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70 lines
1.9 KiB
HTML
70 lines
1.9 KiB
HTML
<p>表： <code>Employee</code></p>
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<pre>
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+--------------+---------+
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| 列名 | 类型 |
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+--------------+---------+
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| id | int |
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| name | varchar |
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| salary | int |
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| departmentId | int |
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+--------------+---------+
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在 SQL 中，id是此表的主键。
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departmentId 是 Department 表中 id 的外键（在 Pandas 中称为 join key）。
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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。
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</pre>
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<p> </p>
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<p>表： <code>Department</code></p>
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<pre>
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+-------------+---------+
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| 列名 | 类型 |
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+-------------+---------+
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| id | int |
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| name | varchar |
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+-------------+---------+
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在 SQL 中，id 是此表的主键列。
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此表的每一行都表示一个部门的 id 及其名称。
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</pre>
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<p> </p>
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<p>查找出每个部门中薪资最高的员工。<br />
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按 <strong>任意顺序</strong> 返回结果表。<br />
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查询结果格式如下例所示。</p>
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<p> </p>
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<p><strong>示例 1:</strong></p>
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<pre>
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<b>输入：</b>
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Employee 表:
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+----+-------+--------+--------------+
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| id | name | salary | departmentId |
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+----+-------+--------+--------------+
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| 1 | Joe | 70000 | 1 |
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| 2 | Jim | 90000 | 1 |
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| 3 | Henry | 80000 | 2 |
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| 4 | Sam | 60000 | 2 |
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| 5 | Max | 90000 | 1 |
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+----+-------+--------+--------------+
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Department 表:
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+----+-------+
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| id | name |
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+----+-------+
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| 1 | IT |
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| 2 | Sales |
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+----+-------+
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<b>输出：</b>
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+------------+----------+--------+
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| Department | Employee | Salary |
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+------------+----------+--------+
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| IT | Jim | 90000 |
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| Sales | Henry | 80000 |
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| IT | Max | 90000 |
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+------------+----------+--------+
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<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>
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