Optimal solution for interview question - sql

Question

Recently in a job interview, I was given the following problem.
Say I have the following table
widget_Name | widget_Costs | In_Stock
---------------------------------------------------------
a | 15.00 | 1
b | 30.00 | 1
c | 20.00 | 1
d | 25.00 | 1
where widget_name is holds the name of the widget, widget_costs is the price of a widget, and in stock is a constant of 1.
Now for my business insurance I have a certain deductible. I am looking to find a sql statement that will tell me every widget and it's price exceeds the deductible. So if my dedudctible is $50.00 the above would just return
widget_Name | widget_Costs | In_Stock
---------------------------------------------------------
a | 15.00 | 1
d | 25.00 | 1
Since widgets b and c where used to meet the deductible
The closest I could get is the following
SELECT
*
FROM (
SELECT
widget_name,
widget_price
FROM interview.tbl_widgets
minus
SELECT widget_name,widget_price
FROM (
SELECT
widget_name,
widget_price,
50 - sum(widget_price) over (ORDER BY widget_price ROWS between unbounded preceding and current row) as running_total
FROM interview.tbl_widgets
)
where running_total >= 0
)
;
Which gives me
widget_Name | widget_Costs | In_Stock
---------------------------------------------------------
c | 20.00 | 1
d | 25.00 | 1
because it uses a and b to meet the majority of the deductible
I was hoping someone might be able to show me the correct answer
EDIT: I understood the interview question to be asking this. Given a table of widgets and their prices and given a dollar amount, substract as many of the widgets you can up to the dollar amount and return those widgets and their prices that remain

Answer 1

I'll put an answer up, just in case it's easier than it looks, but if the idea is just to return any widget that costs more than the deductible then you'd do something like this:
Select
Widget_Name, Widget_Cost, In_Stock
From
Widgets
Where
Widget_Cost > 50 -- SubSelect for variable deductibles?
For your sample data my query returns no rows.

Answer 2

I believe I understand your question, but I'm not 100%. Here is what I'm assuming you mean:
Your deductible is say, $50. To meet the deductible you have you "use" two items. (Is this always two? How high can it go? Can it be just one? What if they don't total exactly $50, there is a lot of missing information). You then want to return the widgets that aren't being used towards deductible. I have the following.
CREATE TABLE #test
(
widget_name char(1),
widget_cost money
)
INSERT INTO #test (widget_name, widget_cost)
SELECT 'a', 15.00 UNION ALL
SELECT 'b', 30.00 UNION ALL
SELECT 'c', 20.00 UNION ALL
SELECT 'd', 25.00
SELECT * FROM #test t1
WHERE t1.widget_name NOT IN (
SELECT t1.widget_name FROM #test t1
CROSS JOIN #test t2
WHERE t1.widget_cost + t2.widget_cost = 50 AND t1.widget_name != t2.widget_name)
Which returns
widget_name widget_cost
----------- ---------------------
a 15.00
d 25.00

Answer 3

This looks like a Bin Packing problem these are really hard to solve especially with SQL.
If you search on SO for Bin Packing + SQL, you'll find how to find Sum(field) in condition ie “select * from table where sum(field) < 150” Which is basically the same problem except you want to add a NOT IN to it.
I couldn't get the accepted answer by brianegge to work but what he wrote about it in general was interesting
..the problem you
describe of wanting the selection of
users which would most closely fit
into a given size, is a bin packing
problem. This is an NP-Hard problem,
and won't be easily solved with ANSI
SQL. However, the above seems to
return the right result, but in fact
it simply starts with the smallest
item, and continues to add items until
the bin is full.
A general, more effective bin packing
algorithm would is to start with the
largest item and continue to add
smaller ones as they fit. This
algorithm would select users 5 and 4.
So with this advice you could write a cursor to loop over the table to do just this (it just wouldn't be pretty).
Aaron Alton gives a nice link to a series of articles that attempts to solve the Bin Packing problem with sql but basically concludes that its probably best to use a cursor to do it.