SQL Quest › SQL Interview Questions › Window Functions
Revenue Share by Category (Window %)
For each product category, calculate its revenue share as a percentage of total revenue. Show category, category_revenue (sum of total, 2 dec), total_revenue (sum across all categories, 2 dec), and revenue_share_pct (category as % of total, 1 dec). Use a window function for total_revenue (not a subquery). Sort by revenue_share_pct DESC. Revenue share with SUM() OVER() is asked at Stripe, Square, and every fintech because it tests whether you can mix aggregate and window functions in the same query.
Solve it in the browser editor →
Runs on SQLite in your browser, graded against the expected result, no signup. A wrong answer gets a diagnosis, not just "incorrect".
Schema
orders
| order_id | customer_id | product | category | quantity | price | total | order_date | country | status |
|---|---|---|---|---|---|---|---|---|---|
| 1 | 1 | Laptop Pro | Electronics | 1 | 1299.99 | 1299.99 | 2024-01-15 | USA | completed |
| 2 | 2 | Wireless Mouse | Electronics | 2 | 49.99 | 99.98 | 2024-01-16 | Canada | completed |
| 3 | 3 | Office Chair | Furniture | 1 | 349.99 | 349.99 | 2024-01-17 | USA | completed |
Expected output: revenue_share_pct: 50.0
Hint
Concepts
SELECT Window Functions SUM ROUND GROUP BY
Practise the topic: SQL practice questions · Window function practice · GROUP BY exercises · Advanced SQL interview questions
In these company practice sets
Amazon · Apple · Meta · Plaid · Ramp · Shopify · Snowflake · Stripe · Walmart · Microsoft
A SQL Quest challenge matched to patterns reported for these companies — not a question any of them has published.
Related questions
Where would this cost you points in an interview?
Ten questions, no signup: a Skillmap across nine SQL skills and the one to fix first.
Take the readiness test