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Interview Core Track · Easy · 15 min

Sales Analysis III

Table: Product +--------------+---------+ | Column Name | Type | +--------------+---------+ | product_id | int | | product_name | varchar | | unit_price | in...

Interview Core Track
Easy
15 min
joins
aggregation
filtering

Company labels are directional practice context, not official interview guidance.

Timer 00:00
Back to practice

Objective

Practice joins through a IshaSQL-tagged business scenario.

Approach

Use this track to improve speed, edge-case handling, and accuracy under timed conditions.

Company context

Company labels are directional practice context, not official interview guidance.

Prereq: query basics
Prereq: filtering

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 duplicate 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 to report the products that were only sold in the first quarter of 2019 . That is, between 2019-01-01 and 2019-03-31 inclusive. 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: +-------------+--------------+ | product_id | product_name | +-------------+--------------+ | 1 | S8 | +-------------+--------------+ Explanation: The product with id 1 was only sold in the spring of 2019. The product with id 2 was sold in the spring of 2019 but was also sold after the spring of 2019. The product with id 3 was sold after spring 2019. We return only product 1 as it is the product that was only sold in the spring of 2019.

Product
product_id INT PRIMARY KEY
product_name VARCHAR(100
Sales
seller_id INT
product_id INT
buyer_id INT
sale_date DATE
quantity INT
price INT
FOREIGN KEY (product_id
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