SQL: How to get min date associated with patient value - sql

Trying to get earliest date associated with each PatientID for this period of time.
Current SQL returns multiple visits/documents within the time period for a patient I need to show only earliest date for patient tied to particular provider in date range.
Multiple Dates for PatientID
USE EHR
SET TRANSACTION ISOLATION LEVEL READ UNCOMMITTED
DECLARE #PROV NVARCHAR (255) ='KCOOPER0'
DECLARE #START_DATE DATETIME = '2017-09-18 00:00:00.000'
DECLARE #END_DATE DATETIME = '2017-12-17 23:59:59.999'
--DECLARE #START_DATE DATETIME = '2017-10-02 00:00:00.000'
--DECLARE #END_DATE DATETIME = '2017-12-31 23:59:59.999'
SELECT DISTINCT
PS.ID AS AppointmentID
, CL.Code AS PatientID
-- , SU.NameFirst AS PROVFNAME
-- , SU.NameLast AS PROVLNAME
-- , SU.NameSuffix AS PROVSUFFIX
, PS.ProviderId
, PS.ScheduledDateTime AS AppointmentDT
, PS.Duration
, PS.[TYPE] AS TypeDescription
, PS.IsActive as [Status]
, PS.ExternalId AS VisitID
-- , REPLACE(REPLACE(LOC.[Description],'[',''),']','') AS LOCATIONPLACE
, CDA.CreatedOn AS CDA
FROM PatientSchedule PS
INNER JOIN ContactsList CL WITH(NOLOCK) ON PS.PatientID=CL.ReferenceID
AND CL.Relation = 0
AND PS.ScheduledDateTime BETWEEN #START_DATE AND #END_DATE
INNER JOIN SystemUsers SU WITH(NOLOCK) ON PS.InterfaceCode=SU.InterfaceCode AND SU.Status='1'
INNER JOIN EMRDocuments ED ON PS.ID=ED.PatientScheduleId
AND ED.IsActive=1
LEFT JOIN
(SELECT DISTINCT ED.ID
,SU.NPI
,ED.PATIENTSCHEDULEID
,EDE.CreatedOn
FROM
EMRDOCUMENTS ED
INNER JOIN SystemUsers SU ON ED.ModifiedByID=SU.ID
AND ED.IsActive = 1
AND ED.IsSignedOff ='TRUE'
INNER JOIN EMRDocumentExport EDE ON ED.ID=EDE.DocumentId
AND EDE.LabCompanyName = 'FollowMyHealth_CCDA'
) CDA ON PS.ID=CDA.PatientScheduleId
WHERE --CL.Code = #PatientID
su.RegisteredProvider =1
AND SU.UserID =#PROV
ORDER BY CL.Code, CDA.CreatedOn

This is the general idea. You can fill in the details.
select your fields
from your tables
join (select patientId, min(the date field you want) minDate
from your tables
where whatever
group by patientId) minDates
on minDates.patientId = sometable.patientId
and the date field you want = minDate
etc

A join-less alternative, using window function and either a Common Table Expression or sticking with a subselect.
using CTE:
with mindates as (
select field1, field2, ...,
AppointmentDT,
min(AppointmentDT) OVER (PARTITION BY PatientID) minptAppointmentDT
from table
)
select field1, field2, ... , AppointmentDT from mindate_table
where AppointmentDT = minptAppointmentDT
using subselect:
select field1, field2, ... , AppointmentDT from
(select field1, field2, ...,
AppointmentDT,
min(AppointmentDT) OVER (PARTITION BY PatientID) minptAppointmentDT
from table) mindates
where AppointmentDT = minptAppointmentDT

Related

How to write SQL query as below

I have a table below
I this table I want to return service 90791 and I want to return the service after that scheduled(H2015).
How can i return it .
starttime and endtime datatype :-char
servicedate data type :-datetime
My current Work:-
declare #date date ,#starttime time ,#endtime time
with AllEntityAccess as (select S.serviceCode,S.clientId,S.serviceDate, S.startTime, S.endTime from servicenotes S
left outer join Clients C on S.clientId = C.clientId where C.clientId = '34'
)
select #date=serviceDate,#starttime=startTime ,#endtime=endTime from AllEntityAccess where serviceCode='90791' order by serviceDate desc
select serviceDate,startTime,* from servicenotes S
left outer join Clients C on S.clientId = C.clientId where C.clientId = '34' and serviceDate >= #date and startTime>= #endtime order by S.startTime asc
You can write query like this
DECLARE #ID INT = (SELECT Id
FROM table
WHERE NAME = 'x'
ORDER BY joinedDate ASC);--assuming your Id column is int
SELECT *
FROM table
WHERE Id >= ID;
declare #last bigint
select top 1 #last=Id
from your_table
where Name='x'
order by Id desc
select top 2 *
from your_table
where Id >= #last
order by Id asc
After edit: Use your queries in "My current work" but change the last to:
select top 2 *
from servicenotes S
where serviceDate>=#date and startTime >= #starttime
order by serviceDate asc, startTime asc

Taking most recent values in sum over date range

I have a table which has the following columns: DeskID *, ProductID *, Date *, Amount (where the columns marked with * make the primary key). The products in use vary over time, as represented in the image below.
Table format on the left, and a (hopefully) intuitive representation of the data on the right for one desk
The objective is to have the sum of the latest amounts of products by desk and date, including products which are no longer in use, over a date range.
e.g. using the data above the desired table is:
So on the 1st Jan, the sum is 1 of Product A
On the 2nd Jan, the sum is 2 of A and 5 of B, so 7
On the 4th Jan, the sum is 1 of A (out of use, so take the value from the 3rd), 5 of B, and 2 of C, so 8 in total
etc.
I have tried using a partition on the desk and product ordered by date to get the most recent value and turned the following code into a function (Function1 below) with #date Date parameter
select #date 'Date', t.DeskID, SUM(t.Amount) 'Sum' from (
select #date 'Date', t.DeskID, t.ProductID, t.Amount
, row_number() over (partition by t.DeskID, t.ProductID order by t.Date desc) as roworder
from Table1 t
where 1 = 1
and t.Date <= #date
) t
where t.roworder = 1
group by t.DeskID
And then using a utility calendar table and cross apply to get the required values over a time range, as below
select * from Calendar c
cross apply Function1(c.CalendarDate)
where c.CalendarDate >= '20190101' and c.CalendarDate <= '20191009'
This has the expected results, but is far too slow. Currently each desk uses around 50 products, and the products roll every month, so after just 5 years each desk has a history of ~3000 products, which causes the whole thing to grind to a halt. (Roughly 30 seconds for a range of a single month)
Is there a better approach?
Change your function to the following should be faster:
select #date 'Date', t.DeskID, SUM(t.Amount) 'Sum'
FROM (SELECT m.DeskID, m.ProductID, MAX(m.[Date) AS MaxDate
FROM Table1 m
where m.[Date] <= #date) d
INNER JOIN Table1 t
ON d.DeskID=t.DeskID
AND d.ProductID=t.ProductID
and t.[Date] = d.MaxDate
group by t.DeskID
The performance of TVF usually suffers. The following removes the TVF completely:
-- DROP TABLE Table1;
CREATE TABLE Table1 (DeskID int not null, ProductID nvarchar(32) not null, [Date] Date not null, Amount int not null, PRIMARY KEY ([Date],DeskID,ProductID));
INSERT Table1(DeskID,ProductID,[Date],Amount)
VALUES (1,'A','2019-01-01',1),(1,'A','2019-01-02',2),(1,'B','2019-01-02',5),(1,'A','2019-01-03',1)
,(1,'B','2019-01-03',4),(1,'C','2019-01-03',3),(1,'B','2019-01-04',5),(1,'C','2019-01-04',2),(1,'C','2019-01-05',2)
GO
DECLARE #StartDate date=N'2019-01-01';
DECLARE #EndDate date=N'2019-01-05';
;WITH cte_p
AS
(
SELECT DISTINCT DeskID,ProductID
FROM Table1
WHERE [Date] <= #EndDate
),
cte_a
AS
(
SELECT #StartDate AS [Date], p.DeskID, p.ProductID, ISNULL(a.Amount,0) AS Amount
FROM (
SELECT t.DeskID, t.ProductID
, MAX(t.Date) AS FirstDate
FROM Table1 t
WHERE t.Date <= #StartDate
GROUP BY t.DeskID, t.ProductID) f
INNER JOIN Table1 a
ON f.DeskID=a.DeskID
AND f.ProductID=a.ProductID
AND f.[FirstDate]=a.[Date]
RIGHT JOIN cte_p p
ON p.DeskID=a.DeskID
AND p.ProductID=a.ProductID
UNION ALL
SELECT DATEADD(DAY,1,a.[Date]) AS [Date], t.DeskID, t.ProductID, t.Amount
FROM Table1 t
INNER JOIN cte_a a
ON t.DeskID=a.DeskID
AND t.ProductID=a.ProductID
AND t.[Date] > a.[Date]
AND t.[Date] <= DATEADD(DAY,1,a.[Date])
WHERE a.[Date]<#EndDate
UNION ALL
SELECT DATEADD(DAY,1,a.[Date]) AS [Date], a.DeskID, a.ProductID, a.Amount
FROM cte_a a
WHERE NOT EXISTS(SELECT 1 FROM Table1 t
WHERE t.DeskID=a.DeskID
AND t.ProductID=a.ProductID
AND t.[Date] > a.[Date]
AND t.[Date] <= DATEADD(DAY,1,a.[Date]))
AND a.[Date]<#EndDate
)
SELECT [Date], DeskID, SUM(Amount)
FROM cte_a
GROUP BY [Date], DeskID;

Why stored procedure returns wrong sum for each group?

I have this query but SUM(SUM(inv.ServicePrice)) over () as TotalRevenueAllServices
return me the wrong sum. I actually want to get sum of all sums that I have done for each group but it returns wrong value.
Select top(3) s.ServiceName, Count(inv.fk_ServiceID) as TotalServicesCount, Sum(inv.ServicePrice) TotalServicesRevenue,
SUM(SUM(inv.ServicePrice)) over () as TotalRevenueAllServices
from Invoices inv
inner join Services s
on s.ServiceID= inv.fk_ServiceID
group by inv.fk_ServiceID, s.ServiceName
Order By ServiceName asc
declare #FromDate date= '22/Nov/2017',
#ToDate date= '24/Nov/2018'
Set #ToDate= ISNULL(#ToDate, getdate());
with MainTable
as
(
Select top(3) s.ServiceName, Count(inv.fk_ServiceID) as TotalServicesCount, Sum(inv.ServicePrice) TotalServicesRevenue
from Invoices inv
inner join Services s
on s.ServiceID= inv.fk_ServiceID
--where CAST(inv.EntryDateTime as DATE) between #FromDate and #ToDate
group by inv.fk_ServiceID, s.ServiceName
Order By ServiceName asc
)
select * , (select sum(totalservicesrevenue) from MainTable) 'AllServicesRevenue'
, (select sum(TotalServicesCount) from MainTable) 'OverallServices'
from MainTable

Aggregate for each day over time series, without using non-equijoin logic

Initial Question
Given the following dataset paired with a dates table:
MembershipId | ValidFromDate | ValidToDate
==========================================
0001 | 1997-01-01 | 2006-05-09
0002 | 1997-01-01 | 2017-05-12
0003 | 2005-06-02 | 2009-02-07
How many Memberships were open on any given day or timeseries of days?
Initial Answer
Following this question being asked here, this answer provided the necessary functionality:
select d.[Date]
,count(m.MembershipID) as MembershipCount
from DIM.[Date] as d
left join Memberships as m
on(d.[Date] between m.ValidFromDateKey and m.ValidToDateKey)
where d.CalendarYear = 2016
group by d.[Date]
order by d.[Date];
though a commenter remarked that There are other approaches when the non-equijoin takes too long.
Followup
As such, what would the equijoin only logic look like to replicate the output of the query above?
Progress So Far
From the answers provided so far I have come up with the below, which outperforms on the hardware I am working with across 3.2 million Membership records:
declare #s date = '20160101';
declare #e date = getdate();
with s as
(
select d.[Date] as d
,count(s.MembershipID) as s
from dbo.Dates as d
join dbo.Memberships as s
on d.[Date] = s.ValidFromDateKey
group by d.[Date]
)
,e as
(
select d.[Date] as d
,count(e.MembershipID) as e
from dbo.Dates as d
join dbo.Memberships as e
on d.[Date] = e.ValidToDateKey
group by d.[Date]
),c as
(
select isnull(s.d,e.d) as d
,sum(isnull(s.s,0) - isnull(e.e,0)) over (order by isnull(s.d,e.d)) as c
from s
full join e
on s.d = e.d
)
select d.[Date]
,c.c
from dbo.Dates as d
left join c
on d.[Date] = c.d
where d.[Date] between #s and #e
order by d.[Date]
;
Following on from that, to split this aggregate into constituent groups per day I have the following, which is also performing well:
declare #s date = '20160101';
declare #e date = getdate();
with s as
(
select d.[Date] as d
,s.MembershipGrouping as g
,count(s.MembershipID) as s
from dbo.Dates as d
join dbo.Memberships as s
on d.[Date] = s.ValidFromDateKey
group by d.[Date]
,s.MembershipGrouping
)
,e as
(
select d.[Date] as d
,e..MembershipGrouping as g
,count(e.MembershipID) as e
from dbo.Dates as d
join dbo.Memberships as e
on d.[Date] = e.ValidToDateKey
group by d.[Date]
,e.MembershipGrouping
),c as
(
select isnull(s.d,e.d) as d
,isnull(s.g,e.g) as g
,sum(isnull(s.s,0) - isnull(e.e,0)) over (partition by isnull(s.g,e.g) order by isnull(s.d,e.d)) as c
from s
full join e
on s.d = e.d
and s.g = e.g
)
select d.[Date]
,c.g
,c.c
from dbo.Dates as d
left join c
on d.[Date] = c.d
where d.[Date] between #s and #e
order by d.[Date]
,c.g
;
Can anyone improve on the above?
If most of your membership validity intervals are longer than few days, have a look at an answer by Martin Smith. That approach is likely to be faster.
When you take calendar table (DIM.[Date]) and left join it with Memberships, you may end up scanning the Memberships table for each date of the range. Even if there is an index on (ValidFromDate, ValidToDate), it may not be super useful.
It is easy to turn it around.
Scan the Memberships table only once and for each membership find those dates that are valid using CROSS APPLY.
Sample data
DECLARE #T TABLE (MembershipId int, ValidFromDate date, ValidToDate date);
INSERT INTO #T VALUES
(1, '1997-01-01', '2006-05-09'),
(2, '1997-01-01', '2017-05-12'),
(3, '2005-06-02', '2009-02-07');
DECLARE #RangeFrom date = '2006-01-01';
DECLARE #RangeTo date = '2006-12-31';
Query 1
SELECT
CA.dt
,COUNT(*) AS MembershipCount
FROM
#T AS Memberships
CROSS APPLY
(
SELECT dbo.Calendar.dt
FROM dbo.Calendar
WHERE
dbo.Calendar.dt >= Memberships.ValidFromDate
AND dbo.Calendar.dt <= Memberships.ValidToDate
AND dbo.Calendar.dt >= #RangeFrom
AND dbo.Calendar.dt <= #RangeTo
) AS CA
GROUP BY
CA.dt
ORDER BY
CA.dt
OPTION(RECOMPILE);
OPTION(RECOMPILE) is not really needed, I include it in all queries when I compare execution plans to be sure that I'm getting the latest plan when I play with the queries.
When I looked at the plan of this query I saw that the seek in the Calendar.dt table was using only ValidFromDate and ValidToDate, the #RangeFrom and #RangeTo were pushed to the residue predicate. It is not ideal. The optimiser is not smart enough to calculate maximum of two dates (ValidFromDate and #RangeFrom) and use that date as a starting point of the seek.
It is easy to help the optimiser:
Query 2
SELECT
CA.dt
,COUNT(*) AS MembershipCount
FROM
#T AS Memberships
CROSS APPLY
(
SELECT dbo.Calendar.dt
FROM dbo.Calendar
WHERE
dbo.Calendar.dt >=
CASE WHEN Memberships.ValidFromDate > #RangeFrom
THEN Memberships.ValidFromDate
ELSE #RangeFrom END
AND dbo.Calendar.dt <=
CASE WHEN Memberships.ValidToDate < #RangeTo
THEN Memberships.ValidToDate
ELSE #RangeTo END
) AS CA
GROUP BY
CA.dt
ORDER BY
CA.dt
OPTION(RECOMPILE)
;
In this query the seek is optimal and doesn't read dates that may be discarded later.
Finally, you may not need to scan the whole Memberships table.
We need only those rows where the given range of dates intersects with the valid range of the membership.
Query 3
SELECT
CA.dt
,COUNT(*) AS MembershipCount
FROM
#T AS Memberships
CROSS APPLY
(
SELECT dbo.Calendar.dt
FROM dbo.Calendar
WHERE
dbo.Calendar.dt >=
CASE WHEN Memberships.ValidFromDate > #RangeFrom
THEN Memberships.ValidFromDate
ELSE #RangeFrom END
AND dbo.Calendar.dt <=
CASE WHEN Memberships.ValidToDate < #RangeTo
THEN Memberships.ValidToDate
ELSE #RangeTo END
) AS CA
WHERE
Memberships.ValidToDate >= #RangeFrom
AND Memberships.ValidFromDate <= #RangeTo
GROUP BY
CA.dt
ORDER BY
CA.dt
OPTION(RECOMPILE)
;
Two intervals [a1;a2] and [b1;b2] intersect when
a2 >= b1 and a1 <= b2
These queries assume that Calendar table has an index on dt.
You should try and see what indexes are better for the Memberships table.
For the last query, if the table is rather large, most likely two separate indexes on ValidFromDate and on ValidToDate would be better than one index on (ValidFromDate, ValidToDate).
You should try different queries and measure their performance on the real hardware with real data. Performance may depend on the data distribution, how many memberships there are, what are their valid dates, how wide or narrow is the given range, etc.
I recommend to use a great tool called SQL Sentry Plan Explorer to analyse and compare execution plans. It is free. It shows a lot of useful stats, such as execution time and number of reads for each query. The screenshots above are from this tool.
On the assumption your date dimension contains all dates contained in all membership periods you can use something like the following.
The join is an equi join so can use hash join or merge join not just nested loops (which will execute the inside sub tree once for each outer row).
Assuming index on (ValidToDate) include(ValidFromDate) or reverse this can use a single seek against Memberships and a single scan of the date dimension. The below has an elapsed time of less than a second for me to return the results for a year against a table with 3.2 million members and general active membership of 1.4 million (script)
DECLARE #StartDate DATE = '2016-01-01',
#EndDate DATE = '2016-12-31';
WITH MD
AS (SELECT Date,
SUM(Adj) AS MemberDelta
FROM Memberships
CROSS APPLY (VALUES ( ValidFromDate, +1),
--Membership count decremented day after the ValidToDate
(DATEADD(DAY, 1, ValidToDate), -1) ) V(Date, Adj)
WHERE
--Members already expired before the time range of interest can be ignored
ValidToDate >= #StartDate
AND
--Members whose membership starts after the time range of interest can be ignored
ValidFromDate <= #EndDate
GROUP BY Date),
MC
AS (SELECT DD.DateKey,
SUM(MemberDelta) OVER (ORDER BY DD.DateKey ROWS UNBOUNDED PRECEDING) AS CountOfNonIgnoredMembers
FROM DIM_DATE DD
LEFT JOIN MD
ON MD.Date = DD.DateKey)
SELECT DateKey,
CountOfNonIgnoredMembers AS MembershipCount
FROM MC
WHERE DateKey BETWEEN #StartDate AND #EndDate
ORDER BY DateKey
Demo (uses extended period as the calendar year of 2016 isn't very interesting with the example data)
One approach is to first use an INNER JOIN to find the set of matches and COUNT() to project MemberCount GROUPed BY DateKey, then UNION ALL with the same set of dates, with a 0 on that projection for the count of members for each date. The last step is to SUM() the MemberCount of this union, and GROUP BY DateKey. As requested, this avoids LEFT JOIN and NOT EXISTS. As another member pointed out, this is not an equi-join, because we need to use a range, but I think it does what you intend.
This will serve up 1 year's worth of data with around 100k logical reads. On an ordinary laptop with a spinning disk, from cold cache, it serves 1 month in under a second (with correct counts).
Here is an example that creates 3.3 million rows of random duration. The query at the bottom returns one month's worth of data.
--Stay quiet for a moment
SET NOCOUNT ON
SET STATISTICS IO OFF
SET STATISTICS TIME OFF
--Clean up if re-running
DROP TABLE IF EXISTS DIM_DATE
DROP TABLE IF EXISTS FACT_MEMBER
--Date dimension
CREATE TABLE DIM_DATE
(
DateKey DATE NOT NULL
)
--Membership fact
CREATE TABLE FACT_MEMBER
(
MembershipId INT NOT NULL
, ValidFromDateKey DATE NOT NULL
, ValidToDateKey DATE NOT NULL
)
--Populate Date dimension from 2001 through end of 2018
DECLARE #startDate DATE = '2001-01-01'
DECLARE #endDate DATE = '2018-12-31'
;WITH CTE_DATE AS
(
SELECT #startDate AS DateKey
UNION ALL
SELECT
DATEADD(DAY, 1, DateKey)
FROM
CTE_DATE AS D
WHERE
D.DateKey < #endDate
)
INSERT INTO
DIM_DATE
(
DateKey
)
SELECT
D.DateKey
FROM
CTE_DATE AS D
OPTION (MAXRECURSION 32767)
--Populate Membership fact with members having a random membership length from 1 to 36 months
;WITH CTE_DATE AS
(
SELECT #startDate AS DateKey
UNION ALL
SELECT
DATEADD(DAY, 1, DateKey)
FROM
CTE_DATE AS D
WHERE
D.DateKey < #endDate
)
,CTE_MEMBER AS
(
SELECT 1 AS MembershipId
UNION ALL
SELECT MembershipId + 1 FROM CTE_MEMBER WHERE MembershipId < 500
)
,
CTE_MEMBERSHIP
AS
(
SELECT
ROW_NUMBER() OVER (ORDER BY NEWID()) AS MembershipId
, D.DateKey AS ValidFromDateKey
FROM
CTE_DATE AS D
CROSS JOIN CTE_MEMBER AS M
)
INSERT INTO
FACT_MEMBER
(
MembershipId
, ValidFromDateKey
, ValidToDateKey
)
SELECT
M.MembershipId
, M.ValidFromDateKey
, DATEADD(MONTH, FLOOR(RAND(CHECKSUM(NEWID())) * (36-1)+1), M.ValidFromDateKey) AS ValidToDateKey
FROM
CTE_MEMBERSHIP AS M
OPTION (MAXRECURSION 32767)
--Add clustered Primary Key to Date dimension
ALTER TABLE DIM_DATE ADD CONSTRAINT PK_DATE PRIMARY KEY CLUSTERED
(
DateKey ASC
)
--Index
--(Optimize in your spare time)
DROP INDEX IF EXISTS SK_FACT_MEMBER ON FACT_MEMBER
CREATE CLUSTERED INDEX SK_FACT_MEMBER ON FACT_MEMBER
(
ValidFromDateKey ASC
, ValidToDateKey ASC
, MembershipId ASC
)
RETURN
--Start test
--Emit stats
SET STATISTICS IO ON
SET STATISTICS TIME ON
--Establish range of dates
DECLARE
#rangeStartDate DATE = '2010-01-01'
, #rangeEndDate DATE = '2010-01-31'
--UNION the count of members for a specific date range with the "zero" set for the same range, and SUM() the counts
;WITH CTE_MEMBER
AS
(
SELECT
D.DateKey
, COUNT(*) AS MembershipCount
FROM
DIM_DATE AS D
INNER JOIN FACT_MEMBER AS M ON
M.ValidFromDateKey <= #rangeEndDate
AND M.ValidToDateKey >= #rangeStartDate
AND D.DateKey BETWEEN M.ValidFromDateKey AND M.ValidToDateKey
WHERE
D.DateKey BETWEEN #rangeStartDate AND #rangeEndDate
GROUP BY
D.DateKey
UNION ALL
SELECT
D.DateKey
, 0 AS MembershipCount
FROM
DIM_DATE AS D
WHERE
D.DateKey BETWEEN #rangeStartDate AND #rangeEndDate
)
SELECT
M.DateKey
, SUM(M.MembershipCount) AS MembershipCount
FROM
CTE_MEMBER AS M
GROUP BY
M.DateKey
ORDER BY
M.DateKey ASC
OPTION (RECOMPILE, MAXDOP 1)
Here's how I'd solve this problem with equijoin:
--data generation
declare #Membership table (MembershipId varchar(10), ValidFromDate date, ValidToDate date)
insert into #Membership values
('0001', '1997-01-01', '2006-05-09'),
('0002', '1997-01-01', '2017-05-12'),
('0003', '2005-06-02', '2009-02-07')
declare #startDate date, #endDate date
select #startDate = MIN(ValidFromDate), #endDate = max(ValidToDate) from #Membership
--in order to use equijoin I need all days between min date and max date from Membership table (both columns)
;with cte as (
select #startDate [date]
union all
select DATEADD(day, 1, [date]) from cte
where [date] < #endDate
)
--in this query, we will assign value to each day:
--one, if project started on that day
--minus one, if project ended on that day
--then, it's enough to (cumulative) sum all this values to get how many projects were ongoing on particular day
select [date],
sum(case when [DATE] = ValidFromDate then 1 else 0 end +
case when [DATE] = ValidToDate then -1 else 0 end)
over (order by [date] rows between unbounded preceding and current row)
from cte [c]
left join #Membership [m]
on [c].[date] = [m].ValidFromDate or [c].[date] = [m].ValidToDate
option (maxrecursion 0)
Here's another solution:
--data generation
declare #Membership table (MembershipId varchar(10), ValidFromDate date, ValidToDate date)
insert into #Membership values
('0001', '1997-01-01', '2006-05-09'),
('0002', '1997-01-01', '2017-05-12'),
('0003', '2005-06-02', '2009-02-07')
;with cte as (
select CAST('2016-01-01' as date) [date]
union all
select DATEADD(day, 1, [date]) from cte
where [date] < '2016-12-31'
)
select [date],
(select COUNT(*) from #Membership where ValidFromDate < [date]) -
(select COUNT(*) from #Membership where ValidToDate < [date]) [ongoing]
from cte
option (maxrecursion 0)
Pay attention, I think #PittsburghDBA is right when it says that current query return wrong result.
The last day of membership is not counted and so final sum is lower than it should be.
I have corrected it in this version.
This should improve a bit your actual progress:
declare #s date = '20160101';
declare #e date = getdate();
with
x as (
select d, sum(c) c
from (
select ValidFromDateKey d, count(MembershipID) c
from Memberships
group by ValidFromDateKey
union all
-- dateadd needed to count last day of membership too!!
select dateadd(dd, 1, ValidToDateKey) d, -count(MembershipID) c
from Memberships
group by ValidToDateKey
)x
group by d
),
c as
(
select d, sum(x.c) over (order by d) as c
from x
)
select d.day, c cnt
from calendar d
left join c on d.day = c.d
where d.day between #s and #e
order by d.day;
First of all, your query yields '1' as MembershipCount even if no active membership exists for the given date.
You should return SUM(CASE WHEN m.MembershipID IS NOT NULL THEN 1 ELSE 0 END) AS MembershipCount.
For optimal performance create an index on Memberships(ValidFromDateKey, ValidToDateKey, MembershipId) and another on DIM.[Date](CalendarYear, DateKey).
With that done, the optimal query shall be:
DECLARE #CalendarYear INT = 2000
SELECT dim.DateKey, SUM(CASE WHEN con.MembershipID IS NOT NULL THEN 1 ELSE 0 END) AS MembershipCount
FROM
DIM.[Date] dim
LEFT OUTER JOIN (
SELECT ValidFromDateKey, ValidToDateKey, MembershipID
FROM Memberships
WHERE
ValidFromDateKey <= CONVERT(DATETIME, CONVERT(VARCHAR, #CalendarYear) + '1231')
AND ValidToDateKey >= CONVERT(DATETIME, CONVERT(VARCHAR, #CalendarYear) + '0101')
) con
ON dim.DateKey BETWEEN con.ValidFromDateKey AND con.ValidToDateKey
WHERE dim.CalendarYear = #CalendarYear
GROUP BY dim.DateKey
ORDER BY dim.DateKey
Now, for your last question, what would be the equijoin equivalent query.
There is NO WAY you can rewrite this as a non-equijoin!
Equijoin doesn't imply using join sintax. Equijoin implies using an equals predicate, whatever the sintax.
Your query yields a range comparison, hence equals doesn't apply: a between or similar is required.

SQL grouping and running total of open items for a date range

I have a table of items that, for sake of simplicity, contains the ItemID, the StartDate, and the EndDate for a list of items.
ItemID StartDate EndDate
1 1/1/2011 1/15/2011
2 1/2/2011 1/14/2011
3 1/5/2011 1/17/2011
...
My goal is to be able to join this table to a table with a sequential list of dates,
and say both how many items are open on a particular date, and also how many items are cumulatively open.
Date ItemsOpened CumulativeItemsOpen
1/1/2011 1 1
1/2/2011 1 2
...
I can see how this would be done with a WHILE loop,
but that has performance implications. I'm wondering how
this could be done with a set-based approach?
SELECT COUNT(CASE WHEN d.CheckDate = i.StartDate THEN 1 ELSE NULL END)
AS ItemsOpened
, COUNT(i.StartDate)
AS ItemsOpenedCumulative
FROM Dates AS d
LEFT JOIN Items AS i
ON d.CheckDate BETWEEN i.StartDate AND i.EndDate
GROUP BY d.CheckDate
This may give you what you want
SELECT DATE,
SUM(ItemOpened) AS ItemsOpened,
COUNT(StartDate) AS ItemsOpenedCumulative
FROM
(
SELECT d.Date, i.startdate, i.enddate,
CASE WHEN i.StartDate = d.Date THEN 1 ELSE 0 END AS ItemOpened
FROM Dates d
LEFT OUTER JOIN Items i ON d.Date BETWEEN i.StartDate AND i.EndDate
) AS x
GROUP BY DATE
ORDER BY DATE
This assumes that your date values are DATE data type. Or, the dates are DATETIME with no time values.
You may find this useful. The recusive part can be replaced with a table. To demonstrate it works I had to populate some sort of date table. As you can see, the actual sql is short and simple.
DECLARE #i table (itemid INT, startdate DATE, enddate DATE)
INSERT #i VALUES (1,'1/1/2011', '1/15/2011')
INSERT #i VALUES (2,'1/2/2011', '1/14/2011')
INSERT #i VALUES (3,'1/5/2011', '1/17/2011')
DECLARE #from DATE
DECLARE #to DATE
SET #from = '1/1/2011'
SET #to = '1/18/2011'
-- the recusive sql is strictly to make a datelist between #from and #to
;WITH cte(Date)
AS (
SELECT #from DATE
UNION ALL
SELECT DATEADD(day, 1, DATE)
FROM cte ch
WHERE DATE < #to
)
SELECT cte.Date, sum(case when cte.Date=i.startdate then 1 else 0 end) ItemsOpened, count(i.itemid) ItemsOpenedCumulative
FROM cte
left join #i i on cte.Date between i.startdate and i.enddate
GROUP BY cte.Date
OPTION( MAXRECURSION 0)
If you are on SQL Server 2005+, you could use a recursive CTE to obtain running totals, with the additional help of the ranking function ROW_NUMBER(), like this:
WITH grouped AS (
SELECT
d.Date,
ItemsOpened = COUNT(i.ItemID),
rn = ROW_NUMBER() OVER (ORDER BY d.Date)
FROM Dates d
LEFT JOIN Items i ON d.Date BETWEEN i.StartDate AND i.EndDate
GROUP BY d.Date
WHERE d.Date BETWEEN #FilterStartDate AND #FilterEndDate
),
cumulative AS (
SELECT
Date,
ItemsOpened,
ItemsOpenedCumulative = ItemsOpened
FROM grouped
WHERE rn = 1
UNION ALL
SELECT
g.Date,
g.ItemsOpened,
ItemsOpenedCumulative = g.ItemsOpenedCumulative + c.ItemsOpened
FROM grouped g
INNER JOIN cumulative c ON g.Date = DATEADD(day, 1, c.Date)
)
SELECT *
FROM cumulative