Related
I have this query, and it returns the following result, I need to delete the records repeated by date, and keep the oldest, how could I do this?
select
a.EMP_ID, a.EMP_DATE,
from
EMPLOYES a
inner join
TABLE2 b on a.table2ID = b.table2ID and b.ID_TYPE = 'E'
where
a.ID = 'VJAHAJHSJHDAJHSJDH'
and year(a.DATE) = 2021
and month(a.DATE) = 1
and a.ID <> 31
order by
a.DATE;
Additionally, I would like to fill in the missing days of the month ... and put them empty if I don't have that data, can this be done?
I would appreciate if you could guide me to solve this problem
Thank you!
The other answers miss some of the requirement..
Initial step - do this once only. Make a calendar table. This will come in handy for all sorts of things over the time:
DECLARE #Year INT = '2000';
DECLARE #YearCnt INT = 50 ;
DECLARE #StartDate DATE = DATEFROMPARTS(#Year, '01','01')
DECLARE #EndDate DATE = DATEADD(DAY, -1, DATEADD(YEAR, #YearCnt, #StartDate));
;WITH Cal(n) AS
(
SELECT 0 UNION ALL SELECT n + 1 FROM Cal
WHERE n < DATEDIFF(DAY, #StartDate, #EndDate)
),
FnlDt(d, n) AS
(
SELECT DATEADD(DAY, n, #StartDate), n FROM Cal
),
FinalCte AS
(
SELECT
[D] = CONVERT(DATE,d),
[Dy] = DATEPART(DAY, d),
[Mo] = DATENAME(MONTH, d),
[Yr] = DATEPART(YEAR, d),
[DN] = DATENAME(WEEKDAY, d),
[N] = n
FROM FnlDt
)
SELECT * INTO Cal FROM finalCte
ORDER BY [Date]
OPTION (MAXRECURSION 0);
credit: mostly this site
Now we can write some simple query to stick your data (with one small addition) onto it:
--your query, minus the date bits in the WHERE, and with a ROW_NUMBER
WITH yourQuery AS(
SELECT a.emp_id, a.emp_date,
ROW_NUMBER() OVER(PARTITION BY CAST(a.emp_date AS DATE) ORDER BY a.emp_date) rn
FROM EMPLOYES a
INNER JOIN TABLE2 b on a.table2ID = b.table2ID
WHERE a.emp_id = 'VJAHAJHSJHDAJHSJDH' AND a.id <> 31 AND b.id_type = 'E'
)
--your query, left joined onto the cal table so that you get a row for every day even if there is no emp data for that day
SELECT c.d, yq.*
FROM
Cal c
LEFT JOIN yourQuery yq
ON
c.d = CAST(yq.emp_date AS DATE) AND --cut the time off
yq.rn = 1 --keep only the earliest time per day
WHERE
c.d BETWEEN '2021-01-01' AND EOMONTH('2021-01-01')
We add a rownumbering to your table, it restarts every time the date changes and counts up in order of time. We make this into a CTE (or a subquery, CTE is cleaner) then we simply left join it to the calendar table. This means that for any date you don't have data, you still have the calendar date. For any days you do have data, the rownumber rn being a condition of the join means that only the first datetime from each day is present in the results
Note: something is wonky about your question . You said you SELECT a.emp_id and your results show 'VJAHAJHSJHDAJHSJDH' is the emp id, but your where clause says a.id twice, once as a string and once as a number - this can't be right, so I've guessed at fixing it but I suspect you have translated your query into something for SO, perhaps to hide real column names.. Also your SELECT has a dangling comma that is a syntax error.
If you have translated/obscured your real query, make absolutely sure you understand any answer here when translating it back. It's very frustrating when someone is coming back and saying "hi your query doesn't work" then it turns out that they damaged it trying to translate it back to their own db, because they hid the real column names in the question..
FInally, do not use functions on table data in a where clause; it generally kills indexing. Always try and find a way of leaving table data alone. Want all of january? Do like I did, and say table.datecolumn BETWEEN firstofjan AND endofjan etc - SQLserver at least stands a chance of using an index for this, rather than calling a function on every date in the table, every time the query is run
You can use ROW_NUMBER
WITH CTE AS
(
SELECT a.EMP_ID, a.EMP_DATE,
RN = ROW_NUMBER() OVER (PARTITION BY a.EMP_ID, CAST(a.DATE as Date) ORDER BY a.DATE ASC)
from EMPLOYES a INNER JOIN TABLE2 b
on a.table2ID = b.table2ID
and b.ID_TYPE = 'E'
where a.ID = 'VJAHAJHSJHDAJHSJDH'
and year(a.DATE) = 2021
and MONTH(a.DATE) = 1
and a.ID <> 31
)
SELECT * FROM CTE
WHERE RN = 1
Try with an aggregate function MAX or MIN
create table #tmp(dt datetime, val numeric(4,2))
insert into #tmp values ('2021-01-01 10:30:35', 1)
insert into #tmp values ('2021-01-02 10:30:35', 2)
insert into #tmp values ('2021-01-02 11:30:35', 3)
insert into #tmp values ('2021-01-03 10:35:35', 4)
select * from #tmp
select tmp.*
from #tmp tmp
inner join
(select max(dt) as dt, cast(dt as date) as dt_aux from #tmp group by cast(dt as date)) compressed_rows on
tmp.dt = compressed_rows.dt
drop table #tmp
results:
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;
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.
I'm looking for a way, how to calculate formula as below:
month 1
result_1 = result_0 + (number_of_open - number_of_close), where result_0 = 0
month 2
result_2 = result_1 + (number_of_open - number_of_close)
month 3
result_3 = result_2 + (number_of_open - number_of_close)
I know how to calculate it when results are shown from the very beginning, means:
but when I have some dates chosen, for example from February 1, 2015, it doesn't count correctly:
It seems to be counted from the taken moment.
Is there any idea how to solve it?
I found a good enough workaround for this. I've been searching how to solve this, and found that I can use SUM() OVER() and it will work as a Running Total. But if I need it to work inside given time-range, I had to use subquery, so I was not able to make it with CTE and had to use temp tables. My code is now:
IF OBJECT_ID('tempdb..#Temp1') IS NOT NULL BEGIN
drop table #Temp1
end
SELECT * into #Temp1
from (
SELECT
datepart(yy, t3.[datestamp]) AS full_year
,datepart(mm, t3.[datestamp]) AS month_number
,count(*) as number_of_activities
,t2.affected_item
FROM [sm70prod].[dbo].[ACTSVCMGTM1] AS t3
JOIN [sm70prod].[dbo].[INCIDENTSM1] AS t2 ON t3.number = t2.incident_id
WHERE
t2.affected_item like 'Service_name'
AND (t3.[type] LIKE 'Open')
GROUP BY t2.affected_item, datepart(yy, t3.[datestamp]), datepart(mm, t3.[datestamp])
)
as databases (full_year, month_number, number_of_activities, affected_item)
;
IF OBJECT_ID('tempdb..#Temp2') IS NOT NULL BEGIN
drop table #Temp2
end
SELECT * into #Temp2
from (
SELECT
datepart(yy, t3.[datestamp]) AS full_year
,datepart(mm, t3.[datestamp]) AS month_number
,count(*) as number_of_activities
,t2.affected_item
FROM [sm70prod].[dbo].[ACTSVCMGTM1] AS t3
JOIN [sm70prod].[dbo].[INCIDENTSM1] AS t2 ON t3.number = t2.incident_id
WHERE
t2.affected_item like 'Service_name'
AND (t3.[type] LIKE 'Closed')
GROUP BY t2.affected_item, datepart(yy, t3.[datestamp]), datepart(mm, t3.[datestamp])
)
as databases (full_year, month_number, number_of_activities, affected_item)
select * from (select sum(o.number_of_activities - c.number_of_activities) over (ORDER BY c.full_year, c.month_number) as [backlog]
from #Temp1 o full join #Temp2 c on o.full_year = c.full_year and o.month_number = c.month_number) sub
--where 'time condition'
and I can put my dates/time condition in 'where' clause.
Now the issue is how to correctly add it to the code where I use CTE and few 'selects' combined with 'union all's. But this is a story for another question, I guess.
I have a MS SQL table that contains stock data with the following columns: Id, Symbol, Date, Open, High, Low, Close.
I would like to self-join the table, so I can get a day-to-day % change for Close.
I must create a query that will join the table with itself in a way that every record contains also the data from the previous session (be aware, that I cannot use yesterday's date).
My idea is to do something like this:
select * from quotes t1
inner join quotes t2
on t1.symbol = t2.symbol and
t2.date = (select max(date) from quotes where symbol = t1.symbol and date < t1.date)
However I do not know if that's the correct/fastest way. What should I take into account when thinking about performance? (E.g. will putting UNIQUE index on a (Symbol, Date) pair improve performance?)
There will be around 100,000 new records every year in this table. I am using MS SQL Server 2008
One option is to use a recursive cte (if I'm understanding your requirements correctly):
WITH RNCTE AS (
SELECT *, ROW_NUMBER() OVER (PARTITION BY symbol ORDER BY date) rn
FROM quotes
),
CTE AS (
SELECT symbol, date, rn, cast(0 as decimal(10,2)) perc, closed
FROM RNCTE
WHERE rn = 1
UNION ALL
SELECT r.symbol, r.date, r.rn, cast(c.closed/r.closed as decimal(10,2)) perc, r.closed
FROM CTE c
JOIN RNCTE r on c.symbol = r.symbol AND c.rn+1 = r.rn
)
SELECT * FROM CTE
ORDER BY symbol, date
SQL Fiddle Demo
If you need a running total for each symbol to use as the percentage change, then easy enough to add an additional column for that amount -- wasn't completely sure what your intentions were, so the above just divides the current closed amount by the previous closed amount.
Something like this w'd work in SQLite:
SELECT ..
FROM quotes t1, quotes t2
WHERE t1.symbol = t2.symbol
AND t1.date < t2.date
GROUP BY t2.ID
HAVING t2.date = MIN(t2.date)
Given SQLite is a simplest of a kind, maybe in MSSQL this will also work with minimal changes.
Index on (symbol, date)
SELECT *
FROM quotes q_curr
CROSS APPLY (
SELECT TOP(1) *
FROM quotes
WHERE symbol = q_curr.symbol
AND date < q_curr.date
ORDER BY date DESC
) q_prev
You do something like this:
with OrderedQuotes as
(
select
row_number() over(order by Symbol, Date) RowNum,
ID,
Symbol,
Date,
Open,
High,
Low,
Close
from Quotes
)
select
a.Symbol,
a.Date,
a.Open,
a.High,
a.Low,
a.Close,
a.Date PrevDate,
a.Open PrevOpen,
a.High PrevHigh,
a.Low PrevLow,
a.Close PrevClose,
b.Close-a.Close/a.Close PctChange
from OrderedQuotes a
join OrderedQuotes b on a.Symbol = b.Symbol and a.RowNum = b.RowNum + 1
If you change the last join to a left join you get a row for the first date for each symbol, not sure if you need that.
You can use option with CTE and ROW_NUMBER ranking function
;WITH cte AS
(
SELECT symbol, date, [Open], [High], [Low], [Close],
ROW_NUMBER() OVER(PARTITION BY symbol ORDER BY date) AS Id
FROM quotes
)
SELECT c1.Id, c1.symbol, c1.date, c1.[Open], c1.[High], c1.[Low], c1.[Close],
ISNULL(c2.[Close] / c1.[Close], 0) AS perc
FROM cte c1 LEFT JOIN cte c2 ON c1.symbol = c2.symbol AND c1.Id = c2.Id + 1
ORDER BY c1.symbol, c1.date
For improving performance(avoiding sorting and RID Lookup) use this index
CREATE INDEX ix_symbol$date_quotes ON quotes(symbol, date) INCLUDE([Open], [High], [Low], [Close])
Simple demo on SQLFiddle
What you had is fine. I don't know if translating the sub-query into the join will help. However, you asked for it, so the way to do it might be to join the table to itself once more.
select *
from quotes t1
inner join quotes t2
on t1.symbol = t2.symbol and t1.date > t2.date
left outer join quotes t3
on t2.symbol = t3.symbol and t2.date > t3.date
where t3.date is null
You could do something like this:
DECLARE #Today DATETIME
SELECT #Today = DATEADD(DAY, 0, DATEDIFF(DAY, 0, CURRENT_TIMESTAMP))
;WITH today AS
(
SELECT Id ,
Symbol ,
Date ,
[OPEN] ,
High ,
LOW ,
[CLOSE],
DATEADD(DAY, -1, Date) AS yesterday
FROM quotes
WHERE date = #today
)
SELECT *
FROM today
LEFT JOIN quotes yesterday ON today.Symbol = yesterday.Symbol
AND today.yesterday = yesterday.Date
That way you limit your "today" results, if that's an option.
EDIT: The CTEs listed as other questions may work well, but I tend to be hesitant to use ROW_NUMBER when dealing with 100K rows or more. If the previous day may not always be yesterday, I tend to prefer to pull out the check for the previous day in its own query then use it for reference:
DECLARE #Today DATETIME, #PreviousDay DATETIME
SELECT #Today = DATEADD(DAY, 0, DATEDIFF(DAY, 0, CURRENT_TIMESTAMP));
SELECT #PreviousDay = MAX(Date) FROM quotes WHERE Date < #Today;
WITH today AS
(
SELECT Id ,
Symbol ,
Date ,
[OPEN] ,
High ,
LOW ,
[CLOSE]
FROM quotes
WHERE date = #today
)
SELECT *
FROM today
LEFT JOIN quotes AS previousday
ON today.Symbol = previousday.Symbol
AND previousday.Date = #PreviousDay