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96 lines
11 KiB
JSON
96 lines
11 KiB
JSON
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"questionId": "184",
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"categoryTitle": "Database",
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"boundTopicId": 1338,
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"title": "Department Highest Salary",
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"titleSlug": "department-highest-salary",
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"content": "<p>Table: <code>Employee</code></p>\n\n<pre>\n+--------------+---------+\n| Column Name | Type |\n+--------------+---------+\n| id | int |\n| name | varchar |\n| salary | int |\n| departmentId | int |\n+--------------+---------+\nid is the primary key (column with unique values) for this table.\ndepartmentId is a foreign key (reference columns) of the ID from the <code>Department </code>table.\nEach row of this table indicates the ID, name, and salary of an employee. It also contains the ID of their department.\n</pre>\n\n<p> </p>\n\n<p>Table: <code>Department</code></p>\n\n<pre>\n+-------------+---------+\n| Column Name | Type |\n+-------------+---------+\n| id | int |\n| name | varchar |\n+-------------+---------+\nid is the primary key (column with unique values) for this table. It is guaranteed that department name is not <code>NULL.</code>\nEach row of this table indicates the ID of a department and its name.\n</pre>\n\n<p> </p>\n\n<p>Write a solution to find employees who have the highest salary in each of the departments.</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> \nEmployee table:\n+----+-------+--------+--------------+\n| id | name | salary | departmentId |\n+----+-------+--------+--------------+\n| 1 | Joe | 70000 | 1 |\n| 2 | Jim | 90000 | 1 |\n| 3 | Henry | 80000 | 2 |\n| 4 | Sam | 60000 | 2 |\n| 5 | Max | 90000 | 1 |\n+----+-------+--------+--------------+\nDepartment table:\n+----+-------+\n| id | name |\n+----+-------+\n| 1 | IT |\n| 2 | Sales |\n+----+-------+\n<strong>Output:</strong> \n+------------+----------+--------+\n| Department | Employee | Salary |\n+------------+----------+--------+\n| IT | Jim | 90000 |\n| Sales | Henry | 80000 |\n| IT | Max | 90000 |\n+------------+----------+--------+\n<strong>Explanation:</strong> Max and Jim both have the highest salary in the IT department and Henry has the highest salary in the Sales department.\n</pre>\n",
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"translatedTitle": "部门工资最高的员工",
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"translatedContent": "<p>表: <code>Employee</code></p>\n\n<pre>\n+--------------+---------+\n| 列名 | 类型 |\n+--------------+---------+\n| id | int |\n| name | varchar |\n| salary | int |\n| departmentId | int |\n+--------------+---------+\n在 SQL 中,id是此表的主键。\ndepartmentId 是 Department 表中 id 的外键(在 Pandas 中称为 join key)。\n此表的每一行都表示员工的 id、姓名和工资。它还包含他们所在部门的 id。\n</pre>\n\n<p> </p>\n\n<p>表: <code>Department</code></p>\n\n<pre>\n+-------------+---------+\n| 列名 | 类型 |\n+-------------+---------+\n| id | int |\n| name | varchar |\n+-------------+---------+\n在 SQL 中,id 是此表的主键列。\n此表的每一行都表示一个部门的 id 及其名称。\n</pre>\n\n<p> </p>\n\n<p>查找出每个部门中薪资最高的员工。<br />\n按 <strong>任意顺序</strong> 返回结果表。<br />\n查询结果格式如下例所示。</p>\n\n<p> </p>\n\n<p><strong>示例 1:</strong></p>\n\n<pre>\n<b>输入:</b>\nEmployee 表:\n+----+-------+--------+--------------+\n| id | name | salary | departmentId |\n+----+-------+--------+--------------+\n| 1 | Joe | 70000 | 1 |\n| 2 | Jim | 90000 | 1 |\n| 3 | Henry | 80000 | 2 |\n| 4 | Sam | 60000 | 2 |\n| 5 | Max | 90000 | 1 |\n+----+-------+--------+--------------+\nDepartment 表:\n+----+-------+\n| id | name |\n+----+-------+\n| 1 | IT |\n| 2 | Sales |\n+----+-------+\n<b>输出:</b>\n+------------+----------+--------+\n| Department | Employee | Salary |\n+------------+----------+--------+\n| IT | Jim | 90000 |\n| Sales | Henry | 80000 |\n| IT | Max | 90000 |\n+------------+----------+--------+\n<strong>解释:</strong>Max 和 Jim 在 IT 部门的工资都是最高的,Henry 在销售部的工资最高。</pre>\n",
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"sampleTestCase": "{\"headers\": {\"Employee\": [\"id\", \"name\", \"salary\", \"departmentId\"], \"Department\": [\"id\", \"name\"]}, \"rows\": {\"Employee\": [[1, \"Joe\", 70000, 1], [2, \"Jim\", 90000, 1], [3, \"Henry\", 80000, 2], [4, \"Sam\", 60000, 2], [5, \"Max\", 90000, 1]], \"Department\": [[1, \"IT\"], [2, \"Sales\"]]}}",
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"Truncate table Employee",
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"insert into Employee (id, name, salary, departmentId) values ('1', 'Joe', '70000', '1')",
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"insert into Employee (id, name, salary, departmentId) values ('2', 'Jim', '90000', '1')",
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"insert into Employee (id, name, salary, departmentId) values ('3', 'Henry', '80000', '2')",
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"insert into Employee (id, name, salary, departmentId) values ('4', 'Sam', '60000', '2')",
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"insert into Employee (id, name, salary, departmentId) values ('5', 'Max', '90000', '1')",
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"Truncate table Department",
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"insert into Department (id, name) values ('1', 'IT')",
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"insert into Department (id, name) values ('2', 'Sales')"
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