I have a control table, where Prices with Item number are tracked date wise.
id ItemNo Price Date
---------------------------
1 a001 100 1/1/2003
2 a001 105 1/2/2003
3 a001 110 1/3/2003
4 b100 50 1/1/2003
5 b100 55 1/2/2003
6 b100 60 1/3/2003
7 c501 35 1/1/2003
8 c501 38 1/2/2003
9 c501 42 1/3/2003
10 a001 95 1/1/2004
This is the query I am running.
SELECT pr.*
FROM prices pr
INNER JOIN
(
SELECT ItemNo, max(date) max_date
FROM prices
GROUP BY ItemNo
) p ON pr.ItemNo = p.ItemNo AND
pr.date = p.max_date
order by ItemNo ASC
I am getting below values
id ItemNo Price Date
------------------------------
10 a001 95 2004-01-01
6 b100 60 2003-01-03
9 c501 42 2003-01-03
Question is, is my query right or wrong? though I am getting my desired result.
Your query does what you want, and is a valid approach to solve your problem.
An alternative option would be to use a correlated subquery for filtering:
select p.*
from prices p
where p.date = (select max(p1.date) from prices where p1.itemno = p.itemno)
The upside of this query is that it can take advantage of an index on (itemno, date).
You can also use window functions:
select *
from (
select p.*, rank() over(partition by itemno order by date desc) rn
from prices p
) p
where rn = 1
I would recommend benchmarking the three options against your real data to assess which one performs better.
Related
I have a simple Order table and one order can have different products with Quantity and it's Product's weight as below
OrderID
ProductName
Qty
Weight
101
ProductA
2
24
101
ProductB
1
24
101
ProductC
1
48
101
ProductD
1
12
101
ProductE
1
12
102
ProductA
5
60
102
ProductB
1
12
I am trying to partition and group the products in such a way that for an order, grouped products weight should not exceed 48.
Expected table look as below
OrderID
ProductName
Qty
Weight
GroupedID
101
ProductA
2
24
1
101
ProductB
1
24
1
101
ProductC
1
48
2
101
ProductD
1
12
3
101
ProductE
1
12
3
102
ProductA
4
48
1
102
ProductA
1
12
2
102
ProductB
1
12
2
Kindly let me know if this is possible.
Thank you.
This is a bin packing problem which is non-trivial in general. It's not just NP-complete but superexponential, ie the time increase as complexity increases is worse than exponential. Dai posted a link to Hugo Kornelis's article series which is referenced by everyone trying to solve this problem. The set-based solution performs really bad. For realistic scenarios you need iteration and preferably, using bin packing libraries eg in Python.
For production work it would be better to take advantage of SQL Server 2017+'s support for Python scripts and use a bin packing library like Google's OR Tools or the binpacking module. Even if you don't want to use sp_execute_external_script you can use a Python script to read the data from the database and split them.
The question's numbers are so regular though you could cheat a bit (actually quite a lot) and distribute all order lines into individual items, calculate the running total per order and then divide the total by the limit to produce the group number.
This works only because the running totals are guaranteed to align with the bin size.
Distributing into items can be done using a Tally/Numbers table, a table with a single Number column storing numbers from 0 to eg 1M.
Given the question's data:
declare #OrderItems table(id int identity(1,1) primary key, OrderID int,ProductName varchar(20),Qty int,Weight int)
insert into #OrderItems(OrderId,ProductName,Qty,Weight)
values
(101,'ProductA',2,24),
(101,'ProductB',1,24),
(101,'ProductC',1,48),
(101,'ProductD',1,12),
(101,'ProductE',1,12),
(102,'ProductA',5,60),
(102,'ProductB',1,12);
The following query will split each order item into individual items. It repeats each order item row as there are individual items and calculates the individual item weight
select o.*, Weight/Qty as ItemWeight
from #OrderItems o inner join Numbers ON Qty >Numbers.Number;
This row:
1 101 ProductA 2 24
Becomes
1 101 ProductA 2 24 12
1 101 ProductA 2 24 12
Calculating the running total inside a query can be done with :
SUM(ItemWeight) OVER(Partition By OrderId
Order By Itemweight
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)
The Order By Itemweight claus means the smallest items are picked first, ie it's a Worst fit algorithm.
The overall query calculating the total and Group ID is
with items as (
select o.*, Weight/Qty as ItemWeight
from #OrderItems o INNER JOIN Numbers ON Qty > Numbers.Number
)
select Id,OrderId,ProductName,Qty,Weight, ItemWeight,
ceiling(SUM(ItemWeight) OVER(Partition By OrderId
Order By Itemweight
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)/48.0)
As GroupId
from items;
After that, individual items need to be grouped back into order items and groups. This produces the final query:
with items as (
select o.*, Weight/Qty as ItemWeight
from #OrderItems o INNER JOIN Numbers ON Qty > Numbers.Number
)
,bins as(
select Id,OrderId,ProductName,Qty,Weight, ItemWeight,
ceiling(SUM(ItemWeight) OVER(Partition By OrderId
Order By Itemweight
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)/48.0) As GroupId
from items
)
select
max(OrderId) as orderid,
max(productname) as ProductName,
count(*) as Qty,
sum(ItemWeight) as Weight,
max(GroupId) as GroupId
from bins
group by id,groupid
order by orderid,groupid
This returns
orderid
ProductName
Qty
Weight
GroupId
101
ProductA
2
24
1
101
ProductD
1
12
1
101
ProductE
1
12
1
101
ProductB
1
24
2
101
ProductC
1
48
3
102
ProductA
4
48
1
102
ProductA
1
12
2
102
ProductB
1
12
2
I have been searching the forum and found a single post that is a little smilair to my problem here: Calculate average for Top n combined with SQL Group By.
My situation is:
I have a table tblWEIGHT that contains: ID, Date, idPONR, Weight
I have a second table tblSALES that contains: ID, Date, Sales, idPONR
I have a third table tblPONR that contains: ID, PONR, idProduct
And a fouth table tblPRODUCT that contais: ID, Product
The linking:
tblWEIGHT.idPONR = tblPONR.ID
tblSALES.idPONR = tblPONR.ID
tblPONR.idProduct = tblPRODUCT.ID
The maintable of my query is tblSALES. I want to all my sales listed, with the moving average of the top5
weights of the PRODUCT where the date of the weight is less than the sales date, and the product is the same as the sold product. Its IMPORTANT that the result isn't grouped by the date. I need all the records of tblSALES.
i have gotten as far as to get the top 1 weight, but im not able to get the moving average instread.
The query that gest the top 1 is the following, and i am guessing that the query i need is going to look a lot like it.
SELECT tblSALES.ID, tblSALES.Dato, tblPONR.idPRODUCT,
(
SELECT top 1 Weight FROM tblWEIGHT INNER JOIN tblPONR ON tblWeight.idPONR = tblPONR.ID
WHERE tblPONR.idPRODUCT = idPRODUCT AND
SALES.Date > tblWEIGHT.Date
ORDER BY tblWEIGHT.Date desc
) AS LatestWeight
FROM tblSALES INNER JOIN VtblPONR ON tblSALES.idPONR = tblPONR.ID
this is not my exact query since im danish and i wouldnt make sense. I know im not supposed to use Date as a fieldname.
i imagine the filan query would be something like:
SELECT tblSALES.ID..... avg(SELECT TOP 5 weight .........)
but doing this i keep getting error at max 1 record can be returned by this subquery
Final Question.
How do i make a query that creates a moving average of the top 5 weights of my sold product, where the date of the weight is earlier than the date i sold the product?
EDIT Sampledata:
DATEFORMAT: dd/mm/yyyy
tblWEIGHT
ID Date idPONR Weight
1 01-01-2020 1 100
2 02-01-2020 2 200
3 03-01-2020 3 200
4 04-01-2020 3 400
5 05-01-2020 2 250
6 06-01-2020 1 150
7 07-01-2020 2 200
tblSALES
ID Date Sales(amt) idPONR
1 05-01-2020 30 1
2 06-01-2020 15 2
3 10-01-2020 20 3
tblPONR
ID PONR(production Number) idProduct
1 2521 1
2 1548 1
3 5484 2
tblPRODUCT
ID Product
1 Bricks
2 Tiles
Desired outcome read comments for AvgWeight
tblSALES.ID tblSALES.Date tblSales.Sales(amt) AvgWeigt
1 05-01-2020 30 123 -->avg(top 5 newest weight of both idPONR 1 And 2 because they are the same product, and where tblWeight.Date<05-01-2020)
2 06-01-2020 15 123 -->avg(top 5 newest weight of both idPONR 1 And 2 because they are the same product, and where tblWeight.Date<06-01-2020)
3 10-01-2020 20 123 -->avg(top 5 newest weight of idPONR 3 since thats the only idPONR with that product, and where tblWeight.Date<10-01-2020)
Consider:
Query1
SELECT tblWeight.ID AS WeightID, tblWeight.Date AS WtDate,
tblWeight.idPONR, tblPONR.PONR, tblPONR.idProduct, tblWeight.Weight, tblSales.SalesAmt,
tblSales.ID AS SalesID, tblSales.Date AS SalesDate
FROM (tblPONR INNER JOIN tblWeight ON tblPONR.ID = tblWeight.idPONR)
INNER JOIN tblSales ON tblPONR.ID = tblSales.idPONR;
Query2
SELECT * FROM Query1 WHERE WeightID IN (
SELECT TOP 5 WeightID FROM Query1 AS Dupe WHERE Dupe.idProduct = Query1.idProduct
AND Dupe.WtDate<Query1.SalesDate ORDER BY Dupe.WtDate);
Query3
SELECT Query2.SalesID, Query2.SalesDate, Query2.SalesAmt,
First(DAvg("Weight","Query2","idProduct=" & [idProduct] & " AND WtDate<#" & [SalesDate] & "#")) AS AvgWt
FROM Query2
GROUP BY Query2.SalesID, Query2.SalesDate, Query2.SalesAmt;
Assume that i have the following table
CREATE TABLE #tblUsersPokemons (
RecordId int NOT NULL,
PokemonId int NOT NULL,
PokemonExp int NOT NULL,
PokemonLevel int NOT NULL,
UserId int NOT NULL
)
Now the below query works awesome as expected
select
SUM(cast(PokemonExp as bigint)) as TotalExp,
MAX(PokemonLevel) as MaxPokeLevel,
Count(PokemonId) as TotalPoke,
UserId
from #tblUsersPokemons
group by UserId
Here example result of such query
ToplamExp MaxPokeLevel TotalPoke UserId
----------- --------------- ----------- --------
29372294 101 4 1
1134696 98 1 2
1400 98 1 101
24534365 98 4 102
1400 98 1 1102
1400 98 1 1103
1400 98 1 2102
1400 98 1 2103
789220 98 7 2105
1468 98 1 3104
Now here my question comes
I want to limit counted PokemonIds. What i mean is i want to select maximum 6 of each same PokemonId records. And from these records top 6 ordered desc by PokemonExp should be counted in.
For example a user has the below records
From this table the query should take record id : 1,2,3,4,5,6,9 and not take 7,8 since top 6 records for PokemonId 1 taken
If I understand correctly, you want the aggregations on the top 6 rows for each user. You can do this easily using row_number():
select SUM(cast(PokemonExp as bigint)) as ToplamExp,
MAX(PokemonLevel) as MaxPokeLevel,
Count(PokemonId) as TotalPoke,UserId
from (select p.*,
row_number() over (partition by userid order by pokemanexp desc) as seqnum
from tblUsersPokemons p
) p
where seqnum <= 6
group by UserId;
EDIT:
I think you want to include PokemonId in the partition by clause:
select SUM(cast(PokemonExp as bigint)) as ToplamExp,
MAX(PokemonLevel) as MaxPokeLevel,
Count(PokemonId) as TotalPoke,UserId
from (select p.*,
row_number() over (partition by userid, PokemonId
order by pokemanexp desc) as seqnum
from tblUsersPokemons p
) p
where seqnum <= 6
group by UserId;
There is a table tbl_products that contains data as shown below:
Id Name
----------
1 P1
2 P2
3 P3
4 P4
5 P5
6 P6
And another table tbl_inputs that contains data as shown below:
Id Product_Id Price Register_Date
----------------------------------------
1 1 10 2010-01-01
2 1 20 2010-10-11
3 1 30 2011-01-01
4 2 100 2010-01-01
5 2 200 2009-01-01
6 3 500 2011-01-01
7 3 270 2010-10-15
8 4 80 2010-01-01
9 4 50 2010-02-02
10 4 92 2011-01-01
I want to select all products(id, name, price, register_date) with maximum date in each group.
For Example:
Id Name Price Register_Date
----------------------------------------
3 P1 30 2011-01-01
4 P2 100 2010-01-01
6 P3 500 2011-01-01
10 P4 92 2011-01-01
select
id
,name
,code
,price
from tbl_products tp
cross apply (
select top 1 price
from tbl_inputs ti
where ti.product_id = tp.id
order by register_date desc
) tii
Although is not the optimum way you can do it like:
;with gb as (
select
distinct
product_id
,max(register_date) As max_register_date
from tbl_inputs
group by product_id
)
select
id
,product_id
,price
,register_date
from tbl_inputs ti
join gb
on ti.product_id=gb.product_id
and ti.register_date = gb.max_register_date
But as I said earlier .. this is not the way to go in this case.
;with cte as
(
select t1.id, t1.name, t1.code, t2.price, t2.register_date,
row_number() over (partition by product_id order by register_date desc) rn
from tbl_products t1
join tbl_inputs t2
on t1.id = t2.product_id
)
select id, name, code, price, register_date
from cte
where rn = 1
Something like this..
select id, product_id, price, max(register_date)
from tbl_inputs
group by id, product_id, price
you can use the max function and the group by clause. if you only need results from the table tbl_inputs you even don't need a join
select product_id, max(register_date), price
from tbl_inputs
group by product_id, price
if you need field from the tbl_prducts you have to use a join.
select p.name, p. code, i.id, i.price, max(i.register_date)
from tbl_products p join tbl_inputs i on p.id=i.product_id
grooup by p.name, p. code, i.id, i.price
Try this:
SELECT id, product_id, price, register_date
FROM tbl_inputs T1 INNER JOIN
(
SELECT product_id, MAX(register_date) As Max_register_date
FROM tbl_inputs
GROUP BY product_id
) T2 ON(T1.product_id= T2.product_id AND T1.register_date= T2.Max_register_date)
This is, of course, assuming your dates are unique. if they are not, you need to add the DISTINCT Keyword to the outer SELECT statement.
edit
Sorry, I didn't explain it very well. Your dates can be duplicated, it's not a problem as long as they are unique per product id. if you can have duplicated dates per product id, then you will have more then one row per product in the outcome of the select statement I suggested, and you will have to find a way to reduce it to one row per product.
i.e:
If you have records like that (when the last date for a product appears more then once in your table with different prices)
id | product_Id | price | register_date
--------------------------------------------
1 | 1 | 10.00 | 01/01/2000
2 | 1 | 20.00 | 01/01/2000
it will result in having both of these records as outcome.
However, if the register_date is unique per product id, then you will get only one result for each product id.
I'm trying to write a query that gets the value of one field that's associated with the maximum value of another field (or fields). Let's say I have the following table of data:
OrderID CustomerID OrderDate LocationID
1 4 1/1/2001 1001
2 4 1/2/2001 1003
3 4 1/3/2001 1001
4 5 1/4/2001 1001
5 5 1/5/2001 1001
6 5 1/6/2001 1003
7 5 1/7/2001 1002
8 5 1/8/2001 1003
9 5 1/8/2001 1002
Grouping by CustomerID, I want to get the maximum OrderDate and then the LocationID associated with whatever is the maximum OrderDate. If there are several records that share the maximum order date, then take the LocationID associated with the maximum OrderID from among those records with the maximum date.
The final set of data should look like this:
CustomerID OrderDate LocationID
4 1/3/2001 1001
5 1/8/2001 1002
I had been trying to write a query with lots of nested subqueries and ugly joins, but I'm not really getting anywhere. What SQL do I need to write to help me get this result.
with cte As
(
select *,
row_number() over (partition by CustomerID
order by OrderDate desc, OrderId desc) as rn
from yourtable
)
select CustomerID, OrderDate,LocationID
from cte
where rn=1;
SELECT
C.Name,
C.CustomerID,
X.*
FROM
Customers C
CROSS APPLY (
SELECT TOP 1 OrderDate, LocationID
FROM Orders O
WHERE C.CustomerID = O.CustomerID
ORDER BY OrderDate Desc, OrderID Desc
) X
If you will pull any columns from the Customers table, this will probably outperform other methods.
If not, then the Row_Number answer, pulling only from Orders, will probably be best. But if you restrict by Customer in any way, then the CROSS APPLY will again be best. Possibly by a big margin.
The trick is to use a subquery as a value, not as a join:
select customerId,orderDate,locationId
from orders o1
where orderDate = (
select top 1 orderdate
from orders o2
where o1.customerId = o2.customerId
order by orderdate desc
)