## SQL Question You want to identify **orders coming from restaurants whose total revenue is in the bottom 25th percentile**. Assume the following tables: ### `restaurants` - `restaurant_id` (BIGINT, PK) - `name` (VARCHAR) - `market_id` (BIGINT) ### `orders` - `order_id` (BIGINT, PK) - `restaurant_id` (BIGINT, FK → restaurants.restaurant_id) - `customer_id` (BIGINT) - `order_total` (DECIMAL(10,2)) — revenue for this order (exclude tips) - `created_at` (TIMESTAMP) - `status` (VARCHAR) — e.g., 'completed', 'canceled' ## Task Write a SQL query to return orders from restaurants whose **total completed-order revenue** is in the **bottom 25%** among all restaurants over a specified analysis window. ### Requirements - Use an analysis window of the **last 30 days** relative to `CURRENT_DATE`. - Consider only `status = 'completed'` orders. - Define restaurant revenue as `SUM(order_total)` over the window. - Compute the **25th percentile** of restaurant revenue across restaurants with ≥1 completed order in the window. ### Output columns - `order_id` - `restaurant_id` - `order_total` - `created_at` - `restaurant_revenue_30d` State any assumptions (e.g., percentile function availability in your SQL dialect).