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leetcode-problemset/leetcode-cn/originData/movie-rating.json
2023-12-09 19:57:46 +08:00

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"question": {
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"questionFrontendId": "1341",
"categoryTitle": "Database",
"boundTopicId": 90536,
"title": "Movie Rating",
"titleSlug": "movie-rating",
"content": "<p>Table: <code>Movies</code></p>\n\n<pre>\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| movie_id | int |\n| title | varchar |\n+---------------+---------+\nmovie_id is the primary key (column with unique values) for this table.\ntitle is the name of the movie.\n</pre>\n\n<p>&nbsp;</p>\n\n<p>Table: <code>Users</code></p>\n\n<pre>\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| user_id | int |\n| name | varchar |\n+---------------+---------+\nuser_id is the primary key (column with unique values) for this table.\n</pre>\n\n<p>&nbsp;</p>\n\n<p>Table: <code>MovieRating</code></p>\n\n<pre>\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| movie_id | int |\n| user_id | int |\n| rating | int |\n| created_at | date |\n+---------------+---------+\n(movie_id, user_id) is the primary key (column with unique values)&nbsp;for this table.\nThis table contains the rating of a movie by a user in their review.\ncreated_at is the user&#39;s review date. \n</pre>\n\n<p>&nbsp;</p>\n\n<p>Write a solution to:</p>\n\n<ul>\n\t<li>Find the name of the user who has rated the greatest number of movies. In case of a tie, return the lexicographically smaller user name.</li>\n\t<li>Find the movie name with the <strong>highest average</strong> rating in <code>February 2020</code>. In case of a tie, return the lexicographically smaller movie name.</li>\n</ul>\n\n<p>The&nbsp;result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<p><strong class=\"example\">Example 1:</strong></p>\n\n<pre>\n<strong>Input:</strong> \nMovies table:\n+-------------+--------------+\n| movie_id | title |\n+-------------+--------------+\n| 1 | Avengers |\n| 2 | Frozen 2 |\n| 3 | Joker |\n+-------------+--------------+\nUsers table:\n+-------------+--------------+\n| user_id | name |\n+-------------+--------------+\n| 1 | Daniel |\n| 2 | Monica |\n| 3 | Maria |\n| 4 | James |\n+-------------+--------------+\nMovieRating table:\n+-------------+--------------+--------------+-------------+\n| movie_id | user_id | rating | created_at |\n+-------------+--------------+--------------+-------------+\n| 1 | 1 | 3 | 2020-01-12 |\n| 1 | 2 | 4 | 2020-02-11 |\n| 1 | 3 | 2 | 2020-02-12 |\n| 1 | 4 | 1 | 2020-01-01 |\n| 2 | 1 | 5 | 2020-02-17 | \n| 2 | 2 | 2 | 2020-02-01 | \n| 2 | 3 | 2 | 2020-03-01 |\n| 3 | 1 | 3 | 2020-02-22 | \n| 3 | 2 | 4 | 2020-02-25 | \n+-------------+--------------+--------------+-------------+\n<strong>Output:</strong> \n+--------------+\n| results |\n+--------------+\n| Daniel |\n| Frozen 2 |\n+--------------+\n<strong>Explanation:</strong> \nDaniel and Monica have rated 3 movies (&quot;Avengers&quot;, &quot;Frozen 2&quot; and &quot;Joker&quot;) but Daniel is smaller lexicographically.\nFrozen 2 and Joker have a rating average of 3.5 in February but Frozen 2 is smaller lexicographically.\n</pre>\n",
"translatedTitle": "电影评分",
"translatedContent": "<p>表:<code>Movies</code></p>\n\n<pre>\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| movie_id | int |\n| title | varchar |\n+---------------+---------+\nmovie_id 是这个表的主键(具有唯一值的列)。\ntitle 是电影的名字。\n</pre>\n\n<p>表:<code>Users</code></p>\n\n<pre>\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| user_id | int |\n| name | varchar |\n+---------------+---------+\nuser_id 是表的主键(具有唯一值的列)。\n</pre>\n\n<p>表:<code>MovieRating</code></p>\n\n<pre>\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| movie_id | int |\n| user_id | int |\n| rating | int |\n| created_at | date |\n+---------------+---------+\n(movie_id, user_id) 是这个表的主键(具有唯一值的列的组合)。\n这个表包含用户在其评论中对电影的评分 rating 。\ncreated_at 是用户的点评日期。 \n</pre>\n\n<p>&nbsp;</p>\n\n<p>请你编写一个解决方案:</p>\n\n<ul>\n\t<li>查找评论电影数量最多的用户名。如果出现平局,返回字典序较小的用户名。</li>\n\t<li>查找在 <code>February 2020</code><strong> 平均评分最高</strong> 的电影名称。如果出现平局,返回字典序较小的电影名称。</li>\n</ul>\n\n<p><strong>字典序</strong> ,即按字母在字典中出现顺序对字符串排序,字典序较小则意味着排序靠前。</p>\n\n<p>返回结果格式如下例所示。</p>\n\n<p>&nbsp;</p>\n\n<p><strong>示例 1</strong></p>\n\n<pre>\n<strong>输入:</strong>\nMovies 表:\n+-------------+--------------+\n| movie_id | title |\n+-------------+--------------+\n| 1 | Avengers |\n| 2 | Frozen 2 |\n| 3 | Joker |\n+-------------+--------------+\nUsers 表:\n+-------------+--------------+\n| user_id | name |\n+-------------+--------------+\n| 1 | Daniel |\n| 2 | Monica |\n| 3 | Maria |\n| 4 | James |\n+-------------+--------------+\nMovieRating 表:\n+-------------+--------------+--------------+-------------+\n| movie_id | user_id | rating | created_at |\n+-------------+--------------+--------------+-------------+\n| 1 | 1 | 3 | 2020-01-12 |\n| 1 | 2 | 4 | 2020-02-11 |\n| 1 | 3 | 2 | 2020-02-12 |\n| 1 | 4 | 1 | 2020-01-01 |\n| 2 | 1 | 5 | 2020-02-17 | \n| 2 | 2 | 2 | 2020-02-01 | \n| 2 | 3 | 2 | 2020-03-01 |\n| 3 | 1 | 3 | 2020-02-22 | \n| 3 | 2 | 4 | 2020-02-25 | \n+-------------+--------------+--------------+-------------+\n<strong>输出:</strong>\nResult 表:\n+--------------+\n| results |\n+--------------+\n| Daniel |\n| Frozen 2 |\n+--------------+\n<strong>解释:</strong>\nDaniel 和 Monica 都点评了 3 部电影(\"Avengers\", \"Frozen 2\" 和 \"Joker\" 但是 Daniel 字典序比较小。\nFrozen 2 和 Joker 在 2 月的评分都是 3.5,但是 Frozen 2 的字典序比较小。\n</pre>\n",
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"sampleTestCase": "{\"headers\": {\"Movies\": [\"movie_id\", \"title\"], \"Users\": [\"user_id\", \"name\"], \"MovieRating\": [\"movie_id\", \"user_id\", \"rating\", \"created_at\"]}, \"rows\": {\"Movies\": [[1, \"Avengers\"], [2, \"Frozen 2\"], [3, \"Joker\"]], \"Users\": [[1, \"Daniel\"], [2, \"Monica\"], [3, \"Maria\"], [4, \"James\"]], \"MovieRating\": [[1, 1, 3, \"2020-01-12\"], [1, 2, 4, \"2020-02-11\"], [1, 3, 2, \"2020-02-12\"], [1, 4, 1, \"2020-01-01\"], [2, 1, 5, \"2020-02-17\"], [2, 2, 2, \"2020-02-01\"], [2, 3, 2, \"2020-03-01\"], [3, 1, 3, \"2020-02-22\"], [3, 2, 4, \"2020-02-25\"]]}}",
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"Create table If Not Exists Users (user_id int, name varchar(30))",
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"Truncate table Movies",
"insert into Movies (movie_id, title) values ('1', 'Avengers')",
"insert into Movies (movie_id, title) values ('2', 'Frozen 2')",
"insert into Movies (movie_id, title) values ('3', 'Joker')",
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"insert into Users (user_id, name) values ('1', 'Daniel')",
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"insert into Users (user_id, name) values ('4', 'James')",
"Truncate table MovieRating",
"insert into MovieRating (movie_id, user_id, rating, created_at) values ('1', '1', '3', '2020-01-12')",
"insert into MovieRating (movie_id, user_id, rating, created_at) values ('1', '2', '4', '2020-02-11')",
"insert into MovieRating (movie_id, user_id, rating, created_at) values ('1', '3', '2', '2020-02-12')",
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"insert into MovieRating (movie_id, user_id, rating, created_at) values ('2', '2', '2', '2020-02-01')",
"insert into MovieRating (movie_id, user_id, rating, created_at) values ('2', '3', '2', '2020-03-01')",
"insert into MovieRating (movie_id, user_id, rating, created_at) values ('3', '1', '3', '2020-02-22')",
"insert into MovieRating (movie_id, user_id, rating, created_at) values ('3', '2', '4', '2020-02-25')"
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