Report the customer ids from the Customer table that bought all the products in the Product table.
This challenge now meets the current minimum standard for sitemap inclusion and independent indexing.
Report the customer ids from the Customer table that bought all the products in the Product table.
This is a compact example of relational division: finding entities that are related to every value in another set. The same idea appears in entitlement checks, feature adoption queries, and completeness reporting where a user must satisfy all required items.
customer_idproduct_keyproduct_keySELECT
customer_id
FROM customer
GROUP BY customer_id
HAVING COUNT(DISTINCT product_key) = (
SELECT COUNT(*)
FROM product
)The product table defines the full required set. If a customer has purchased the same number of distinct product keys as the catalog contains, then that customer has bought every product. This is the cleanest and most portable version for this schema.
SELECT DISTINCT c.customer_id
FROM customer c
WHERE NOT EXISTS (
SELECT 1
FROM product p
WHERE NOT EXISTS (
SELECT 1
FROM customer c2
WHERE c2.customer_id = c.customer_id
AND c2.product_key = p.product_key
)
)The NOT EXISTS version expresses the logic more literally: there must not exist any product that the current customer failed to buy. It is more verbose than the counting approach, but it generalizes well when duplicates or extra conditions make direct counts less obvious.
Do not use COUNT(product_key) without DISTINCT if duplicate purchases are possible. A customer who bought the same product multiple times could then appear to cover the entire catalog even when they are missing another product.
The product table is the authoritative definition of the full set. Hard-coding the required count makes the query brittle when the catalog changes.
NOT EXISTS is useful when the matching rules become more complex than a simple distinct count, or when you want the logic to read as an explicit all-items check instead of a counting shortcut.
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