Leetcodify Friends Recommendations Problem

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+-------------+---------+
| Column Name | Type    |
+-------------+---------+
| user_id     | int     |
| song_id     | int     |
| day         | date    |
+-------------+---------+
There is no primary key for this table. It may contain duplicates.
Each row of this table indicates that the user user_id listened to the song song_id on the day day.

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+---------------+---------+
| Column Name   | Type    |
+---------------+---------+
| user1_id      | int     |
| user2_id      | int     |
+---------------+---------+
(user1_id, user2_id) is the primary key for this table.
Each row of this table indicates that the users user1_id and user2_id are friends.
Note that user1_id < user2_id.

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Listens table:
+---------+---------+------------+
| user_id | song_id | day        |
+---------+---------+------------+
| 1       | 10      | 2021-03-15 |
| 1       | 11      | 2021-03-15 |
| 1       | 12      | 2021-03-15 |
| 2       | 10      | 2021-03-15 |
| 2       | 11      | 2021-03-15 |
| 2       | 12      | 2021-03-15 |
| 3       | 10      | 2021-03-15 |
| 3       | 11      | 2021-03-15 |
| 3       | 12      | 2021-03-15 |
| 4       | 10      | 2021-03-15 |
| 4       | 11      | 2021-03-15 |
| 4       | 13      | 2021-03-15 |
| 5       | 10      | 2021-03-16 |
| 5       | 11      | 2021-03-16 |
| 5       | 12      | 2021-03-16 |
+---------+---------+------------+

Friendship table:
+----------+----------+
| user1_id | user2_id |
+----------+----------+
| 1        | 2        |
+----------+----------+

Result table:
+---------+----------------+
| user_id | recommended_id |
+---------+----------------+
| 1       | 3              |
| 2       | 3              |
| 3       | 1              |
| 3       | 2              |
+---------+----------------+
Users 1 and 2 listened to songs 10, 11, and 12 on the same day, but they are already friends.
Users 1 and 3 listened to songs 10, 11, and 12 on the same day. Since they are not friends, we recommend them to each other.
Users 1 and 4 did not listen to the same three songs.
Users 1 and 5 listened to songs 10, 11, and 12, but on different days.

Similarly, we can see that users 2 and 3 listened to songs 10, 11, and 12 on the same day and are not friends, so we recommend them to each other.

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with allRecs as (
	select distinct
	  l1.user_id as user1_id,
	  l2.user_id as user2_id
	from Listens l1 inner join Listens l2 on l1.song_id = l2.song_id and l1.day=l2.day and l1.user_id < l2.user_id
	where not exists(select * from Friendship f where l1.user_id = f.user1_id and l2.user_id = f.user2_id)
	group by l1.user_id, l2.user_id, l1.day
	having count(distinct l1.song_id) >= 3
) 
select user1_id as user_id,
       user2_id as recommended_id
from allRecs
union
select user2_id as user_id,
       user1_id as recommended_id
from allRecs