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Kotlin-based LeetCode algorithm problem solutions, regularly updated
1251\. Average Selling Price
Easy
SQL Schema
Table: `Prices`
+---------------+---------+
| Column Name | Type |
+---------------+---------+
| product_id | int |
| start_date | date |
| end_date | date |
| price | int |
+---------------+---------+
(product_id, start_date, end_date) is the primary key for this table. Each row of this table indicates the price of the product_id in the period from start_date to end_date. For each product_id there will be no two overlapping periods. That means there will be no two intersecting periods for the same product_id.
Table: `UnitsSold`
+---------------+---------+
| Column Name | Type |
+---------------+---------+
| product_id | int |
| purchase_date | date |
| units | int |
+---------------+---------+
There is no primary key for this table, it may contain duplicates. Each row of this table indicates the date, units, and product_id of each product sold.
Write an SQL query to find the average selling price for each product. `average_price` should be **rounded to 2 decimal places**.
Return the result table in **any order**.
The query result format is in the following example.
**Example 1:**
**Input:** Prices table:
+------------+------------+------------+--------+
| product_id | start_date | end_date | price |
+------------+------------+------------+--------+
| 1 | 2019-02-17 | 2019-02-28 | 5 |
| 1 | 2019-03-01 | 2019-03-22 | 20 |
| 2 | 2019-02-01 | 2019-02-20 | 15 |
| 2 | 2019-02-21 | 2019-03-31 | 30 |
+------------+------------+------------+--------+
UnitsSold table:
+------------+---------------+-------+
| product_id | purchase_date | units |
+------------+---------------+-------+
| 1 | 2019-02-25 | 100 |
| 1 | 2019-03-01 | 15 |
| 2 | 2019-02-10 | 200 |
| 2 | 2019-03-22 | 30 |
+------------+---------------+-------+
**Output:**
+------------+---------------+
| product_id | average_price |
+------------+---------------+
| 1 | 6.96 |
| 2 | 16.96 |
+------------+---------------+
**Explanation:**
Average selling price = Total Price of Product / Number of products sold.
Average selling price for product 1 = ((100 * 5) + (15 * 20)) / 115 = 6.96
Average selling price for product 2 = ((200 * 15) + (30 * 30)) / 230 = 16.96