HardSQL challenge #215WINDOW FUNCTIONGROUP BYRANKING

Rank Products by Total Units Sold

Return each product with its rank by total quantity sold.

The challenge runs on the SQLabHub practice database (SQLite) and uses the order_items table. You can solve it in the browser, with nothing to install.

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The task

Rank products by total sales globally.

A correct answer returns 119 rows with 2 columns: product_id, rnk.

Tables used in this challenge

order_items 496 rows

id INTEGER (PK) · order_id INTEGER · product_id INTEGER · quantity INTEGER · unit_price REAL · subtotal REAL

First 3 rows of the order_items table
idorder_idproduct_idquantityunit_pricesubtotal
11765192.21961.05
21823107.1321.3
316515.395.39

The first rows of each table are shown. See how all the tables relate on the database schema page.

Expected output

Expected output of the challenge
product_idrnk
381
322
1193
1064
185

First 5 of 119 rows. This is the output of the model solution on the practice database. The task does not fix a sort order, so your rows may come back in a different order.

What you practise

  • Summarising many rows into one value with COUNT, SUM, AVG, MIN or MAX
  • Grouping rows with GROUP BY to get one result row per group
  • Ranking rows with RANK() or DENSE_RANK() and handling ties

Hint and approach

Try the challenge first. Open these only when you need them.

Show the hint

SUM + RANK

Show the step-by-step approach

How the model solution is built, in the order the database evaluates it:

  1. Read from the order_items table.
  2. Group the rows by product_id, so the result has one row for each value.
  3. For each group, compute SUM(quantity).
  4. Rank the rows with RANK(), ordered by SUM(quantity) descending. Tied rows share a rank and the next rank is skipped.

Model solution

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What to watch for

RANK() OVER (ORDER BY SUM(quantity) DESC) is legal because window functions are evaluated after GROUP BY. Products with the same total share a rank, and the following rank is skipped.

  • RANK() and DENSE_RANK(). RANK() skips numbers after a tie (1, 1, 3) and DENSE_RANK() does not (1, 1, 2). Filtering on rank <= N returns more than N rows when there are ties.
  • GROUP BY. Every selected column must either be in GROUP BY or sit inside an aggregate. SQLite accepts other columns and returns an arbitrary value for them; most databases raise an error.
  • Aggregate functions. Aggregates skip NULLs. AVG divides by the number of non-NULL values and COUNT(column) can be smaller than COUNT(*).
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