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N038-M4 Tier 3 · Intermediate · medium ecommerce · Brightlane

Return the ID, category ID, and price of every product, plus both the minimum and maximum prices across the product's category on each row

Part of Window Functions Introduction (OVER, PARTITION BY) in SQL

The problem

Brightlane's product manager wants the price range for each product's category alongside the individual product price.

Write a query to return the ID, category ID, and price of every product, plus both the minimum and maximum prices across the product's category on each row.

Assumptions:

  • The products table has one row per product with an id, a category_id, and a price.
  • A category's minimum price is the lowest price across every product in that category_id. A category's maximum price is the highest price across every product in that category_id. Both values should appear on every row that shares a category_id.

Output:

  • One row per product, with columns id, category_id, price, cat_min_price, and cat_max_price.
Schema · ecommerce 5 tables
categories
id integer
name text
parent_id? integer
products
id integer
name text
category_id integer
price numeric
stock_qty integer
attributes? jsonb
order_items
id integer
order_id integer
product_id integer
quantity integer
unit_price numeric
customers
id integer
name text
email text
city? text
country text
created_at timestamptz
is_active boolean
orders
id integer
customer_id integer
ordered_at timestamptz
status text
total_amount numeric
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Solution query
SELECT
  id,
  category_id,
  price,
  MIN(price) OVER (
    PARTITION BY
      category_id
  ) AS cat_min_price,
  MAX(price) OVER (
    PARTITION BY
      category_id
  ) AS cat_max_price
FROM
  products

The shape

Two window functions ride alongside each other, both partitioned by category_id. MIN(price) OVER (PARTITION BY category_id) writes the category's lowest price onto every row in the category, and MAX(price) OVER (PARTITION BY category_id) writes the category's highest price onto the same rows. Every product keeps its own price and gets the category's range as two additional columns.

Clause by clause

  • SELECT id, category_id, price returns each product's identifier, category, and individual price.
  • The two window columns are:
MIN(price) OVER (PARTITION BY category_id) AS cat_min_price,
MAX(price) OVER (PARTITION BY category_id) AS cat_max_price

Each OVER (PARTITION BY category_id) defines its own window: rows are grouped by category_id, the function runs independently inside each group, and the per-group result is replicated onto every row of that group. MIN and MAX see the same partitioning, so all rows in a given category share both the same cat_min_price and the same cat_max_price.

  • FROM products reads the catalog. The product manager wants the range next to each individual product, so every row stays in.

Why two windows and not one

A single window function returns one column. The brief needs both ends of the range, the minimum and the maximum, alongside each product's individual price. Two parallel windows are how a window query produces more than one per-group aggregate: each window function names its own column in the SELECT list and pulls its own value from the same partition.

You practiced two parallel OVER (PARTITION BY ...) windows — MIN and MAX partitioned by the same column produce the partition's range as two columns, side by side with the per-record value.

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