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2025-01-09 20:29:41 +08:00
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commit 48cdd06c2b
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leetcode-cn/originData/department-highest-salary.json
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@@ -12,12 +12,12 @@
"translatedContent": "<p>表：&nbsp;<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>&nbsp;</p>\n\n<p>表：&nbsp;<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>&nbsp;</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>&nbsp;</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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"difficulty": "Medium",
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"similarQuestions": "[]",
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@@ -59,7 +59,7 @@
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@@ -81,7 +81,7 @@
"insert into Department (id, name) values ('2', 'Sales')"
],
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