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1321. 餐馆营业额变化增长

题目描述

表: Customer

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| customer_id   | int     |
| name          | varchar |
| visited_on    | date    |
| amount        | int     |
+---------------+---------+
在 SQL 中,(customer_id, visited_on) 是该表的主键。
该表包含一家餐馆的顾客交易数据。
visited_on 表示 (customer_id) 的顾客在 visited_on 那天访问了餐馆。
amount 是一个顾客某一天的消费总额。

 

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)。

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。average_amount 要 保留两位小数。

结果按 visited_on 升序排序

返回结果格式的例子如下。

 

示例 1:

输入:
Customer 表:
+-------------+--------------+--------------+-------------+
| customer_id | name         | visited_on   | amount      |
+-------------+--------------+--------------+-------------+
| 1           | Jhon         | 2019-01-01   | 100         |
| 2           | Daniel       | 2019-01-02   | 110         |
| 3           | Jade         | 2019-01-03   | 120         |
| 4           | Khaled       | 2019-01-04   | 130         |
| 5           | Winston      | 2019-01-05   | 110         | 
| 6           | Elvis        | 2019-01-06   | 140         | 
| 7           | Anna         | 2019-01-07   | 150         |
| 8           | Maria        | 2019-01-08   | 80          |
| 9           | Jaze         | 2019-01-09   | 110         | 
| 1           | Jhon         | 2019-01-10   | 130         | 
| 3           | Jade         | 2019-01-10   | 150         | 
+-------------+--------------+--------------+-------------+
输出:
+--------------+--------------+----------------+
| visited_on   | amount       | average_amount |
+--------------+--------------+----------------+
| 2019-01-07   | 860          | 122.86         |
| 2019-01-08   | 840          | 120            |
| 2019-01-09   | 840          | 120            |
| 2019-01-10   | 1000         | 142.86         |
+--------------+--------------+----------------+
解释:
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
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
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
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

解法

方法一

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# Write your MySQL query statement below
WITH
    t AS (
        SELECT
            visited_on,
            SUM(amount) OVER (
                ORDER BY visited_on
                ROWS 6 PRECEDING
            ) AS amount,
            RANK() OVER (
                ORDER BY visited_on
                ROWS 6 PRECEDING
            ) AS rk
        FROM
            (
                SELECT visited_on, SUM(amount) AS amount
                FROM Customer
                GROUP BY visited_on
            ) AS tt
    )
SELECT visited_on, amount, ROUND(amount / 7, 2) AS average_amount
FROM t
WHERE rk > 6;

方法二

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# Write your MySQL query statement below
SELECT
    a.visited_on,
    SUM(b.amount) AS amount,
    ROUND(SUM(b.amount) / 7, 2) AS average_amount
FROM
    (SELECT DISTINCT visited_on FROM customer) AS a
    JOIN customer AS b ON DATEDIFF(a.visited_on, b.visited_on) BETWEEN 0 AND 6
WHERE a.visited_on >= (SELECT MIN(visited_on) FROM customer) + 6
GROUP BY 1
ORDER BY 1;

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