 1, #StartDate) [Date]
,CONVERT(DATETIME,(DATEADD(DAY, nbr - 1, #StartDate))) [MidnightDate]
,DATEADD(mi, #0900,(CONVERT(DATETIME,(DATEADD(DAY, nbr - 1, #StartDate))))) [0900Date]
FROM
(
SELECT
ROW_NUMBER() OVER ( ORDER BY c.object_id ) AS nbr
FROM sys.columns c
) nbrs
WHERE nbr - 1 <= DATEDIFF(DAY, #StartDate, #EndDate)
The stumbling block I’ve hit is how to join the cte to the WardStays dataset, because there’s no appropriate key… I’ve tried a few iterations of using a subquery to make this work, but either I’m taking the wrong approach or I’m getting my syntax in a mess.
In simple terms, the logic I’m trying to create to get the output is something like:
SELECT
[Date]
,SUM (case when WST.Ward_Start_Date_Time <= [MidnightDate] AND (WST.Ward_End_Date_Time >= [MidnightDate] OR WST.Ward_End_Date_Time IS NULL then 1 else 0 end) [No. Beds Occupied at 00:00]
,SUM (case when WST.Ward_Start_Date_Time <= [0900Date] AND (WST.Ward_End_Date_Time >= [0900Date] OR WST.Ward_End_Date_Time IS NULL then 1 else 0 end) [No. Beds Occupied at 09:00]
FROM WardStaysTable WST
GROUP BY [Date]
Is the above somehow possible, or am I barking up the wrong tree and need to take a different approach altogether? Appreciate any advice.
I would expect something like this:
WITH dates as (
SELECT CAST(#StartDate as DATETIME) as dte
UNION ALL
SELECT DATEADD(DAY, 1, dte)
FROM dates
WHERE dte < #EndDate
)
SELECT dates.dte [Date],
SUM(CASE WHEN Ward_Start_Date_Time <= dte AND
Ward_END_Date_Time >= dte
THEN 1 ELSE 0
END) as num_beds_0000,
SUM(CASE WHEN Ward_Start_Date_Time <= dte + CAST('09:00' as DATETIME) AND
Ward_END_Date_Time >= dte + CAST('09:00' as DATETIME)
THEN 1 ELSE 0
END) as num_beds_0900
FROM dates LEFT JOIN
WardStaysTable wt
ON wt.Ward_Start_Date_Time <= DATEADD(day, 1, dates.dte) AND
wt.Ward_END_Date_Time >= dates.dte
GROUP BY dates.dte
ORDER BY dates.dte;
The cte is just creating the list of dates.
What a cool exercise. Here is what I came up with:
CREATE TABLE #tmp (ID int, StartDte datetime, EndDte datetime)
INSERT INTO #tmp values(1,'2017-09-03 15:04:00.000','2017-09-27 06:55:00.000')
INSERT INTO #tmp values(2,'2017-09-04 08:08:00.000','2017-09-06 18:00:00.000')
INSERT INTO #tmp values(3,'2017-09-04 13:00:00.000','2017-09-04 22:00:00.000')
INSERT INTO #tmp values(4,'2017-09-04 20:54:00.000','2017-09-08 14:30:00.000')
INSERT INTO #tmp values(5,'2017-09-04 20:52:00.000','2017-09-13 11:50:00.000')
INSERT INTO #tmp values(6,'2017-09-05 13:32:00.000','2017-09-11 14:49:00.000')
INSERT INTO #tmp values(7,'2017-09-05 13:17:00.000','2017-09-12 21:00:00.000')
INSERT INTO #tmp values(8,'2017-09-05 23:11:00.000','2017-09-06 07:38:00.000')
INSERT INTO #tmp values(9,'2017-09-05 11:35:00.000','2017-09-14 16:12:00.000')
INSERT INTO #tmp values(10,'2017-09-05 14:05:00.000','2017-09-11 16:30:00.000')
DECLARE
#StartDate DATE = '09/01/2017'
,#EndDate DATE = '10/01/2017'
, #nHours INT = 9
;WITH d(OrderDate) AS
(
SELECT DATEADD(DAY, n-1, #StartDate)
FROM (SELECT TOP (DATEDIFF(DAY, #StartDate, #EndDate) + 1)
ROW_NUMBER() OVER (ORDER BY [object_id]) FROM sys.all_objects) AS x(n)
)
, CTE AS(
select OrderDate, t2.*
from #tmp t2
cross apply(select orderdate from d ) d
where StartDte >= #StartDate and EndDte <= #EndDate)
select OrderDate,
SUM(CASE WHEN OrderDate >= StartDte and OrderDate <= EndDte THEN 1 ELSE 0 END) [No. Beds Occupied at 00:00],
SUM(CASE WHEN StartDTE <= DateAdd(hour,#nHours,CAST(OrderDate as datetime)) and DateAdd(hour,#nHours,CAST(OrderDate as datetime)) <= EndDte THEN 1 ELSE 0 END) [No. Beds Occupied at 09:00]
from CTE
GROUP BY OrderDate
This should allow you to check for any hour of the day using the #nHours parameter if you so choose. If you only want to see records that actually fall within your date range then you can filter the cross apply on start and end dates.
I have a table like this:
Value TimeStamp
1 2016-04-01 00:01:09.000
0 2016-04-01 00:01:09.000
0 2016-04-01 00:01:37.000
1 2016-04-01 00:01:37.000
1 2016-04-01 00:04:52.000
1 2016-04-01 00:09:58.000
1 2016-04-01 00:15:05.000
1 2016-04-01 00:20:11.000
1 2016-04-01 00:24:49.000
1 2016-04-01 00:29:55.000
1 2016-04-01 00:31:19.000
0 2016-04-01 00:31:19.000
0 2016-04-01 00:31:46.000
1 2016-04-01 00:31:46.000
1 2016-04-01 00:35:01.000
1 2016-04-01 00:40:07.000
1 2016-04-01 00:44:46.000
1 2016-04-01 00:49:52.000
1 2016-04-01 00:54:58.000
1 2016-04-01 01:00:04.000
1 2016-04-01 01:01:28.000
0 2016-04-01 01:01:28.000
0 2016-04-01 01:05:10.000
0 2016-04-01 01:09:49.000
And i want to count the seconds where value is 1 (switch ON) PER DAY, here is the deal; When the timeStamp repeats it means that there was a change from 0 to 1 or viceversa in the switch value, I already had many aproches like:
Q1 AS (SELECT ROW_NUMBER() OVER (ORDER BY TimeStamp) AS id,
Value, Timestamp
FROM Q2
GROUP BY idVBox, sensorType, sensorSubtype, timeStamp
HAVING COUNT(TimeStamp) > 1)
Then:
SELECT A.Value, DATEDIFF(SECOND,A.TimeStamp,B.TimeStamp)
FROM Q1 AS A
INNER JOIN Q1 AS B
ON B.ID = A.ID + 1
AND B.ID%2 = 0
Then Group by and Sum, but here the problem is that i don't know if the value comes in 1 or 0 from the past day, and the switch can change it's state quick and never get an actual value of it's actual state. Any other idea?
What you want to do, is add a dummy sensor state switch into your set at the beginning of the day before you start your calculation.
The extra records added are:
0, '2016-04-01 00:00:00'
1, '2016-04-01 00:00:00' -- This is conditional on the first record in your set having a value of 1
The overall query is below
Note: in order to determine what record is actually the first in sequence I used "ID" column.
;WITH Q0 AS(
-- Inserts a new record ( 0, '2016-04-01 00:00:00' ) to the beginning of the day
SELECT TOP 1 0 AS Value, CONVERT( DATETIME, CONVERT( DATE, LogDate )) AS LogDate
FROM #SwitchLog
UNION ALL
-- Inserts a new record ( 1, '2016-04-01 00:00:00' ) to the beginning of the day when the first record has Value = 1
SELECT Value, CONVERT( DATETIME, CONVERT( DATE, LogDate )) AS LogDate
FROM
( SELECT TOP 1 ID, Value, LogDate
FROM #SwitchLog
ORDER BY LogDate ASC, ID ASC ) AS DummyRecord --<-- NOTE: the use of a table ID column
WHERE Value = 1
UNION ALL
SELECT Value, LogDate
FROM #SwitchLog
)
,
Q1 AS (SELECT ROW_NUMBER() OVER (ORDER BY LogDate) AS id,
SUM( Value ) AS Value, LogDate
FROM Q0
GROUP BY LogDate
HAVING COUNT(LogDate) > 1)
SELECT A.Value, DATEDIFF(SECOND,A.LogDate,B.LogDate) AS Total
FROM Q1 AS A
INNER JOIN Q1 AS B
ON B.ID = A.ID + 1 AND B.ID%2 = 0
Output:
Value Total
----------- -----------
1 69
1 1782
1 1782
Same approach should be used to insert dummy record(s) at the end of the period/day ((day + 1) 00:00:00) to cater for situations where sensor value is 1 at the end of the day.
If using SQL Server 2012 then you could make good use of the LAG() function.
First, join the table on duplicate dates where value=1. Next, calculate difference between the on and the previous on. Finally, sum it up.
NOTE : The LAG() will return null for first on of the day.
SELECT
Seconds=SUM(X.Seconds)
FROM
(
SELECT
Seconds=DATEDIFF(SECOND,LAG(T1.TimeStamp) OVER (ORDER BY T1.TimeStamp),T1.TimeStamp)
FROM
MyTable T1
INNER JOIN MyTable T2 ON T2.TimeStamp=T1.TimeStamp AND T1.Value<>T2.Value
WHERE
T1.Value=1
)AS X
I've got a bit of a messy table on my hands that has two fields, a date field and a time field that are both strings. What I need to do is get the minimum date from those fields, or just the record itself if there is no date/time attached to it. Here's some sample data:
ID First Last Date Time
1 Joe Smith 2013-09-06 04:00
1 Joe Smith 2013-09-06 02:00
2 Jack Jones
3 John Jack 2013-09-05 06:00
3 John Jack 2013-09-15 15:00
What I would want from a query is to get the following:
ID First Last Date Time
1 Joe Smith 2013-09-06 02:00
2 Jack Jones
3 John Jack 2013-09-05 06:00
The min date/time for ID 1 and 3 and then just ID 2 back because he doesn't have a date/time. I cam up with the following query that gives me ID's 1 and 3 exactly as I would want them:
SELECT *
FROM test as t
where
cast(t.date + ' ' + t.time as Datetime ) = (select top 1 cast(p.date + ' ' + p.time as Datetime ) as dtime from test as p where t.ID = p.ID order by dtime)
But it doesn't return row number 2 at all. I imagine there's a better way to go about doing this. Any ideas?
You can do this with row_number():
select ID, First, Last, Date, Time
from (select t.*,
row_number() over (partition by id order by date, time) as seqnum
from test t
) t
where seqnum = 1;
Although storing dates and times as strings is not recommended, you at least do it right. The values use the ISO standard format (or close enough) so alphabetic sorting is the same as date/time sorting.
Assuming [Date] and [Time] are the types I think they are, and not strings:
SELECT ID,[First],[Last],[Date],[Time] FROM
(
SELECT ID,[First],[Last],[Date],[Time],rn = ROW_NUMBER()
OVER (PARTITION BY ID ORDER BY [Date], [Time])
FROM dbo.test
) AS t WHERE rn = 1;
Example:
DECLARE #x TABLE
(
ID INT,
[First] VARCHAR(32),
[Last] VARCHAR(32),
[Date] DATE,
[Time] TIME(0)
);
INSERT #x VALUES
(1,'Joe ','Smith','2013-09-06','04:00'),
(1,'Joe ','Smith','2013-09-06','02:00'),
(2,'Jack','Jones',NULL, NULL ),
(3,'John','Jack ','2013-09-05','06:00'),
(3,'John','Jack ','2013-09-15','15:00');
SELECT ID,[First],[Last],[Date],[Time] FROM
(
SELECT ID, [First],[Last],[Date],[Time],rn = ROW_NUMBER()
OVER (PARTITION BY ID ORDER BY [Date], [Time])
FROM #x
) AS x WHERE rn = 1;
Results:
ID First Last Date Time
-- ----- ----- ---------- --------
1 Joe Smith 2013-09-06 02:00:00
2 Jack Jones NULL NULL
3 John Jack 2013-09-05 06:00:00
Try:
SELECT
*
FROM
test as t
WHERE
CAST(t.date + ' ' + t.time as Datetime) =
(
select top 1 cast(p.date + ' ' + p.time as Datetime ) as dtime
from test as p
where t.ID = p.ID
order by dtime
)
OR (t.date='' AND t.time='')