Here's a simplified example of my SALESORDERLINES table:
ORDER
LINE
ITEM
100
1
ITEMA
100
2
ITEMB
100
3
FEE
101
1
ITEMA
101
2
FEE
102
1
ITEMC
102
2
ITEMD
102
3
ITEME
103
1
ITEMA
103
2
FEE
104
1
ITEMB
104
2
ITEMC
The key values for the table are ORDER and LINE.
The last line item of each order is supposed to be item "FEE", but occasionally order entry forgets to include it. I'm trying to find every instance where they failed to include the fee on the order.
So for the example data above, I would want to return order numbers 102 and 104 only.
Any ideas?
Just a guess since you don't specify what resultset you desire. And surely there is another table that you did not include that represents "orders" - perhaps named SALESORDERS?
Assuming that, then I suggest:
select ord."ORDER" -- a terrible idea to use reserved words as names
from dbo.SALESORDERS as ord
where not exists (select * from dbo.SALESORDERLINES as ordlines
where ord."ORDER" = ordlines."ORDER" and ordlines.ITEM = 'FEE')
order by ...;
Certainly there are other ways. EXCEPT comes to mind.
Try this :
SELECT ORDER
FROM TableA
WHERE ORDER NOT IN (
SELECT ORDER
FROM TableA
WHERE ITEM = 'FEE'
GROUP BY ORDER)
GROUP BY ORDER
Related
I have two tables in a MS Access database as shown below. CustomerId is a primary key and fkCustomerId is a foreign key linked to the CustomerId in the other table.
Customer table
CustomerId
Name
1
John
2
Bob
3
David
Purchase table
fkCustomerId
OrderDate
fkStockId
1
01/02/2010
100
3
08/07/2010
101
2
14/01/2011
102
2
21/10/2011
103
3
02/03/2012
104
1
30/09/2012
105
3
01/01/2013
106
1
18/04/2014
107
3
22/11/2015
108
I am trying to return a list of customers showing the last fkStockId for each customer ordered before a given date.
So for the date 01/10/2012, I'd be looking for a return of
fkCustomerId
Name
fkStockId
1
John
105
2
Bob
103
3
David
104
A solution seems to be escaping me, any help would be greatly appreciated.
You can use nested select to get last order date.
SELECT Purchase.fkCustomerId,
Name,
fkStockId
FROM Purchase
JOIN
(
SELECT fkCustomerId,
MAX(OrderDate) as last_OrderDate
FROM Purchase
WHERE OrderDate < '01/10/2012'
GROUP BY fkCustomerId
) AS lastOrder
ON lastOrder.fkCustomerId = Purchase.fkCustomerId
AND last_OrderDate = OrderDate
LEFT JOIN Customer
ON Customer.CustomerId = Purchase.fkCustomerId
This example assumes OrderDate before '01/10/2012'. You might need to change it if you want it to be filtered by a different value.
Another assumption is that there's only one corresponding fkStockId for each OrderDate
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 a SQL Server database of orders I'm struggling with. For a normal order a single table provides the following results:
Orders:
ID Customer Shipdate Order ID
-----------------------------------------------------------------
1 Tom 2015-01-01 100
2 Bob 2014-03-20 200
At some point they needed orders that were placed by more than one customer. So they created a row for each customer and split the record over multiple rows.
Orders:
ID Customer Shipdate Order ID
-----------------------------------------------------------------
1 Tom 2015-01-01 100
2 Bob 2014-03-20 200
3 John
4 Dan
5 2014-05-10 300
So there is another table I can join on to make sense of this which relates the three rows which are actually one order.
Joint.Orders:
ID Related ID
-----------------------------------------------------------------
5 3
5 4
I'm a little new to SQL and while I can join on the other table and filter to only get the data relating to Order ID 300, but what I'd really like is to concatenate the customers, but after searching for a while I can't see how to do this. What'd I'd really like to achieve is this as an output:
ID Customer Shipdate Order ID
----------------------------------------------------------------
1 Tom 2015-01-01 100
2 Bob 2014-03-20 200
5 John, Dan 2014-05-10 300
You should consider changing the schema first. The below query might help you get a feel of how it can be done with your current design.
Select * From Orders Where IsNull(Customer, '') <> ''
Union All
Select ID,
Customer = (Select Customer + ',' From Orders OI Where OI.ID (Select RelatedID from JointOrders JO Where JO.ID = O.ID)
,ShipDate, OrderID
From Orders O Where IsNull(O.Customer, '') = ''
I have two tables ACTUAL AND ESTIMATE having unique column(sal_id, gal_id, amount, tax).
In ACTUAL table I have
actual_id, sal_id, gal_id, process_flag, amount, tax
1 111 222 N 100 1
2 110 223 N 200 2
In ESTIMATE table I have
estimate_id, sal_id, gal_id, process_flag, amount, tax
3 111 222 N 50 1
4 123 250 N 150 2
5 212 312 Y 10 1
Now I want a final table, which should have record from ACTUAL table and if no record exist for sal_id+gal_id mapping in ACTUAL but exist in ESTIMATE, then populate estimate record (along with addition of amount and tax).
In FINAL table
id sal_id, gal_id, actual_id, estimate_id, total
1 111 222 1 null 101 (since record exist in actual table for 111 222)
2 110 223 2 null 202 (since record exist in actual table for 110 223)
3 123 250 null 4 51 (since record not exist in actual table but estimate exist for 123 250)
(for 212 312 combination in estimate, since record already processed, no need to process again).
I am using Oracle 11g. Please help me on writing a logic in a single sql query?
Thanks.
There are several ways to write this query. One way is to use join and coalesce:
select coalesce(a.sal_id, e.sal_id) as sal_id,
coalesce(a.gal_id, e.gal_id) as gal_id,
coalesce(a.actual_value, e.estimate_value) as actual_value
from actual a full outer join
estimate e
on a.sal_id = e.sal_id and
a.gal_id = e.gal_id
This assumes that sal_id/gal_id provides a unique match between the tables.
Since you are using Oracle, here is perhaps a clearer way of doing it:
select sal_id, gal_id, actual_value
from (select *,
max(isactual) over (partition by sal_id, gal_id) as hasactual
from ((select 1 as isactual, *
from actual
) union all
(select 0 as isactual, *
from estimate
)
) t
) t
where isactual = 1 or hasactual = 0
This query uses a window function to determine whether there is an actual record with the matching sal_id/gal_id. The logic is to take all actuals and then all records that have no match in the actuals.
I have a table like the one below. It is a record of daily featured products and the customers that purchased them (similar to a daily deal site). A given client can only purchase a product one time per feature, but they may purchase the same product if it is featured multiple times.
FeatureID | ClientID | FeatureDate | ProductID
1 1002 2011-05-01 500
1 2333 2011-05-01 500
1 4458 2011-05-01 500
2 8888 2011-05-10 700
2 2333 2011-05-10 700
2 1111 2011-05-10 700
3 1002 2011-05-20 500
3 4444 2011-05-20 500
4 4444 2011-05-30 500
4 2333 2011-05-30 500
4 1002 2011-05-30 500
I want to count by FeatureID the number of clients that purchased FeatureID X AND who purchased the same productID during a previous feature.
For the table above the expected result would be:
FeatureID | CountofReturningClients
1 0
2 0
3 1
4 3
Ideally I would like to do this with SQL, but am also open to doing some manipulation in Excel/PowerPivot. Thanks!!
If you join your table to itself, you can find the data you're looking for. Be careful, because this query can take a long time if the table has a lot of data and is not indexed well.
SELECT t_current.FEATUREID, COUNT(DISTINCT t_prior.CLIENTID)
FROM table_name t_current
LEFT JOIN table_name t_prior
ON t_current.FEATUREDATE > t_prior.FEATUREDATE
AND t_current.CLIENTID = t_prior.CLIENTID
AND t_current.PRODUCTID = t_prior.PRODUCTID
GROUP BY t_current.FEATUREID
"Per feature, count the clients who match for any earlier Features with the same product"
SELECT
Curr.FeatureID
COUNT(DISTINCT Prev.ClientID) AS CountofReturningClients --edit thanks to feedback
FROM
MyTable Curr
LEFT JOIN
MyTable Prev WHERE Curr.FeatureID > Prev.FeatureID
AND Curr.ClientID = Prev.ClientID
AND Curr.ProductID = Prev.ProductID
GROUP BY
Curr.FeatureID
Assumptions: You have a table called Features that is:
FeatureID, FeatureDate, ProductID
If not then you could always create one on the fly with a temporary table, cte or view.
Then:
SELECT
FeatureID
, (
SELECT COUNT(DISTINCT ClientID) FROM Purchases WHERE Purchases.FeatureDate < Feature.FeatureDate AND Feature.ProductID = Purchases.ProductID
) as CountOfReturningClients
FROM Features
ORDER BY FeatureID
New to this, but wouldn't the following work?
SELECT FeatureID, (CASE WHEN COUNT(clientid) > 1 THEN COUNT(clientid) ELSE 0 END)
FROM table
GROUP BY featureID