41-01532-the-most-recent-three-orders.sql

1532. The Most Recent Three Orders

    Table: Customers

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| customer_id   | int     |
| name          | varchar |
+---------------+---------+
customer_id is the column with unique values for this table.
This table contains information about customers.

 

Table: Orders

+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| order_id      | int     |
| order_date    | date    |
| customer_id   | int     |
| cost          | int     |
+---------------+---------+
order_id is the column with unique values for this table.
This table contains information about the orders made by customer_id.
Each customer has one order per day.

 

Write a solution to find the most recent three orders of each user. If a user ordered less than three orders, return all of their orders.

Return the result table ordered by customer_name in ascending order and in case of a tie by the customer_id in ascending order. If there is still a tie, order them by order_date in descending order.

The result format is in the following example.

 

Example 1:

Input: 
Customers table:
+-------------+-----------+
| customer_id | name      |
+-------------+-----------+
| 1           | Winston   |
| 2           | Jonathan  |
| 3           | Annabelle |
| 4           | Marwan    |
| 5           | Khaled    |
+-------------+-----------+
Orders table:
+----------+------------+-------------+------+
| order_id | order_date | customer_id | cost |
+----------+------------+-------------+------+
| 1        | 2020-07-31 | 1           | 30   |
| 2        | 2020-07-30 | 2           | 40   |
| 3        | 2020-07-31 | 3           | 70   |
| 4        | 2020-07-29 | 4           | 100  |
| 5        | 2020-06-10 | 1           | 1010 |
| 6        | 2020-08-01 | 2           | 102  |
| 7        | 2020-08-01 | 3           | 111  |
| 8        | 2020-08-03 | 1           | 99   |
| 9        | 2020-08-07 | 2           | 32   |
| 10       | 2020-07-15 | 1           | 2    |
+----------+------------+-------------+------+
Output: 
+---------------+-------------+----------+------------+
| customer_name | customer_id | order_id | order_date |
+---------------+-------------+----------+------------+
| Annabelle     | 3           | 7        | 2020-08-01 |
| Annabelle     | 3           | 3        | 2020-07-31 |
| Jonathan      | 2           | 9        | 2020-08-07 |
| Jonathan      | 2           | 6        | 2020-08-01 |
| Jonathan      | 2           | 2        | 2020-07-30 |
| Marwan        | 4           | 4        | 2020-07-29 |
| Winston       | 1           | 8        | 2020-08-03 |
| Winston       | 1           | 1        | 2020-07-31 |
| Winston       | 1           | 10       | 2020-07-15 |
+---------------+-------------+----------+------------+
Explanation: 
Winston has 4 orders, we discard the order of "2020-06-10" because it is the oldest order.
Annabelle has only 2 orders, we return them.
Jonathan has exactly 3 orders.
Marwan ordered only one time.
We sort the result table by customer_name in ascending order, by customer_id in ascending order, and by order_date in descending order in case of a tie.

 Follow up: Could you write a general solution for the most recent n orders?

SQL Schema:
Create table If Not Exists Customers (customer_id int, name varchar(10))
Create table If Not Exists Orders (order_id int, order_date date, customer_id int, cost int)
Truncate table Customers
insert into Customers (customer_id, name) values ('1', 'Winston')
insert into Customers (customer_id, name) values ('2', 'Jonathan')
insert into Customers (customer_id, name) values ('3', 'Annabelle')
insert into Customers (customer_id, name) values ('4', 'Marwan')
insert into Customers (customer_id, name) values ('5', 'Khaled')
Truncate table Orders
insert into Orders (order_id, order_date, customer_id, cost) values ('1', '2020-07-31', '1', '30')
insert into Orders (order_id, order_date, customer_id, cost) values ('2', '2020-7-30', '2', '40')
insert into Orders (order_id, order_date, customer_id, cost) values ('3', '2020-07-31', '3', '70')
insert into Orders (order_id, order_date, customer_id, cost) values ('4', '2020-07-29', '4', '100')
insert into Orders (order_id, order_date, customer_id, cost) values ('5', '2020-06-10', '1', '1010')
insert into Orders (order_id, order_date, customer_id, cost) values ('6', '2020-08-01', '2', '102')
insert into Orders (order_id, order_date, customer_id, cost) values ('7', '2020-08-01', '3', '111')
insert into Orders (order_id, order_date, customer_id, cost) values ('8', '2020-08-03', '1', '99')
insert into Orders (order_id, order_date, customer_id, cost) values ('9', '2020-08-07', '2', '32')
insert into Orders (order_id, order_date, customer_id, cost) values ('10', '2020-07-15', '1', '2')
    

-- we needed top 3, so subquery won't be possible without window function
-- used dense_rank()

with CTE as
    (select *, dense_rank() over(partition by customer_id order by order_date desc) as rnk
    from Orders)

select c.name as customer_name, CTE.customer_id, CTE.order_id, CTE.order_date
from CTE
join Customers c
on CTE.customer_id = c.customer_id
where rnk <= 3
order by name, customer_id, order_date desc

-- no companies listed