Table: Prices
\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| product_id | int |\n| start_date | date |\n| end_date | date |\n| price | int |\n+---------------+---------+\n(product_id, start_date, end_date) is the primary key (combination of columns with unique values) for this table.\nEach row of this table indicates the price of the product_id in the period from start_date to end_date.\nFor each product_id there will be no two overlapping periods. That means there will be no two intersecting periods for the same product_id.\n\n\n
\n\n
Table: UnitsSold
\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| product_id | int |\n| purchase_date | date |\n| units | int |\n+---------------+---------+\nThis table may contain duplicate rows.\nEach row of this table indicates the date, units, and product_id of each product sold. \n\n\n
\n\n
Write a solution to find the average selling price for each product. average_price should be rounded to 2 decimal places. If a product does not have any sold units, its average selling price is assumed to be 0.
Return the result table in any order.
\n\nThe result format is in the following example.
\n\n\n
Example 1:
\n\n\nInput: \nPrices table:\n+------------+------------+------------+--------+\n| product_id | start_date | end_date | price |\n+------------+------------+------------+--------+\n| 1 | 2019-02-17 | 2019-02-28 | 5 |\n| 1 | 2019-03-01 | 2019-03-22 | 20 |\n| 2 | 2019-02-01 | 2019-02-20 | 15 |\n| 2 | 2019-02-21 | 2019-03-31 | 30 |\n+------------+------------+------------+--------+\nUnitsSold table:\n+------------+---------------+-------+\n| product_id | purchase_date | units |\n+------------+---------------+-------+\n| 1 | 2019-02-25 | 100 |\n| 1 | 2019-03-01 | 15 |\n| 2 | 2019-02-10 | 200 |\n| 2 | 2019-03-22 | 30 |\n+------------+---------------+-------+\nOutput: \n+------------+---------------+\n| product_id | average_price |\n+------------+---------------+\n| 1 | 6.96 |\n| 2 | 16.96 |\n+------------+---------------+\nExplanation: \nAverage selling price = Total Price of Product / Number of products sold.\nAverage selling price for product 1 = ((100 * 5) + (15 * 20)) / 115 = 6.96\nAverage selling price for product 2 = ((200 * 15) + (30 * 30)) / 230 = 16.96\n\n", "translatedTitle": "平均售价", "translatedContent": "
表：Prices
\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| product_id | int |\n| start_date | date |\n| end_date | date |\n| price | int |\n+---------------+---------+\n(product_id，start_date，end_date) 是\n\nprices表的主键（具有唯一值的列的组合）。\nprices表的每一行表示的是某个产品在一段时期内的价格。\n每个产品的对应时间段是不会重叠的，这也意味着同一个产品的价格时段不会出现交叉。
\n\n
表：UnitsSold
\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| product_id | int |\n| purchase_date | date |\n| units | int |\n+---------------+---------+\n该表可能包含重复数据。\n该表的每一行表示的是每种产品的出售日期，单位和产品 id。\n\n
\n\n
编写解决方案以查找每种产品的平均售价。average_price 应该 四舍五入到小数点后两位。如果产品没有任何售出，则假设其平均售价为 0。
返回结果表 无顺序要求 。
\n\n结果格式如下例所示。
\n\n\n\n
示例 1：
\n\n\n输入：\nPrices table:\n+------------+------------+------------+--------+\n| product_id | start_date | end_date | price |\n+------------+------------+------------+--------+\n| 1 | 2019-02-17 | 2019-02-28 | 5 |\n| 1 | 2019-03-01 | 2019-03-22 | 20 |\n| 2 | 2019-02-01 | 2019-02-20 | 15 |\n| 2 | 2019-02-21 | 2019-03-31 | 30 |\n+------------+------------+------------+--------+\nUnitsSold table:\n+------------+---------------+-------+\n| product_id | purchase_date | units |\n+------------+---------------+-------+\n| 1 | 2019-02-25 | 100 |\n| 1 | 2019-03-01 | 15 |\n| 2 | 2019-02-10 | 200 |\n| 2 | 2019-03-22 | 30 |\n+------------+---------------+-------+\n输出：\n+------------+---------------+\n| product_id | average_price |\n+------------+---------------+\n| 1 | 6.96 |\n| 2 | 16.96 |\n+------------+---------------+\n解释：\n平均售价 = 产品总价 / 销售的产品数量。\n产品 1 的平均售价 = ((100 * 5)+(15 * 20) )/ 115 = 6.96\n产品 2 的平均售价 = ((200 * 15)+(30 * 30) )/ 230 = 16.96\n", "isPaidOnly": false, "difficulty": "Easy", 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"{\"headers\":{\"Prices\":[\"product_id\",\"start_date\",\"end_date\",\"price\"],\"UnitsSold\":[\"product_id\",\"purchase_date\",\"units\"]},\"rows\":{\"Prices\":[[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\":[[1,\"2019-02-25\",100],[1,\"2019-03-01\",15],[2,\"2019-02-10\",200],[2,\"2019-03-22\",30]]}}", "metaData": "{\"mysql\":[\"Create table If Not Exists Prices (product_id int, start_date date, end_date date, price int)\",\"Create table If Not Exists UnitsSold (product_id int, purchase_date date, units int)\"],\"mssql\":[\"Create table Prices (product_id int, start_date date, end_date date, price int)\",\"Create table UnitsSold (product_id int, purchase_date date, units int)\"],\"oraclesql\":[\"Create table Prices (product_id int, start_date date, end_date date, price int)\",\"Create table UnitsSold (product_id int, purchase_date date, units int)\",\"ALTER SESSION SET 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