I have a table that contains columns such as Price_Date, Catagory, Size, Grade, Country, and Price. The table sometimes do not contain data for Sundays or holidays (like christmas, thanksgivings, etc).
What I am trying to achieve here is when the table do not contain data for certain date, I want it to automaticaly populate data from the pervious day.
For example, the table do not contain 01/06/2019 data. It does not have the date at all. In this case, I want to automatically assign 01/06/2019 date which was missing and populate it with 01/05/2019 data.
Price_Date Catagory Size Grade Country Price
--------------------------------------------------------------------------------
2019-01-05 0 32 1 2 24.25
2019-01-05 0 36 1 2 24.25
2019-01-05 0 40 1 2 24.25
2019-01-05 0 48 1 2 24.25
2019-01-05 0 60 1 2 23.25
2019-01-05 0 70 1 2 21.25
2019-01-05 0 84 1 2 17.25
Here is the SQL query that I came up with.
And sorry if I am making this post in a wrong section.
WITH MyRowSet
AS
(
select distinct
d.date_key
,p.Size_Value
,Catagory_Value
,cast (Price_Date as datetime) as prev_effex
,ROW_NUMBER() OVER (PARTITION BY date_key,Size_Value,Catagory_Value order by date_key,cast (Price_Date as datetime) desc) AS RowNum
from
FSPPRICE P
CROSS APPLY Dim_Time d
where
d.Date_KEY <(GETDATE()) and
(D.Date_KEY > (select min(cast (Price_Date as datetime)) as min_date from FSPPRICE))
and
cast (Price_Date as datetime) <> D.Date_Key and cast (Price_Date as datetime) < D.Date_Key
group by d.date_key,Price_Date,Size_Value,Catagory_Value
)
SELECT
r.Date_KEY AS effectiveon
,P.Catagory_Value
,cast(P.Size_Value as varchar) as Size_Value
,P.Grade_Value
,P.Country
,P.Price
,P.Active_Code
FROM MyRowSet AS R INNER JOIN
FSPPRICE AS P
ON r.prev_effex = P.Price_Date and r.Catagory_Value=p.Catagory_Value and r.Size_Value=p.Size_Value WHERE (rownum < 2)
declare #dt date = GETDATE();--any given date
select #dt as price_date, category, size, grade, grade, country, price
from
#t
where price_date in (select MAX(price_date) price_date from #t where price_date <= #dt)
Related
I have pricing record with overlapping dates. On few dates there are more than one overlapping prices. Please follow the example below:
Example on 2022/02/15 there are 2 prices 10 and 8 .
article
price
startdate
enddate
123
10
2022/02/02
2049/12/31
123
8
2022/02/14
2022/09/14
123
5
2022/03/14
2022/04/06
123
4
2022/04/11
2022/04/27
I want to apply the effective price for date ranges like below and avoid conflicting prices in the output.
article
price
startdate
enddate
123
10
2022/02/02
2022/02/13
123
8
2022/02/14
2022/03/13
123
5
2022/03/14
2022/04/06
123
8
2022/04/07
2022/04/10
123
4
2022/04/11
2022/04/27
123
8
2022/04/28
2022/09/14
123
10
2022/09/15
2049/12/31
I can think of window functions to adjust the end dates and prices, but I cannot wrap my head around the problem completely to get the complete solution. Any suggestion/solution is appreciated.
Database: Snowflake
Thank you
Using the logic of new starting price window wins for overlaps.
Discreate Date version:
with data(article,price,startdate,enddate) as (
select * FROM VALUES
(123, 10, '2022-02-02'::date, '2049-12-31'::date),
(123, 8, '2022-02-14'::date, '2022-09-14'::date),
(123, 5, '2022-03-14'::date, '2022-04-06'::date),
(123, 4, '2022-04-11'::date, '2022-04-27'::date)
), dis_times as (
select article,
date as startdate,
lead(date) over(partition by article order by date)-1 as enddate
from (
select distinct article, startdate as date from data
union
select distinct article, enddate+1 as date from data
)
qualify enddate is not null
)
select
d1.article,
d1.price,
d2.startdate,
d2.enddate
from data as d1
join dis_times as d2
on d1.article = d2.article
and d2.startdate between d1.startdate and d1.enddate qualify row_number() over (partition by d1.article, s_startdate order by d1.startdate desc) = 1
order by 1,3;
gives:
ARTICLE
PRICE
S_STARTDATE
S_ENDDATE
123
10
2022-02-02
2022-02-13
123
8
2022-02-14
2022-03-13
123
5
2022-03-14
2022-04-06
123
8
2022-04-07
2022-04-10
123
4
2022-04-11
2022-04-27
123
8
2022-04-28
2022-09-14
123
10
2022-09-15
2049-12-31
Continuous Timestamp version:
with data(article,price,startdate,enddate) as (
select * FROM VALUES
(123, 10, '2022-02-02'::date, '2049-12-31'::date),
(123, 8, '2022-02-14'::date, '2022-09-14'::date),
(123, 5, '2022-03-14'::date, '2022-04-06'::date),
(123, 4, '2022-04-11'::date, '2022-04-27'::date)
), dis_times as (
select article,
date as startdate,
lead(date) over(partition by article order by date) as enddate
from (
select distinct article, startdate as date from data
union
select distinct article, enddate as date from data
)
qualify enddate is not null
)
select
d1.article,
d1.price,
d2.startdate,
d2.enddate
from data as d1
join dis_times as d2
on d1.article = d2.article
and d2.startdate >= d1.startdate and d2.startdate < d1.enddate
qualify row_number() over (partition by d1.article, s_startdate order by d1.startdate desc) = 1
order by 1,3;
which gives:
ARTICLE
PRICE
S_STARTDATE
S_ENDDATE
123
10
2022-02-02
2022-02-14
123
8
2022-02-14
2022-03-14
123
5
2022-03-14
2022-04-06
123
8
2022-04-06
2022-04-11
123
4
2022-04-11
2022-04-27
123
8
2022-04-27
2022-09-14
123
10
2022-09-14
2049-12-31
Thanks to MatBailie for the tighter join suggestion.
join dis_times as d2
on d1.article = d2.article
and d2.startdate between d1.startdate and d1.enddate
the continuous range I would normally do in this for
and d2.startdate between d1.startdate and d1.enddate and d2.startdate < d1.enddate
instead of this form
and d2.startdate >= d1.startdate and d2.startdate < d1.enddate
because I in experience it performed better. always test your complexities.
First thing I did was --I turned your price-per-date range data into a price-per-date lookup table.
create or replace temporary table price_date_lookup as
select distinct
article,
dateadd('day',b.index-1,start_date) as dates,
first_value(price) over (partition by article, dates order by end_date) as price
from my_table,
lateral split_to_table(repeat('.',datediff(day,start_date,end_date)), '.') b;
Notes:
first_value handles overlaps by overriding prices based on their end dates.
lateral... basically helps create a date column with all the days in the range
As soon as I created that table, I figured the rest could be approached like a gaps and island problem.
with cte1 as
(select *, case when lag(price) over (partition by article order by dates)=price then 0 else 1 end as price_start --flag start of a new price island
from price_date_lookup),
cte2 as
(select *, sum(price_start) over (partition by article order by dates) as price_id --assign id to all the price islands
from cte1)
select article,
price,
min(dates) as start_date,
max(dates) as end_date
from cte2
group by article,price,price_id;
I need to create a report and I am struggling with the SQL script.
The table I want to query is a company_status_history table which has entries like the following (the ones that I can't figure out)
Table company_status_history
Columns:
| id | company_id | status_id | effective_date |
Data:
| 1 | 10 | 1 | 2016-12-30 00:00:00.000 |
| 2 | 10 | 5 | 2017-02-04 00:00:00.000 |
| 3 | 11 | 5 | 2017-06-05 00:00:00.000 |
| 4 | 11 | 1 | 2018-04-30 00:00:00.000 |
I want to answer to the question "Get all companies that have been at least for some point in status 1 inside the time period 01/01/2017 - 31/12/2017"
Above are the cases that I don't know how to handle since I need to add some logic of type :
"If this row is status 1 and it's date is before the date range check the next row if it has a date inside the date range."
"If this row is status 1 and it's date is after the date range check the row before if it has a date inside the date range."
I think this can be handled as a gaps and islands problem. Consider the following input data: (same as sample data of OP plus two additional rows)
id company_id status_id effective_date
-------------------------------------------
1 10 1 2016-12-15
2 10 1 2016-12-30
3 10 5 2017-02-04
4 10 4 2017-02-08
5 11 5 2017-06-05
6 11 1 2018-04-30
You can use the following query:
SELECT t.id, t.company_id, t.status_id, t.effective_date, x.cnt
FROM company_status_history AS t
OUTER APPLY
(
SELECT COUNT(*) AS cnt
FROM company_status_history AS c
WHERE c.status_id = 1
AND c.company_id = t.company_id
AND c.effective_date < t.effective_date
) AS x
ORDER BY company_id, effective_date
to get:
id company_id status_id effective_date grp
-----------------------------------------------
1 10 1 2016-12-15 0
2 10 1 2016-12-30 1
3 10 5 2017-02-04 2
4 10 4 2017-02-08 2
5 11 5 2017-06-05 0
6 11 1 2018-04-30 0
Now you can identify status = 1 islands using:
;WITH CTE AS
(
SELECT t.id, t.company_id, t.status_id, t.effective_date, x.cnt
FROM company_status_history AS t
OUTER APPLY
(
SELECT COUNT(*) AS cnt
FROM company_status_history AS c
WHERE c.status_id = 1
AND c.company_id = t.company_id
AND c.effective_date < t.effective_date
) AS x
)
SELECT id, company_id, status_id, effective_date,
ROW_NUMBER() OVER (PARTITION BY company_id ORDER BY effective_date) -
cnt AS grp
FROM CTE
Output:
id company_id status_id effective_date grp
-----------------------------------------------
1 10 1 2016-12-15 1
2 10 1 2016-12-30 1
3 10 5 2017-02-04 1
4 10 4 2017-02-08 2
5 11 5 2017-06-05 1
6 11 1 2018-04-30 2
Calculated field grp will help us identify those islands:
;WITH CTE AS
(
SELECT t.id, t.company_id, t.status_id, t.effective_date, x.cnt
FROM company_status_history AS t
OUTER APPLY
(
SELECT COUNT(*) AS cnt
FROM company_status_history AS c
WHERE c.status_id = 1
AND c.company_id = t.company_id
AND c.effective_date < t.effective_date
) AS x
), CTE2 AS
(
SELECT id, company_id, status_id, effective_date,
ROW_NUMBER() OVER (PARTITION BY company_id ORDER BY effective_date) -
cnt AS grp
FROM CTE
)
SELECT company_id,
MIN(effective_date) AS start_date,
CASE
WHEN COUNT(*) > 1 THEN DATEADD(DAY, -1, MAX(effective_date))
ELSE MIN(effective_date)
END AS end_date
FROM CTE2
GROUP BY company_id, grp
HAVING COUNT(CASE WHEN status_id = 1 THEN 1 END) > 0
Output:
company_id start_date end_date
-----------------------------------
10 2016-12-15 2017-02-03
11 2018-04-30 2018-04-30
All you want know is those records from above that overlap with the specified interval.
Demo here with somewhat more complicated use case.
Maybe this is what you are looking for? For these kind of questions, you need to join two instance of your table, in this case I am just joining with next record by Id, which probably is not totally correct. To do it better, you can create a new Id using a windowed function like row_number, ordering the table by your requirement criteria
If this row is status 1 and it's date is before the date range check
the next row if it has a date inside the date range
declare #range_st date = '2017-01-01'
declare #range_en date = '2017-12-31'
select
case
when csh1.status_id=1 and csh1.effective_date<#range_st
then
case
when csh2.effective_date between #range_st and #range_en then true
else false
end
else NULL
end
from company_status_history csh1
left join company_status_history csh2
on csh1.id=csh2.id+1
Implementing second criteria:
"If this row is status 1 and it's date is after the date range check
the row before if it has a date inside the date range."
declare #range_st date = '2017-01-01'
declare #range_en date = '2017-12-31'
select
case
when csh1.status_id=1 and csh1.effective_date<#range_st
then
case
when csh2.effective_date between #range_st and #range_en then true
else false
end
when csh1.status_id=1 and csh1.effective_date>#range_en
then
case
when csh3.effective_date between #range_st and #range_en then true
else false
end
else null -- ¿?
end
from company_status_history csh1
left join company_status_history csh2
on csh1.id=csh2.id+1
left join company_status_history csh3
on csh1.id=csh3.id-1
I would suggest the use of a cte and the window functions ROW_NUMBER. With this you can find the desired records. An example:
DECLARE #t TABLE(
id INT
,company_id INT
,status_id INT
,effective_date DATETIME
)
INSERT INTO #t VALUES
(1, 10, 1, '2016-12-30 00:00:00.000')
,(2, 10, 5, '2017-02-04 00:00:00.000')
,(3, 11, 5, '2017-06-05 00:00:00.000')
,(4, 11, 1, '2018-04-30 00:00:00.000')
DECLARE #StartDate DATETIME = '2017-01-01';
DECLARE #EndDate DATETIME = '2017-12-31';
WITH cte AS(
SELECT *
,ROW_NUMBER() OVER (PARTITION BY company_id ORDER BY effective_date) AS rn
FROM #t
),
cteLeadLag AS(
SELECT c.*, ISNULL(c2.effective_date, c.effective_date) LagEffective, ISNULL(c3.effective_date, c.effective_date)LeadEffective
FROM cte c
LEFT JOIN cte c2 ON c2.company_id = c.company_id AND c2.rn = c.rn-1
LEFT JOIN cte c3 ON c3.company_id = c.company_id AND c3.rn = c.rn+1
)
SELECT 'Included' AS RangeStatus, *
FROM cteLeadLag
WHERE status_id = 1
AND effective_date BETWEEN #StartDate AND #EndDate
UNION ALL
SELECT 'Following' AS RangeStatus, *
FROM cteLeadLag
WHERE status_id = 1
AND effective_date > #EndDate
AND LagEffective BETWEEN #StartDate AND #EndDate
UNION ALL
SELECT 'Trailing' AS RangeStatus, *
FROM cteLeadLag
WHERE status_id = 1
AND effective_date < #EndDate
AND LeadEffective BETWEEN #StartDate AND #EndDate
I first select all records with their leading and lagging Dates and then I perform your checks on the inclusion in the desired timespan.
Try with this, self-explanatory. Responds to this part of your question:
I want to answer to the question "Get all companies that have been at
least for some point in status 1 inside the time period 01/01/2017 -
31/12/2017"
Case that you want to find those id's that have been in any moment in status 1 and have records in the period requested:
SELECT *
FROM company_status_history
WHERE id IN
( SELECT Id
FROM company_status_history
WHERE status_id=1 )
AND effective_date BETWEEN '2017-01-01' AND '2017-12-31'
Case that you want to find id's in status 1 and inside the period:
SELECT *
FROM company_status_history
WHERE status_id=1
AND effective_date BETWEEN '2017-01-01' AND '2017-12-31'
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 been scratching my head with this one for an hour still cannot seem to figure out a way to allocate Payment amount of $30 to the rows in the following table.
Given that i have the following items. Negative amount means the customer is in debt and owes us that amount. Now given that customer pays $30. We need to allocate that to the item.
ItemId amount sDATE
BD98E890-C7F8-47F4-9125-A68A88DD178D -10 2016-01-04 00:00:00.000
7E047DE6-0DB7-4EDB-A751-C43BBD4610E5 -20 2016-01-05 00:00:00.000
5004AE1F-2A15-47E5-96FF-69A6C7D35521 -10 2016-01-06 00:00:00.000
for a payment of $30 the output should look like.
itemId BeforeAllocation AfterAllocation LeftToAllocate sDate
BD98E890-C7F8-47F4-9125-A68A88DD178D -10 0 30 2016-01-04 00:00:00.000
7E047DE6-0DB7-4EDB-A751-C43BBD4610E5 -20 0 20 2016-01-05 00:00:00.000
5004AE1F-2A15-47E5-96FF-69A6C7D35521 -10 -10 0 2016-01-06 00:00:00.000
and if customer is paying partial amount for exmaple $25 the output should be.
itemId BeforeAllocation AfterAllocation LeftToAllocate sDate
BD98E890-C7F8-47F4-9125-A68A88DD178D -10 0 25 2016-01-04 00:00:00.000
7E047DE6-0DB7-4EDB-A751-C43BBD4610E5 -20 -5 15 2016-01-05 00:00:00.000
5004AE1F-2A15-47E5-96FF-69A6C7D35521 -10 -10 0 2016-01-06 00:00:00.000
Code:
Create table #temp(ItemId UNIQUEIDENTIFIER , amount INT, sDATE DATETIME)
INSERT INTO #temp
( ItemId,
amount,
sDATE )
VALUES ( NEWID(),-10,'2016-01-04' ),
( NEWID(),-20,'2016-01-05' ),
( NEWID(),-10,'2016-01-06' )
SELECT * FROM (
SELECT 'BD98E890-C7F8-47F4-9125-A68A88DD178D' itemId, -10 BeforeAllocation, 0 AfterAllocation, 30 LeftToAllocate, '2016-01-04 00:00:00.000' sDate
UNION
SELECT '7E047DE6-0DB7-4EDB-A751-C43BBD4610E5' itemId, -20 BeforeAllocation, 0 AfterAllocation, 20 LeftToAllocate, '2016-01-05 00:00:00.000' sDate
UNION
SELECT '5004AE1F-2A15-47E5-96FF-69A6C7D35521' itemId, -10 BeforeAllocation, -10 AfterAllocation,0 LeftToAllocate, '2016-01-06 00:00:00.000' sDate
)s
ORDER BY sdate
SELECT * FROM (
SELECT 'BD98E890-C7F8-47F4-9125-A68A88DD178D' itemId, -10 BeforeAllocation, 0 AfterAllocation, 25 LeftToAllocate, '2016-01-04 00:00:00.000' sDate
UNION
SELECT '7E047DE6-0DB7-4EDB-A751-C43BBD4610E5' itemId, -20 BeforeAllocation, -5 AfterAllocation, 15 LeftToAllocate, '2016-01-05 00:00:00.000' sDate
UNION
SELECT '5004AE1F-2A15-47E5-96FF-69A6C7D35521' itemId, -10 BeforeAllocation, -10 AfterAllocation,0 LeftToAllocate, '2016-01-06 00:00:00.000' sDate
)s
ORDER BY sdate
Calculate an expression BeforeAllocationRT, to record the running total of BeforeAllocation (i.e. the sum of BeforeAllocation for this row and all preceding rows). If you're using SQL Server 2012 or later you can use window functions, otherwise you need a clumsy subexpression - see this question for exact instructions.
Calculate an expression for the amount to allocate
SELECT Allocation = CASE
WHEN BeforeAllocationRT + #Payment > 0
-- pay full amount for this item
THEN -#BeforeAllocation
WHEN BeforeAllocationRT + #Payment > #BeforeAllocation
-- pay partial amount for this item
THEN -(#BeforeAllocationRT+#Payment)
ELSE
-- pay nothing for this item
0
END
, ...
Calculate expressions for AfterAllocation and LeftToAllocate.
SELECT
AfterAllocation = BeforeAllocation + Allocation
,LeftToAllocate = CASE WHEN BeforeAllocationRT+#Payment>0 THEN #Payment-BeforeAllocationRT ELSE 0 END
,...
Combine steps 1,2,3 using CTEs or subexpressions.
Disclaimer: I don't have access to a SQL Server instance right now, so none of this is tested.
try this,
DECLARE #PaidAmout INT = 30
;WITH CTE AS
(
SELECT ItemId, amount, sDATE, ROW_NUMBER() OVER(ORDER BY sDATE) AS RowNo
FROM #temp
),
Amount AS
(
SELECT ItemId,
RowNo,
amount AS BeforeAllocation,
0 AS AfterAllocation,
#PaidAmout AS LeftToAllocate,
sDATE,
#PaidAmout + Amount AS LeftAmount
FROM CTE
WHERE RowNo = 1
UNION ALL
SELECT c.ItemId,
c.RowNo,
c.amount AS BeforeAllocation,
CASE WHEN a.LeftAmount + c.Amount < 0 THEN a.LeftAmount + c.Amount ELSE 0 END AS AfterAllocation,
CASE WHEN a.LeftAmount < 0 THEN 0 ELSE a.LeftAmount END AS LeftToAllocate,
c.sDATE,
a.LeftAmount + c.Amount AS LeftAmount
FROM CTE c
INNER JOIN Amount a ON a.RowNo + 1 = c.RowNo
)
SELECT ItemId,
BeforeAllocation,
AfterAllocation,
LeftToAllocate,
sDATE
FROM Amount
I want to be able to "book" within range of dates, but you can't book across gaps of days. So booking across multiple rates is fine as long as they are contiguous.
I am happy to change data structure/index, if there are better ways of storing start/end ranges.
So far I have a "rates" table which contains Start/End Periods of time with a daily rate.
e.g. Rates Table.
ID Price From To
1 75.00 2015-04-12 2016-04-15
2 100.00 2016-04-16 2016-04-17
3 50.00 2016-04-18 2016-04-30
For the above data I would want to return:
From To
2015-04-12 2016-4-30
For simplicity sake it is safe to assume that dates are safely consecutive. For contiguous dates To is always 1 day before from.
For the case there is only 1 row, I would want it to return the From/To of that single row.
Also to clarify if I had the following data:
ID Price From To
1 75.00 2015-04-12 2016-04-15
2 100.00 2016-04-17 2016-04-18
3 50.00 2016-04-19 2016-04-30
4 50.00 2016-05-01 2016-05-21
Meaning where there is a gap >= 1 day it would count as a separate range.
In which case I would expect the following:
From To
2015-04-12 2016-04-15
2015-04-17 2016-05-21
Edit 1
After playing around I have come up with the following SQL which seems to work. Although I'm not sure if there are better ways/issues with it?
WITH grouped_rates AS
(SELECT
from_date,
to_date,
SUM(grp_start) OVER (ORDER BY from_date, to_date) group
FROM (SELECT
gite_id,
from_date,
to_date,
CASE WHEN (from_date - INTERVAL '1 DAY') = lag(to_date)
OVER (ORDER BY from_date, to_date)
THEN 0
ELSE 1
END grp_start
FROM rates
GROUP BY from_date, to_date) AS start_groups)
SELECT
min(from_date) from_date,
max(to_date) to_date
FROM grouped_rates
GROUP BY grp;
This is identifying contiguous overlapping groups in the data. One approach is to find where each group begins and then do a cumulative sum. The following query adds a flag indicating if a row starts a group:
select r.*,
(case when not exists (select 1
from rates r2
where r2.from < r.from and r2.to >= r.to or
(r2.from = r.from and r2.id < r.id)
)
then 1 else 0 end) as StartFlag
from rate r;
The or in the correlation condition is to handle the situation where intervals that define a group overlap on the start date for the interval.
You can then do a cumulative sum on this flag and aggregate by that sum:
with r as (
select r.*,
(case when not exists (select 1
from rates r2
where (r2.from < r.from and r2.to >= r.to) or
(r2.from = r.from and r2.id < r.id)
)
then 1 else 0 end) as StartFlag
from rate r
)
select min(from), max(to)
from (select r.*,
sum(r.StartFlag) over (order by r.from) as grp
from r
) r
group by grp;
CREATE TABLE prices( id INTEGER NOT NULL PRIMARY KEY
, price MONEY
, date_from DATE NOT NULL
, date_upto DATE NOT NULL
);
-- some data (upper limit is EXCLUSIVE)
INSERT INTO prices(id, price, date_from, date_upto) VALUES
( 1, 75.00, '2015-04-12', '2016-04-16' )
,( 2, 100.00, '2016-04-17', '2016-04-19' )
,( 3, 50.00, '2016-04-19', '2016-05-01' )
,( 4, 50.00, '2016-05-01', '2016-05-22' )
;
-- SELECT * FROM prices;
-- Recursive query to "connect the dots"
WITH RECURSIVE rrr AS (
SELECT date_from, date_upto
, 1 AS nperiod
FROM prices p0
WHERE NOT EXISTS (SELECT * FROM prices nx WHERE nx.date_upto = p0.date_from) -- no preceding segment
UNION ALL
SELECT r.date_from, p1.date_upto
, 1+r.nperiod AS nperiod
FROM prices p1
JOIN rrr r ON p1.date_from = r.date_upto
)
SELECT * FROM rrr r
WHERE NOT EXISTS (SELECT * FROM prices nx WHERE nx.date_from = r.date_upto) -- no following segment
;
Result:
date_from | date_upto | nperiod
------------+------------+---------
2015-04-12 | 2016-04-16 | 1
2016-04-17 | 2016-05-22 | 3
(2 rows)