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commit 48cdd06c2b
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@@ -12,12 +12,12 @@
"translatedContent": "<p>表: <code>Customer</code></p>\n\n<pre>\n+---------------+---------+\n| Column Name | Type |\n+---------------+---------+\n| customer_id | int |\n| name | varchar |\n| visited_on | date |\n| amount | int |\n+---------------+---------+\n在 SQL 中,(customer_id, visited_on) 是该表的主键。\n该表包含一家餐馆的顾客交易数据。\nvisited_on 表示 (customer_id) 的顾客在 visited_on 那天访问了餐馆。\namount 是一个顾客某一天的消费总额。\n</pre>\n\n<p>&nbsp;</p>\n\n<p>你是餐馆的老板,现在你想分析一下可能的营业额变化增长(每天至少有一位顾客)。</p>\n\n<p>计算以 7 天(某日期 + 该日期前的 6 天)为一个时间段的顾客消费平均值。<code>average_amount</code>&nbsp;要 <strong>保留两位小数。</strong></p>\n\n<p>结果按 <code>visited_on</code>&nbsp;<strong>升序排序</strong>。</p>\n\n<p>返回结果格式的例子如下。</p>\n\n<p>&nbsp;</p>\n\n<p><strong>示例 1:</strong></p>\n\n<pre>\n<strong>输入:</strong>\nCustomer 表:\n+-------------+--------------+--------------+-------------+\n| customer_id | name | visited_on | amount |\n+-------------+--------------+--------------+-------------+\n| 1 | Jhon | 2019-01-01 | 100 |\n| 2 | Daniel | 2019-01-02 | 110 |\n| 3 | Jade | 2019-01-03 | 120 |\n| 4 | Khaled | 2019-01-04 | 130 |\n| 5 | Winston | 2019-01-05 | 110 | \n| 6 | Elvis | 2019-01-06 | 140 | \n| 7 | Anna | 2019-01-07 | 150 |\n| 8 | Maria | 2019-01-08 | 80 |\n| 9 | Jaze | 2019-01-09 | 110 | \n| 1 | Jhon | 2019-01-10 | 130 | \n| 3 | Jade | 2019-01-10 | 150 | \n+-------------+--------------+--------------+-------------+\n<strong>输出:</strong>\n+--------------+--------------+----------------+\n| visited_on | amount | average_amount |\n+--------------+--------------+----------------+\n| 2019-01-07 | 860 | 122.86 |\n| 2019-01-08 | 840 | 120 |\n| 2019-01-09 | 840 | 120 |\n| 2019-01-10 | 1000 | 142.86 |\n+--------------+--------------+----------------+\n<strong>解释:</strong>\n第一个七天消费平均值从 2019-01-01 到 2019-01-07 是restaurant-growth/restaurant-growth/ (100 + 110 + 120 + 130 + 110 + 140 + 150)/7 = 122.86\n第二个七天消费平均值从 2019-01-02 到 2019-01-08 是 (110 + 120 + 130 + 110 + 140 + 150 + 80)/7 = 120\n第三个七天消费平均值从 2019-01-03 到 2019-01-09 是 (120 + 130 + 110 + 140 + 150 + 80 + 110)/7 = 120\n第四个七天消费平均值从 2019-01-04 到 2019-01-10 是 (130 + 110 + 140 + 150 + 80 + 110 + 130 + 150)/7 = 142.86</pre>\n",
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@@ -83,7 +83,7 @@
"insert into Customer (customer_id, name, visited_on, amount) values ('3', 'Jade', '2019-01-10', '150')"
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