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96 lines
13 KiB
JSON
96 lines
13 KiB
JSON
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"questionId": "1174",
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"questionFrontendId": "1084",
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"categoryTitle": "Database",
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"boundTopicId": 11003,
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"title": "Sales Analysis III",
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"titleSlug": "sales-analysis-iii",
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"content": "<p>Table: <code>Product</code></p>\n\n<pre>\n+--------------+---------+\n| Column Name | Type |\n+--------------+---------+\n| product_id | int |\n| product_name | varchar |\n| unit_price | int |\n+--------------+---------+\nproduct_id is the primary key (column with unique values) of this table.\nEach row of this table indicates the name and the price of each product.\n</pre>\n\n<p>Table: <code>Sales</code></p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type |\n+-------------+---------+\n| seller_id | int |\n| product_id | int |\n| buyer_id | int |\n| sale_date | date |\n| quantity | int |\n| price | int |\n+-------------+---------+\nThis table can have duplicate rows.\nproduct_id is a foreign key (reference column) to the Product table.\nEach row of this table contains some information about one sale.\n</pre>\n\n<p> </p>\n\n<p>Write a solution to report the <strong>products</strong> that were <strong>only</strong> sold in the first quarter of <code>2019</code>. That is, between <code>2019-01-01</code> and <code>2019-03-31</code> inclusive.</p>\n\n<p>Return the result table in <strong>any order</strong>.</p>\n\n<p>The result format is in the following example.</p>\n\n<p> </p>\n<p><strong class=\"example\">Example 1:</strong></p>\n\n<pre>\n<strong>Input:</strong> \nProduct table:\n+------------+--------------+------------+\n| product_id | product_name | unit_price |\n+------------+--------------+------------+\n| 1 | S8 | 1000 |\n| 2 | G4 | 800 |\n| 3 | iPhone | 1400 |\n+------------+--------------+------------+\nSales table:\n+-----------+------------+----------+------------+----------+-------+\n| seller_id | product_id | buyer_id | sale_date | quantity | price |\n+-----------+------------+----------+------------+----------+-------+\n| 1 | 1 | 1 | 2019-01-21 | 2 | 2000 |\n| 1 | 2 | 2 | 2019-02-17 | 1 | 800 |\n| 2 | 2 | 3 | 2019-06-02 | 1 | 800 |\n| 3 | 3 | 4 | 2019-05-13 | 2 | 2800 |\n+-----------+------------+----------+------------+----------+-------+\n<strong>Output:</strong> \n+-------------+--------------+\n| product_id | product_name |\n+-------------+--------------+\n| 1 | S8 |\n+-------------+--------------+\n<strong>Explanation:</strong> \nThe product with id 1 was only sold in the spring of 2019.\nThe product with id 2 was sold in the spring of 2019 but was also sold after the spring of 2019.\nThe product with id 3 was sold after spring 2019.\nWe return only product 1 as it is the product that was only sold in the spring of 2019.\n</pre>\n",
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"translatedTitle": "销售分析III",
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"translatedContent": "<p>表： <code>Product</code></p>\n\n<pre>\n+--------------+---------+\n| Column Name | Type |\n+--------------+---------+\n| product_id | int |\n| product_name | varchar |\n| unit_price | int |\n+--------------+---------+\nproduct_id 是该表的主键（具有唯一值的列）。\n该表的每一行显示每个产品的名称和价格。\n</pre>\n\n<p>表：<code>Sales</code></p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type |\n+-------------+---------+\n| seller_id | int |\n| product_id | int |\n| buyer_id | int |\n| sale_date | date |\n| quantity | int |\n| price | int |\n+------ ------+---------+\n这个表可能有重复的行。\nproduct_id 是 Product 表的外键（reference 列）。\n该表的每一行包含关于一个销售的一些信息。\n</pre>\n\n<p> </p>\n\n<p>编写解决方案，报告<code>2019年春季</code>才售出的产品。即<strong>仅</strong>在<code><strong>2019-01-01</strong></code>至<code><strong>2019-03-31</strong></code>（含）之间出售的商品。</p>\n\n<p>以 <strong>任意顺序</strong> 返回结果表。</p>\n\n<p>结果格式如下所示。</p>\n\n<p> </p>\n\n<p><strong>示例 1:</strong></p>\n\n<pre>\n<strong>输入：</strong>\nProduct table:\n+------------+--------------+------------+\n| product_id | product_name | unit_price |\n+------------+--------------+------------+\n| 1 | S8 | 1000 |\n| 2 | G4 | 800 |\n| 3 | iPhone | 1400 |\n+------------+--------------+------------+\n<code>Sales </code>table:\n+-----------+------------+----------+------------+----------+-------+\n| seller_id | product_id | buyer_id | sale_date | quantity | price |\n+-----------+------------+----------+------------+----------+-------+\n| 1 | 1 | 1 | 2019-01-21 | 2 | 2000 |\n| 1 | 2 | 2 | 2019-02-17 | 1 | 800 |\n| 2 | 2 | 3 | 2019-06-02 | 1 | 800 |\n| 3 | 3 | 4 | 2019-05-13 | 2 | 2800 |\n+-----------+------------+----------+------------+----------+-------+\n<strong>输出：</strong>\n+-------------+--------------+\n| product_id | product_name |\n+-------------+--------------+\n| 1 | S8 |\n+-------------+--------------+\n<strong>解释:</strong>\nid 为 1 的产品仅在 2019 年春季销售。\nid 为 2 的产品在 2019 年春季销售，但也在 2019 年春季之后销售。\nid 为 3 的产品在 2019 年春季之后销售。\n我们只返回 id 为 1 的产品，因为它是 2019 年春季才销售的产品。</pre>\n",
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"sampleTestCase": "{\"headers\":{\"Product\":[\"product_id\",\"product_name\",\"unit_price\"],\"Sales\":[\"seller_id\",\"product_id\",\"buyer_id\",\"sale_date\",\"quantity\",\"price\"]},\"rows\":{\"Product\":[[1,\"S8\",1000],[2,\"G4\",800],[3,\"iPhone\",1400]],\"Sales\":[[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]]}}",
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"Truncate table Product",
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"insert into Product (product_id, product_name, unit_price) values ('1', 'S8', '1000')",
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"insert into Product (product_id, product_name, unit_price) values ('2', 'G4', '800')",
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"insert into Product (product_id, product_name, unit_price) values ('3', 'iPhone', '1400')",
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"Truncate table Sales",
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"insert into Sales (seller_id, product_id, buyer_id, sale_date, quantity, price) values ('1', '1', '1', '2019-01-21', '2', '2000')",
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"insert into Sales (seller_id, product_id, buyer_id, sale_date, quantity, price) values ('1', '2', '2', '2019-02-17', '1', '800')",
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"insert into Sales (seller_id, product_id, buyer_id, sale_date, quantity, price) values ('2', '2', '3', '2019-06-02', '1', '800')",
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"insert into Sales (seller_id, product_id, buyer_id, sale_date, quantity, price) values ('3', '3', '4', '2019-05-13', '2', '2800')"
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