Daily Leads and Partners

Tags : mysql, sql, leetcode, easy

SQL Schema

Create table If Not Exists DailySales(date_id date, make_name varchar(20), lead_id int, partner_id int)
Truncate table DailySales
insert into DailySales (date_id, make_name, lead_id, partner_id) values ('2020-12-8', 'toyota', '0', '1')
insert into DailySales (date_id, make_name, lead_id, partner_id) values ('2020-12-8', 'toyota', '1', '0')
insert into DailySales (date_id, make_name, lead_id, partner_id) values ('2020-12-8', 'toyota', '1', '2')
insert into DailySales (date_id, make_name, lead_id, partner_id) values ('2020-12-7', 'toyota', '0', '2')
insert into DailySales (date_id, make_name, lead_id, partner_id) values ('2020-12-7', 'toyota', '0', '1')
insert into DailySales (date_id, make_name, lead_id, partner_id) values ('2020-12-8', 'honda', '1', '2')
insert into DailySales (date_id, make_name, lead_id, partner_id) values ('2020-12-8', 'honda', '2', '1')
insert into DailySales (date_id, make_name, lead_id, partner_id) values ('2020-12-7', 'honda', '0', '1')
insert into DailySales (date_id, make_name, lead_id, partner_id) values ('2020-12-7', 'honda', '1', '2')
insert into DailySales (date_id, make_name, lead_id, partner_id) values ('2020-12-7', 'honda', '2', '1')

Table: DailySales

+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| date_id     | date    |
| make_name   | varchar |
| lead_id     | int     |
| partner_id  | int     |
+-------------+---------+
This table does not have a primary key.
This table contains the date and the name of the product sold and the IDs of the lead and partner it was sold to.
The name consists of only lowercase English letters.

Your Task:

Write an SQL query that will, for each date_id and make_name, return the number of distinct lead_id’s and distinct partner_id’s.

Return the result table in any order.

The query result format is in the following example.

Example #

Input: 
DailySales table:
+-----------+-----------+---------+------------+
| date_id   | make_name | lead_id | partner_id |
+-----------+-----------+---------+------------+
| 2020-12-8 | toyota    | 0       | 1          |
| 2020-12-8 | toyota    | 1       | 0          |
| 2020-12-8 | toyota    | 1       | 2          |
| 2020-12-7 | toyota    | 0       | 2          |
| 2020-12-7 | toyota    | 0       | 1          |
| 2020-12-8 | honda     | 1       | 2          |
| 2020-12-8 | honda     | 2       | 1          |
| 2020-12-7 | honda     | 0       | 1          |
| 2020-12-7 | honda     | 1       | 2          |
| 2020-12-7 | honda     | 2       | 1          |
+-----------+-----------+---------+------------+
Output: 
+-----------+-----------+--------------+-----------------+
| date_id   | make_name | unique_leads | unique_partners |
+-----------+-----------+--------------+-----------------+
| 2020-12-8 | toyota    | 2            | 3               |
| 2020-12-7 | toyota    | 1            | 2               |
| 2020-12-8 | honda     | 2            | 2               |
| 2020-12-7 | honda     | 3            | 2               |
+-----------+-----------+--------------+-----------------+
Explanation: 
For 2020-12-8, toyota gets leads = [0, 1] and partners = [0, 1, 2] while honda gets leads = [1, 2] and partners = [1, 2].
For 2020-12-7, toyota gets leads = [0] and partners = [1, 2] while honda gets leads = [0, 1, 2] and partners = [1, 2].

Solutions #


-- Write your T-SQL query statement below
select date_id, make_name, count(distinct lead_id) as "unique_leads", count(distinct partner_id) as "unique_partners"
from dailysales 
group by date_id, make_name
;