How to count over rows and avoid duplicates? - sql

Question

For a university project I have to calculate a kpi based on the data of one table. The table stores data about baskets of a supermarket and the shopped line items and their product category. I have to calculate a number of all product categories of products which were bought in a specific store. So in tables it looks like this:
StoreId BasketID CategoryId
1 1 1
1 1 2
1 1 3
1 2 1
1 2 3
1 2 4
2 3 1
2 3 2
2 3 3
2 4 1
As a result of the query I want a table which counts the distinct product categories over all basket associated to a store.
Something like this:
StoreId Count(CategoryId)
1 4
2 3
If I do a not dynamic statement with hard values, it is working.
select basket_hash, store_id, count(DISTINCT retailer_category_id)
from promo.checkout_item
where store_id = 2
and basket_hash = 123
GROUP BY basket_hash, store_id;
But when I try to write it in a dynamic way, the sql calculates the amount per basket and adds the single amounts together.
select store_id, Count(DISTINCT retailer_category_id)
from promo.checkout_item
group by store_id;
But like this it isn't comparing the categories over all baskets associated to a store and I'm getting duplicates because a category can be in basket 1 and in basket 2.
Can somebody pls help?!
Thx!

Answer 1

As your expected result, Do you want following statement?
SELECT StoreId, COUNT(*)
FROM (
SELECT DISTINCT StoreId, CategoryId
FROM table_name
)
GROUP BY StoreId;
Please, replace "table_name" in statement by your table's name.
I'm not sure what is "dynamic way" meaning.

Answer 2

I'm confused by your requirements. This is what I suppose you mean:
with checkout_item (store_id, basket_hash, retailer_category_id) as (
values
(1,1,1),(1,1,2),(1,1,3),(1,2,1),(1,2,3),
(1,2,4),(2,3,1),(2,3,2),(2,3,3),(2,4,1)
)
select distinct store_id, basket_hash, store_cats, basket_cats
from (
select store_id, basket_hash,
max(store_cats) over (partition by store_id) as store_cats,
max(basket_cats) over (partition by basket_hash) as basket_cats
from (
select store_id, basket_hash,
dense_rank() over (
partition by store_id
order by retailer_category_id
) as store_cats,
dense_rank() over (
partition by basket_hash
order by retailer_category_id
) as basket_cats
from checkout_item
) s
) s
order by 1, 2
;
store_id | basket_hash | store_cats | basket_cats
----------+-------------+------------+-------------
1 | 1 | 4 | 3
1 | 2 | 4 | 3
2 | 3 | 3 | 3
2 | 4 | 3 | 1