Is Sales Analysis I easy or hard?

Sales Analysis I is classified as Easy. The problem mainly tests familiarity with SQL aggregation using GROUP BY and filtering results with MAX or ranking functions rather than complex database logic.

Sales Analysis I Python/Java solution

Sales Analysis I is a SQL database problem rather than an algorithm implemented in Python or Java. The expected solution uses SQL queries—typically MySQL—combining GROUP BY, SUM(price), and a MAX aggregation or window function.

How to solve Sales Analysis I in O(n)?

Use SQL aggregation to compute SUM(price) for each seller with GROUP BY seller_id. Then compare those totals with the maximum total sales using a subquery or a window function such as RANK(). Since the table is scanned once for aggregation, the overall complexity remains O(n).

What is the best approach for Sales Analysis I?

The most common solution aggregates total sales per seller using GROUP BY and SUM(price), then filters sellers whose totals equal the maximum total using a subquery. This runs in O(n) time with O(k) space where k is the number of sellers. It relies on standard SQL features and is the approach most interviewers expect.

Is Sales Analysis I asked at Google/Amazon/Meta?

This exact problem appears on LeetCode as a database practice question. Variations of aggregation queries—finding maximum totals, top sellers, or ranking groups—are common in SQL interview rounds at companies like Amazon and Meta, especially for data or backend roles.

What data structure is used in Sales Analysis I?

The solution relies on relational database operations rather than traditional data structures. SQL engines internally use hash aggregation or sorting during GROUP BY operations to compute totals per seller efficiently.

What is the time complexity of Sales Analysis I?

The query processes the Sales table once to compute aggregated totals per seller, giving O(n) time complexity where n is the number of sales records. Storing grouped totals requires O(k) space for k distinct sellers.

1082. Sales Analysis I - Practice Online

Table: Product

+--------------+---------+
| Column Name  | Type    |
+--------------+---------+
| product_id   | int     |
| product_name | varchar |
| unit_price   | int     |
+--------------+---------+
product_id is the primary key (column with unique values) of this table.
Each row of this table indicates the name and the price of each product.

Table: Sales

+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| seller_id   | int     |
| product_id  | int     |
| buyer_id    | int     |
| sale_date   | date    |
| quantity    | int     |
| price       | int     |
+-------------+---------+
This table can have repeated rows.
product_id is a foreign key (reference column) to the Product table.
Each row of this table contains some information about one sale.

Write a solution that reports the best seller by total sales price, If there is a tie, report them all.

Return the result table in any order.

The result format is in the following example.

Example 1:

Input: 
Product table:
+------------+--------------+------------+
| product_id | product_name | unit_price |
+------------+--------------+------------+
| 1          | S8           | 1000       |
| 2          | G4           | 800        |
| 3          | iPhone       | 1400       |
+------------+--------------+------------+
Sales table:
+-----------+------------+----------+------------+----------+-------+
| seller_id | product_id | buyer_id | sale_date  | quantity | price |
+-----------+------------+----------+------------+----------+-------+
| 1         | 1          | 1        | 2019-01-21 | 2        | 2000  |
| 1         | 2          | 2        | 2019-02-17 | 1        | 800   |
| 2         | 2          | 3        | 2019-06-02 | 1        | 800   |
| 3         | 3          | 4        | 2019-05-13 | 2        | 2800  |
+-----------+------------+----------+------------+----------+-------+
Output: 
+-------------+
| seller_id   |
+-------------+
| 1           |
| 3           |
+-------------+
Explanation: Both sellers with id 1 and 3 sold products with the most total price of 2800.