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100 lines
3.0 KiB
HTML
100 lines
3.0 KiB
HTML
<p>表： <code>Users</code></p>
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<pre>
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+----------------+---------+
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| Column Name | Type |
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+----------------+---------+
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| user_id | int |
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| join_date | date |
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| favorite_brand | varchar |
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+----------------+---------+
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user_id 是此表主键（具有唯一值的列）。
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表中描述了购物网站的用户信息，用户可以在此网站上进行商品买卖。
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</pre>
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<p> </p>
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<p>表： <code>Orders</code></p>
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<pre>
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+---------------+---------+
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| Column Name | Type |
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+---------------+---------+
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| order_id | int |
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| order_date | date |
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| item_id | int |
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| buyer_id | int |
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| seller_id | int |
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+---------------+---------+
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order_id 是此表主键（具有唯一值的列）。
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item_id 是 Items 表的外键（reference 列）。
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（buyer_id，seller_id）是 User 表的外键。
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</pre>
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<p> </p>
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<p>表：<code>Items</code></p>
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<pre>
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+---------------+---------+
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| Column Name | Type |
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+---------------+---------+
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| item_id | int |
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| item_brand | varchar |
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+---------------+---------+
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item_id 是此表的主键（具有唯一值的列）。
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</pre>
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<p> </p>
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<p>编写解决方案找出每个用户的注册日期和在 <strong><code>2019</code> </strong>年作为买家的订单总数。</p>
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<p>以 <strong>任意顺序</strong> 返回结果表。</p>
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<p>查询结果格式如下。</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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<strong>输入：</strong>
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Users 表:
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+---------+------------+----------------+
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| user_id | join_date | favorite_brand |
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+---------+------------+----------------+
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| 1 | 2018-01-01 | Lenovo |
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| 2 | 2018-02-09 | Samsung |
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| 3 | 2018-01-19 | LG |
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| 4 | 2018-05-21 | HP |
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+---------+------------+----------------+
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Orders 表:
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+----------+------------+---------+----------+-----------+
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| order_id | order_date | item_id | buyer_id | seller_id |
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+----------+------------+---------+----------+-----------+
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| 1 | 2019-08-01 | 4 | 1 | 2 |
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| 2 | 2018-08-02 | 2 | 1 | 3 |
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| 3 | 2019-08-03 | 3 | 2 | 3 |
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| 4 | 2018-08-04 | 1 | 4 | 2 |
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| 5 | 2018-08-04 | 1 | 3 | 4 |
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| 6 | 2019-08-05 | 2 | 2 | 4 |
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+----------+------------+---------+----------+-----------+
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Items 表:
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+---------+------------+
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| item_id | item_brand |
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+---------+------------+
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| 1 | Samsung |
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| 2 | Lenovo |
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| 3 | LG |
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| 4 | HP |
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+---------+------------+
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<strong>输出：</strong>
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+-----------+------------+----------------+
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| buyer_id | join_date | orders_in_2019 |
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+-----------+------------+----------------+
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| 1 | 2018-01-01 | 1 |
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| 2 | 2018-02-09 | 2 |
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| 3 | 2018-01-19 | 0 |
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| 4 | 2018-05-21 | 0 |
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+-----------+------------+----------------+</pre>
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