Is Calculate Product Final Price easy or hard?

The problem is typically considered medium difficulty because it requires understanding how joins work and how to handle missing matches correctly. The SQL itself is short, but recognizing when to use a LEFT JOIN instead of a subquery is the key concept.

Calculate Product Final Price Python/Java solution

In SQL environments like MySQL, the solution uses a LEFT JOIN and a price calculation expression. In Python with Pandas, the equivalent approach uses DataFrame.merge(..., how='left') followed by a vectorized calculation of the final price column. Java database solutions typically execute the same SQL join query through JDBC.

How to solve Calculate Product Final Price in O(n)?

Use a LEFT JOIN to combine the product table with the discount table based on the matching key. After the join, compute the final price using an arithmetic expression that substitutes missing discounts with zero using IFNULL or COALESCE. This avoids repeated lookups and processes the dataset in a single join pass.

What is the best approach for Calculate Product Final Price?

The most efficient solution uses a LEFT JOIN between the products table and the discounts table. This guarantees that every product remains in the result set even when no discount exists. The final price is calculated with an expression such as price * (1 - IFNULL(discount,0)/100). This approach runs in roughly O(n + m) time depending on indexing.

Is Calculate Product Final Price asked at Google/Amazon/Meta?

SQL join and price‑calculation problems appear frequently in interviews at companies like Amazon, Google, and data‑focused roles across tech companies. While the exact problem may vary, the core concept—joining tables and applying conditional calculations—is a common database interview pattern.

What data structure is used in Calculate Product Final Price?

The problem relies on relational database tables and SQL join operations rather than traditional in‑memory data structures. The key concept is the LEFT JOIN, which merges rows from two tables while preserving all rows from the left table.

What is the time complexity of Calculate Product Final Price?

The optimized SQL solution using a LEFT JOIN runs in O(n + m) time where n is the number of products and m is the number of discount rows. Database engines typically use indexed joins to match rows efficiently. The space complexity is O(1) because the computation happens during query execution without additional data structures.

3293. Calculate Product Final Price - Practice Online

Table: Products

+------------+---------+ 
| Column Name| Type    | 
+------------+---------+ 
| product_id | int     | 
| category   | varchar |
| price      | decimal |
+------------+---------+
product_id is the unique key for this table.
Each row includes the product's ID, its category, and its price.

Table: Discounts

+------------+---------+ 
| Column Name| Type    | 
+------------+---------+ 
| category   | varchar |
| discount   | int     |
+------------+---------+
category is the primary key for this table.
Each row contains a product category and the percentage discount applied to that category (values range from 0 to 100).

Write a solution to find the final price of each product after applying the category discount. If a product's category has no associated discount, its price remains unchanged.

Return the result table ordered by product_id in ascending order.

The result format is in the following example.

Example:

Input:

Products table:

+------------+-------------+-------+
| product_id | category    | price |
+------------+-------------+-------+
| 1          | Electronics | 1000  |
| 2          | Clothing    | 50    |
| 3          | Electronics | 1200  | 
| 4          | Home        | 500   |
+------------+-------------+-------+

Discounts table:

+------------+----------+
| category   | discount |
+------------+----------+
| Electronics| 10       |
| Clothing   | 20       |
+------------+----------+

Output:

+------------+------------+-------------+
| product_id | final_price| category    |
+------------+------------+-------------+
| 1          | 900        | Electronics |
| 2          | 40         | Clothing    |
| 3          | 1080       | Electronics |
| 4          | 500        | Home        |
+------------+------------+-------------+

Explanation:

For product 1, it belongs to the Electronics category which has a 10% discount, so the final price is 1000 - (10% of 1000) = 900.
For product 2, it belongs to the Clothing category which has a 20% discount, so the final price is 50 - (20% of 50) = 40.
For product 3, it belongs to the Electronics category and receives a 10% discount, so the final price is 1200 - (10% of 1200) = 1080.
For product 4, no discount is available for the Home category, so the final price remains 500.

Result table is ordered by product_id in ascending order.