I have two tables: [transaction_table] (t) and [rate_table] (r)
I want to FROM [transaction_table] LEFT JOIN [rate_table] according to the t.transaction_date and r.effective_date and the product.
Anyone know how? Thanks in advance.
Here's my code:
but it returns undesired outcome
SELECT t.*, r.rate
FROM [transaction_table] t
LEFT JOIN [rate_table] r on (t.product = r.product and t.transaction_date >= r.effective_date)
Desired Outcome: Transaction Table LEFT JOIN Rate Table, with rate according to the effective_date
transaction_date
product
amt
rate
2020-01-01
A
200
0.2
2020-04-01
A
200
0.3
2020-04-01
B
100
0.1
2021-01-01
A
200
0.5
[Transaction_Table]: contains all transactions of different products
transaction_date
product
amt
2020-01-01
A
200
2020-04-01
A
200
2020-04-01
B
100
2021-01-01
A
200
[Rate_Table]: contains rate adjustement of different products with an "effective_date"
effective_date
product
rate
2019-01-01
A
0.2
2019-01-01
B
0.1
2020-04-01
A
0.3
2020-09-01
A
0.5
You are joining all rates before the transaction date while you only want to get the newest of these. You can achieve this with a TOP(1) query in an OUTER APPLY
select t.*, r.rate
from transaction_table t
outer apply
(
select top(1) *
from rate_table r
where r.product = t.product
and r.effective_date <= t.transaction_date
order by r.effective_date desc
);
or in a subquery in the SELECT clause:
select
t.*,
(
select top(1) r.rate
from rate_table r
where r.product = t.product
and r.effective_date <= t.transaction_date
order by r.effective_date desc
) as rate
from transaction_table t;
You can use the APPLY operator to get the latest rate by product and based on latest effective_date
SELECT t.*, r.rate
FROM [transaction_table] t
CROSS APPLY
(
SELECT TOP (1) r.rate
FROM [rate_table] r
WHERE t.product = r.product
AND t.transaction_date >= r.effective_date
ORDER BY r.effective_date DESC
) r
You may also want to use OUTER APPLY instead of CROSS APPLY if there are possibility of a non matching rate in the rate_table
You can either use a derived table in which you define an end date for the rate by getting the next effective date using LEAD(), i.e.
SELECT tt.transaction_date,
tt.product,
tt.amt,
rt.rate
FROM Transaction_Table AS tt
LEFT JOIN
( SELECT rt.effective_date,
rt.product,
rt.rate,
end_date = LEAD(rt.effective_date)
OVER(PARTITION BY rt.product ORDER BY rt.effective_date)
FROM rate_table AS rt
) AS rt
ON rt.product = tt.product
AND rt.effective_date <= tt.transaction_date
AND (rt.end_date > tt.transaction_date OR rt.end_date IS NULL);
Or you can use OUTER APPLY with TOP 1 and then order by effective_date to get the latest rate prior to the transaction date:
SELECT tt.transaction_date,
tt.product,
tt.amt,
rt.rate
FROM Transaction_Table AS tt
OUTER APPLY
( SELECT TOP (1) rt.rate
FROM rate_table AS rt
WHERE rt.product = tt.product
AND rt.effective_date <= tt.transaction_date
ORDER BY rt.effective_date DESC
) AS rt;
I would typically approach this using the first method as it is more likely that your rate table is significantly smaller than transaction table, but depending on your overall data and indexes you may find OUTER APPLY performs better.
If you are dealing with very high volumes of data and performance is an issue then materialising your rate table will probably help, e.g.
IF OBJECT_ID(N'tempdb..#rate', 'U') IS NOT NULL
DROP TABLE #rate;
CREATE TABLE #rate
(
Product CHAR(1) NOT NULL, --Change type as necessary
FromDate DATE NOT NULL,
ToDate DATE NULL,
Rate DECIMAL(10, 2) NOT NULL, -- Change type as necessary
PRIMARY KEY (Product, FromDate)
);
INSERT #rate(Product, FromDate, ToDate, Rate)
SELECT rt.product,
rt.effective_date,
end_date = LEAD(rt.effective_date)
OVER(PARTITION BY rt.product ORDER BY rt.effective_date),
rt.rate
FROM rate_table AS rt;
SELECT tt.transaction_date,
tt.product,
tt.amt,
rt.rate
FROM Transaction_Table AS tt
LEFT JOIN #rate AS rt
ON rt.product = tt.product
AND rt.FromDate <= tt.transaction_date
AND (rt.ToDate > tt.transaction_date OR rt.ToDate IS NULL);
Related
I have 3 tables in oracle sql namely investor, share and transaction.
I am trying to get new investors invested in any shares for a certain period. As they are the new investor, there should not be a transaction in the transaction table for that investor against that share prior to the search period.
For the transaction table with the following records:
Id TranDt InvCode ShareCode
1 2020-01-01 00:00:00.000 inv1 S1
2 2019-04-01 00:00:00.000 inv1 S1
3 2020-04-01 00:00:00.000 inv1 S1
4 2021-03-06 11:50:20.560 inv2 S2
5 2020-04-01 00:00:00.000 inv3 S1
For the search period between 2020-01-01 and 2020-05-01, I should get the output as
5 2020-04-01 00:00:00.000 inv3 S1
Though there are transactions for inv1 in the table for that period, there is also a transaction prior to the search period, so that shouldn't be included as it's not considered as new investor within the search period.
Below query is working but it's really taking ages to return the results calling from c# code leading to timeout issues. Is there anything we can do to refine to get the results quicker?
WITH
INVESTORS AS
(
SELECT I.INVCODE FROM INVESTOR I WHERE I.CLOSED IS NULL)
),
SHARES AS
(
SELECT S.SHARECODE FROM SHARE S WHERE S.DORMANT IS NULL))
),
SHARES_IN_PERIOD AS
(
SELECT DISTINCT
T.INVCODE,
T.SHARECODE,
T.TYPE
FROM TRANSACTION T
JOIN INVESTORS I ON T.INVCODE = I.INVCODE
JOIN SHARES S ON T.SHARECODE = S.SHARECODE
WHERE T.TRANDT >= :startDate AND T.TRANDT <= :endDate
),
PREVIOUS_SHARES AS
(
SELECT DISTINCT
T.INVCODE,
T.SHARECODE,
T.TYPE
FROM TRANSACTION T
JOIN INVESTORS I ON T.INVCODE = I.INVCODE
JOIN SHARES S ON T.TRSTCODE = S.TRSTCODE
WHERE T.TRANDT < :startDate
)
SELECT
DISTINCT
SP.INVCODE AS InvestorCode,
SP.SHARECODE AS ShareCode,
SP.TYPE AS ShareType
FROM SHARES_IN_PERIOD SP
WHERE (SP.INVCODE, SP.SHARECODE, SP.TYPE) NOT IN
(
SELECT
PS.INVCODE,
PS.SHARECODE,
PS.TYPE
FROM PREVIOUS_SHARES PS
)
With the suggestion given by #Gordon Linoff, I tried following options (for all the shares I need) but they are taking long time too. Transaction table is over 32 million rows.
1.
WITH
SHARES AS
(
SELECT S.SHARECODE FROM SHARE S WHERE S.DORMANT IS NULL))
)
select t.invcode, t.sharecode, t.type
from (select t.*,
row_number() over (partition by invcode, sharecode, type order by trandt)
as seqnum
from transactions t
) t
join shares s on s.sharecode = t.sharecode
where seqnum = 1 and
t.trandt >= date '2020-01-01' and
t.trandt < date '2020-05-01';
WITH
INVESTORS AS
(
SELECT I.INVCODE FROM INVESTOR I WHERE I.CLOSED IS NULL)
),
SHARES AS
(
SELECT S.SHARECODE FROM SHARE S WHERE S.DORMANT IS NULL))
)
select t.invcode, t.sharecode, t.type
from (select t.*,
row_number() over (partition by invcode, sharecode, type order by trandt)
as seqnum
from transactions t
) t
join investors i on i.invcode = t.invcode
join shares s on s.sharecode = t.sharecode
where seqnum = 1 and
t.trandt >= date '2020-01-01' and
t.trandt < date '2020-05-01';
select t.invcode, t.sharecode, t.type
from (select t.*,
row_number() over (partition by invcode, sharecode, type order by trandt)
as seqnum
from transactions t
) t
where seqnum = 1 and
t.sharecode IN (SELECT S.SHARECODE FROM SHARE S WHERE S.DORMANT IS NULL)))
and
t.trandt >= date '2020-01-01' and
t.trandt < date '2020-05-01';
If you want to know if the first record in transactions for a share is during a period, you can use window functions:
select t.*
from (select t.*,
row_number() over (partition by invcode, sharecode order by trandt) as seqnum
from transactions t
) t
where seqnum = 1 and
t.sharecode = :sharecode and
t.trandt >= date '2020-01-01' and
t.trandt < date '2020-05-01';
For performance for this code, you want an index on transactions(invcode, sharecode, trandate).
Hello I am trying to calculate the time difference of 2 consecutive rows for Date (either in hours or Days), as attached in the image
Highlighted in Yellow is the result I want which is basically the difference of the date in that row and 1 above.
How can we achieve it in the SQL? Attached is my complex code which has the rest of the fields in it
with cte
as
(
select m.voucher_no, CONVERT(VARCHAR(30),CONVERT(datetime, f.action_Date, 109),100) as action_date,f.col1_Value,f.col3_value,f.col4_value,f.comments,f.distr_user,f.wf_status,f.action_code,f.wf_user_id
from attdetailmap m
LEFT JOIN awftaskfin f ON f.oid = m.oid and f.client ='PC'
where f.action_Date !='' and action_date between '$?datef' and '$?datet'
),
.*select *, ROW_NUMBER() OVER(PARTITION BY action_Date,distr_user,wf_Status,wf_user_id order by action_Date,distr_user,wf_Status,wf_user_id ) as row_no_1 from cte
cte2 as
(
select *, ROW_NUMBER() OVER(PARTITION BY voucher_no,action_Date,distr_user,wf_Status,wf_user_id order by voucher_no ) as row_no_1 from cte
)
select distinct(v.dim_value) as resid,c.voucher_no,CONVERT(datetime, c.action_Date, 109) as action_Date,c.col4_value,c.comments,c.distr_user,v.description,c.wf_status,c.action_code, c.wf_user_id,v1.description as name,r.rel_value as pay_office,r1.rel_value as site
from cte2 c
LEFT OUTER JOIN aagviuserdetail v ON v.user_id = c.distr_user
LEFT OUTER JOIN aagviuserdetail v1 ON v1.user_id = c.wf_user_id
LEFT OUTER JOIN ahsrelvalue r ON r.resource_id = v.dim_Value and r.rel_Attr_id = 'P1' and r.period_to = '209912'
LEFT OUTER JOIN ahsrelvalue r1 ON r1.resource_id = v.dim_Value and r1.rel_Attr_id = 'Z1' and r1.period_to = '209912'
where c.row_no_1 = '1' and r.rel_value like '$?site1' and voucher_no like '$?trans'
order by voucher_no,action_Date
The key idea is lag(). However, date/time functions vary among databases. So, the idea is:
select t.*,
(date - lag(date) over (partition by transaction_no order by date)) as diff
from t;
I should note that this exact syntax might not work in your database -- because - may not even be defined on date/time values. However, lag() is a standard function and should be available.
For instance, in SQL Server, this would look like:
select t.*,
datediff(second, lag(date) over (partition by transaction_no order by date), date) / (24.0 * 60 * 60) as diff_days
from t;
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;
I'm trying to find the average qty on hand of my inventory over a date range from parameter #StartDate by averaging the ending qty from each day. I have three tables: a part table, a part transaction table, and a warehouse table, mocked up below.
PartNum | PartNum TranDate TranQty | PartNum OnHandQty
---------- | ------------------------------------ | --------------------
P1 | P1 6/28/2016 5 | P1 30
P2 | P1 6/26/2016 3 | P2 2
| P1 6/26/2016 -1 |
| P1 6/15/2016 2 |
| P2 6/15/2016 1 |
If today is 6/30/2016 and #StartDate = 6/1/2016, I expect a result like:
PartNum AverageOnHand
------------------------
P1 22.9
P2 1.5
However, I don't know what function would best allow me to get to an appropriate weighted sum which I could divide by the difference in dates. Is there a SumProduct function or similar that I can use here? My code, so far, is below:
select
[Part].[PartNum] as [Part_PartNum],
(max(PartWhse.OnHandQty)*datediff(day,max(PartTran.TranDate),Constants.Today)) as [Calculated_WeightedSum],
(WeightedSum/DATEDIFF(day, #StartDate, Constants.Today)) as [Calculated_AverageOnHand]
from Erp.Part as Part
right outer join Erp.PartTran as PartTran on
Part.PartNum = PartTran.PartNum
inner join Erp.PartWhse as PartWhse on
Part.PartNum = PartWhse.PartNum
group by [Part].[PartNum]
Here is a sql-server 2012 + method that is interesting.
;WITH cte AS (
SELECT
p.PartNum
,CAST(t.TranDate AS DATE) AS TranDate
,i.OnHandQty
--,SUM(SUM(t.TranQty)) OVER (PARTITION BY p.PartNum ORDER BY CAST(t.TranDate AS DATE) DESC) AS InventoryChange
,i.OnHandQty - SUM(SUM(t.TranQty)) OVER (PARTITION BY p.PartNum ORDER BY CAST(t.TranDate AS DATE) DESC) AS InventoryOnDate
,DATEDIFF(day,
CAST(ISNULL(LAG(MAX(TranDate)) OVER (PARTITION BY p.PartNum ORDER BY CAST(t.TranDate AS DATE) ASC),#StartDate) AS DATE)
,CAST(t.TranDate AS DATE)
) AS DaysAtInventory
FROM
#Parts p
LEFT JOIN #Transact t
ON p.PartNum = t.PartNum
LEFT JOIN #Inventory i
ON p.PartNum = i.PartNum
GROUP BY
p.PartNum
,CAST(t.TranDate AS DATE)
,i.OnHandQty
)
SELECT
PartNum
,(SUM(ISNULL(DaysAtInventory,0) * ISNULL(InventoryOnDate,0))
+ ((DATEDIFF(day,MAX(TranDate),CAST(GETDATE() AS DATE)) + 1) * ISNULL(MAX(OnHandQty),0)))
/((DATEDIFF(day,CAST(#StartDate AS DATE),CAST(GETDATE() AS DATE)) + 1) * 1.00) AS AvgDailyInventory
FROM
cte
GROUP BY
PartNum
This one actually gave me the 22.9 but 1.53333 the 333 gets introduced because 1 day has to get put somewhere so I stuck it as the current inventory.
Here is a previous method I answered with and this one it is a little easier to conceptualize the data..... I would be curious about performance differences between the 2 methods.
Some of these steps can be combined to be a little more concise but this works (although I got 22.6 not .1 or .9....) I rounded everything to a whole date while doing this so that you don't have to worry about beginning and end of day.
DECLARE #StartDate DATETIME = '6/1/2016'
;WITH cteDates AS (
SELECT #StartDate AS d
UNION ALL
SELECT
d + 1 AS d
FROM
cteDates c
WHERE c.d + 1 <= CAST(CAST(GETDATE() AS DATE) AS DATETIME)
--get dates to today beginning of day
)
, ctePartsDaysCross AS (
SELECT
d.d
,p.PartNum
,ISNULL(i.OnHandQty,0) AS OnHandQty
FROM
cteDates d
CROSS JOIN #Parts p
LEFT JOIN #Inventory i
ON p.PartNum = i.PartNum
)
, cteTransactsQuantityByDate AS (
SELECT
CAST(t.TranDate AS DATE) as d
,t.PartNum
,TranQty = SUM(t.TranQty)
FROM
#Transact t
GROUP BY
CAST(t.TranDate AS DATE)
,t.PartNum
)
,cteDailyInventory AS (
SELECT
c.d
,c.PartNum
,c.OnHandQty - SUM(ISNULL(t.TranQty,0)) OVER (PARTITION BY c.PartNum ORDER BY c.d DESC) AS DailyOnHand
FROM
ctePartsDaysCross c
LEFT JOIN cteTransactsQuantityByDate t
ON c.d = t.d
AND c.PartNum = t.PartNum
)
SELECT
PartNum
,AVG(CAST(DailyOnHand AS DECIMAL(6,3)))
FROM
cteDailyInventory
GROUP BY
PartNum
Here is the test data:
IF OBJECT_ID('tempdb..#Parts') IS NOT NULL
BEGIN
DROP TABLE #Parts
END
IF OBJECT_ID('tempdb..#Transact') IS NOT NULL
BEGIN
DROP TABLE #Transact
END
IF OBJECT_ID('tempdb..#Inventory') IS NOT NULL
BEGIN
DROP TABLE #Inventory
END
CREATE TABLE #Parts (
PartNum CHAR(2)
)
CREATE TABLE #Transact (
AutoId INT IDENTITY(1,1) NOT NULL
,PartNum CHAR(2)
,TranDate DATETIME
,TranQty INT
)
CREATE TABLE #Inventory (
PartNum CHAR(2)
,OnHandQty INT
)
INSERT INTO #Parts (PartNum) VALUES ('P1'),('P2'),('P3')
INSERT INTO #Transact (PartNum, TranDate, TranQty)
VALUES ('P1','6/28/2016',5),('P1','6/26/2016',3),('P1','6/26/2016',-1)
,('P1','6/15/2016',2) ,('P2','6/15/2016',1)
INSERT INTO #Inventory (PartNum, OnHandQty) VALUES ('P1',30),('P2',2)
I am thinking 1 recursive cte might be simpler might post that as an update.
Reverse the transactions to compute daily quantities. Add in the missing dates and look backward to the most recent date to fill in the daily quantities. I think I'm going to try for a better solution than this one.
http://rextester.com/JLD19862
with trn as (
select PartNum, TranDate, TranQty from PartTran
union all
select PartNum, cast('20160601' as date), 0 from PartWhse
union all
select PartNum, cast('20160630' as date), 0 from PartWhse
), qty as (
select
t.PartNum, t.TranDate,
-- assumes that end date corresponds with OnHandQty
min(w.OnHandQty) + sum(t.TranQty)
- sum(sum(t.TranQty))
over (partition by t.PartNum order by t.TranDate desc) as DailyOnHand,
coalesce(
lead(t.TranDate) over (partition by t.PartNum order by t.TranDate),
dateadd(day, 1, t.TranDate)
) as NextTranDate
-- if lead() isn't available...
-- coalesce(
-- (
-- select min(t2.TranDate) from trn as t2
-- where t2.PartNum = t.PartNum and t2.TranDate > t.TranDate
-- ),
-- dateadd(day, 1, t.TranDate)
-- ) as NextTranDate
from PartWhse as w inner join trn as t on t.PartNum = w.PartNum
where t.TranDate between '20160601' and '20160630'
group by t.PartNum, t.TranDate
)
select
PartNum,
sum(datediff(day, TranDate, NextTranDate) * DailyOnHand) * 1.00
/ sum(datediff(day, TranDate, NextTranDate)) as DailyAvg
from qty
group by PartNum;
I was able to solve this with a sum. First, I multiplied the final quantity on hand by the number of days in the range. Next, I multiplied each change in inventory by the time from #StartDate until the TransDate.
select
[Part].[PartNum] as [Part_PartNum],
(max(PartWhse.OnHandQty)*datediff(day,#StartDate,Constants.Today)-
sum(PartTran.TranQty*datediff(day,#StartDate,PartTran.TranDate))) as [Calculated_WeightedSum],
(WeightedSum/DATEDIFF(day, #StartDate, Constants.Today)) as [Calculated_AverageOnHand]
from Erp.Part as Part
right outer join Erp.PartTran as PartTran on
Part.PartNum = PartTran.PartNum
inner join Erp.PartWhse as PartWhse on
Part.PartNum = PartWhse.PartNum
group by [Part].[PartNum]
Thanks for your help everyone! You really helped me think it through.
I have a table with 3 colums. Here is an example with just a few entries to demo. The table represents the dates that an item's price changes. I need a query that will tell me the prices for all the items on a specific date. The specific date may be between price changes. The price changes at midnight, so the date of the change, that is the price from then until and on the day before the previous change:
itemCode datePriceEffective price
AB 2012-01-01 9.99
AB 2012-03-02 10.50
XY 2011-09-20 34.99
I wish to get all the items prices for a given date. There is not an entry for every date, just the dates that the price changes.
so 2012-03-05 would return
AB 10.50
XY 34.99
and 2012-02-27 would return:
AB 9.99
XY 34.99
The SQL query needed to get this escapes me. Answers appreciated.
Edited as answers are going in wrong direction see italics for edit.
This retrieves first record by descending order of datePriceEffective per itemCode.
select top 1 with ties *
from ATable
where datePriceEffective <= #givenDate
order by row_number() over (partition by itemCode
order by datePriceEffective desc)
SELECT itemCode,price FRom TableNameHere WHERE datePriceEffective <= '2012-03-05'
Edit after more info - a 'simple' answer to hopefully make it easy to follow.
You're getting thelatest date for the item that is valid in your required date range and then joining the table to itself to get the price at that date
SELECT t1.itemCode,t1.price FROM
(
SELECT itemCode,MAX(datePriceEffective) AS datePriceEffective
FROM TableNameHere
WHERE datePriceEffective <= '2012-03-05'
) a
INNER JOIN TableNameHere t1 ON t1.itemCode = a.itemCode AND t1.datePriceEffective = a.datePriceEffective
You will need to join back to the table as follows:
declare #effdate datetime
set #effdate = CONVERT(datetime,'2012-02-27')
;WITH CTE_DATA as (
select itemCode='AB', datePriceEffective = CONVERT(Datetime,'2012-01-01'), price = 9.99
union all select itemCode='AB', datePriceEffective = CONVERT(Datetime,'2012-03-02'), price = 10.50
union all select itemCode='XY', datePriceEffective = CONVERT(Datetime,'2011-09-20'), price = 34.99
)
select
d.itemcode,
price
from
CTE_DATA d
join (
select
itemcode,
effdate = MAX(datepriceeffective)
from CTE_DATA sub where sub.datepriceeffective <= #effdate
group by itemcode
) x
on x.itemCode = d.itemCode
and x.effdate = d.datePriceEffective
Note that the CTE is just for this example, you should swap it for your real table.
UPDATE: An alternative approach is to use ROW_NUMBER and PARTITION as follows:
SELECT
itemcode,
price
FROM
(
SELECT
itemcode,
price,
rowno = ROW_NUMBER() over (partition by itemcode order by datePriceEffective desc)
from
CTE_DATA
where datePriceEffective <= #effdate
) x
where
rowno = 1
(Substitute this select for the one in the previous query to try it out on the data)
declare #date datetime = '2012-03-05'
select distinct itemcode,
(
select top(1) itemprice
from mytable mt2
where
mt1.itemcode = mt2.itemcode and
mt2.datepriceeffective <= #date
order by datepriceeffective desc
) as itemprice
from
mytable mt1
where
datepriceeffective <= #date
SELECT b.itemCode,
(SELECT Price FROM dbo.tblProducts a WHERE datePriceEffective =
(SELECT MAX(a.datePriceEffective) FROM dbo.tblProducts a WHERE a.itemCode = b.itemCode)) AS Price
FROM dbo.tblProducts b
WHERE b.datePriceEffective <= '2012-03-05'
GROUP BY b.itemCode
I have tested it! It will give you the most updated price for each Item
Assuming that you have another column called 'GivenDate', below is the query.
SELECT itemCode, price
FROM tblName
WHERE GivenDate= '2012-03-05'
This works on sql2000
SELECT s.itemCode
, ( SELECT TOP 1 price
FROM #MyTable
WHERE itemCode = s.itemCode
AND datePriceEffective < #SearchDate ) AS price
FROM (
SELECT DISTINCT itemCode
FROM #MyTable
) s