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94 lines
12 KiB
JSON
94 lines
12 KiB
JSON
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"categoryTitle": "Database",
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"boundTopicId": 33159,
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"title": "Immediate Food Delivery II",
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"titleSlug": "immediate-food-delivery-ii",
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"content": "<p>Table: <code>Delivery</code></p>\n\n<pre>\n+-----------------------------+---------+\n| Column Name | Type |\n+-----------------------------+---------+\n| delivery_id | int |\n| customer_id | int |\n| order_date | date |\n| customer_pref_delivery_date | date |\n+-----------------------------+---------+\ndelivery_id is the column of unique values of this table.\nThe table holds information about food delivery to customers that make orders at some date and specify a preferred delivery date (on the same order date or after it).\n</pre>\n\n<p> </p>\n\n<p>If the customer's preferred delivery date is the same as the order date, then the order is called <strong>immediate;</strong> otherwise, it is called <strong>scheduled</strong>.</p>\n\n<p>The <strong>first order</strong> of a customer is the order with the earliest order date that the customer made. It is guaranteed that a customer has precisely one first order.</p>\n\n<p>Write a solution to find the percentage of immediate orders in the first orders of all customers, <strong>rounded to 2 decimal places</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> \nDelivery table:\n+-------------+-------------+------------+-----------------------------+\n| delivery_id | customer_id | order_date | customer_pref_delivery_date |\n+-------------+-------------+------------+-----------------------------+\n| 1 | 1 | 2019-08-01 | 2019-08-02 |\n| 2 | 2 | 2019-08-02 | 2019-08-02 |\n| 3 | 1 | 2019-08-11 | 2019-08-12 |\n| 4 | 3 | 2019-08-24 | 2019-08-24 |\n| 5 | 3 | 2019-08-21 | 2019-08-22 |\n| 6 | 2 | 2019-08-11 | 2019-08-13 |\n| 7 | 4 | 2019-08-09 | 2019-08-09 |\n+-------------+-------------+------------+-----------------------------+\n<strong>Output:</strong> \n+----------------------+\n| immediate_percentage |\n+----------------------+\n| 50.00 |\n+----------------------+\n<strong>Explanation:</strong> \nThe customer id 1 has a first order with delivery id 1 and it is scheduled.\nThe customer id 2 has a first order with delivery id 2 and it is immediate.\nThe customer id 3 has a first order with delivery id 5 and it is scheduled.\nThe customer id 4 has a first order with delivery id 7 and it is immediate.\nHence, half the customers have immediate first orders.\n</pre>\n",
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"translatedTitle": "即时食物配送 II",
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"translatedContent": "<p>配送表: <code>Delivery</code></p>\n\n<pre>\n+-----------------------------+---------+\n| Column Name | Type |\n+-----------------------------+---------+\n| delivery_id | int |\n| customer_id | int |\n| order_date | date |\n| customer_pref_delivery_date | date |\n+-----------------------------+---------+\ndelivery_id 是该表中具有唯一值的列。\n该表保存着顾客的食物配送信息，顾客在某个日期下了订单，并指定了一个期望的配送日期（和下单日期相同或者在那之后）。\n</pre>\n\n<p> </p>\n\n<p>如果顾客期望的配送日期和下单日期相同，则该订单称为 「<strong>即时订单</strong>」，否则称为「<strong>计划订单</strong>」。</p>\n\n<p>「<strong>首次订单</strong>」是顾客最早创建的订单。我们保证一个顾客只会有一个「首次订单」。</p>\n\n<p>编写解决方案以获取即时订单在所有用户的首次订单中的比例。<strong>保留两位小数。</strong></p>\n\n<p>结果示例如下所示：</p>\n\n<p> </p>\n\n<p><strong>示例 1：</strong></p>\n\n<pre>\n<strong>输入：</strong>\nDelivery 表：\n+-------------+-------------+------------+-----------------------------+\n| delivery_id | customer_id | order_date | customer_pref_delivery_date |\n+-------------+-------------+------------+-----------------------------+\n| 1 | 1 | 2019-08-01 | 2019-08-02 |\n| 2 | 2 | 2019-08-02 | 2019-08-02 |\n| 3 | 1 | 2019-08-11 | 2019-08-12 |\n| 4 | 3 | 2019-08-24 | 2019-08-24 |\n| 5 | 3 | 2019-08-21 | 2019-08-22 |\n| 6 | 2 | 2019-08-11 | 2019-08-13 |\n| 7 | 4 | 2019-08-09 | 2019-08-09 |\n+-------------+-------------+------------+-----------------------------+\n<strong>输出：</strong>\n+----------------------+\n| immediate_percentage |\n+----------------------+\n| 50.00 |\n+----------------------+\n<strong>解释：</strong>\n1 号顾客的 1 号订单是首次订单，并且是计划订单。\n2 号顾客的 2 号订单是首次订单，并且是即时订单。\n3 号顾客的 5 号订单是首次订单，并且是计划订单。\n4 号顾客的 7 号订单是首次订单，并且是即时订单。\n因此，一半顾客的首次订单是即时的。\n</pre>\n",
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"sampleTestCase": "{\"headers\":{\"Delivery\":[\"delivery_id\",\"customer_id\",\"order_date\",\"customer_pref_delivery_date\"]},\"rows\":{\"Delivery\":[[1,1,\"2019-08-01\",\"2019-08-02\"],[2,2,\"2019-08-02\",\"2019-08-02\"],[3,1,\"2019-08-11\",\"2019-08-12\"],[4,3,\"2019-08-24\",\"2019-08-24\"],[5,3,\"2019-08-21\",\"2019-08-22\"],[6,2,\"2019-08-11\",\"2019-08-13\"],[7,4,\"2019-08-09\",\"2019-08-09\"]]}}",
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"Create table If Not Exists Delivery (delivery_id int, customer_id int, order_date date, customer_pref_delivery_date date)",
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"Truncate table Delivery",
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"insert into Delivery (delivery_id, customer_id, order_date, customer_pref_delivery_date) values ('1', '1', '2019-08-01', '2019-08-02')",
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"insert into Delivery (delivery_id, customer_id, order_date, customer_pref_delivery_date) values ('2', '2', '2019-08-02', '2019-08-02')",
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"insert into Delivery (delivery_id, customer_id, order_date, customer_pref_delivery_date) values ('3', '1', '2019-08-11', '2019-08-12')",
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"insert into Delivery (delivery_id, customer_id, order_date, customer_pref_delivery_date) values ('4', '3', '2019-08-24', '2019-08-24')",
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"insert into Delivery (delivery_id, customer_id, order_date, customer_pref_delivery_date) values ('5', '3', '2019-08-21', '2019-08-22')",
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"insert into Delivery (delivery_id, customer_id, order_date, customer_pref_delivery_date) values ('6', '2', '2019-08-11', '2019-08-13')",
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"insert into Delivery (delivery_id, customer_id, order_date, customer_pref_delivery_date) values ('7', '4', '2019-08-09', '2019-08-09')"
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