+---------------+---------+
| Column Name | Type |
+---------------+---------+
| movie\_id | int |
| title | varchar |
+---------------+---------+
movie\_id is the primary key for this table.
title is the name of the movie.
Table: Users
+---------------+---------+
| Column Name | Type |
+---------------+---------+
| user\_id | int |
| name | varchar |
+---------------+---------+
user\_id is the primary key for this table.
Table: Movie_Rating
+---------------+---------+
| Column Name | Type |
+---------------+---------+
| movie\_id | int |
| user\_id | int |
| rating | int |
| created\_at | date |
+---------------+---------+
(movie\_id, user\_id) is the primary key for this table.
This table contains the rating of a movie by a user in their review.
created\_at is the user's review date.
Write the following SQL query:
Find the name of the user who has rated the greatest number of movies. In case of a tie, return lexicographically smaller user name.
Find the movie name with the highest average rating in February 2020. In case of a tie, return lexicographically smaller movie name.
The query is returned in 2 rows, the query result format is in the following example:
Movies table:
+-------------+--------------+
| movie\_id | title |
+-------------+--------------+
| 1 | Avengers |
| 2 | Frozen 2 |
| 3 | Joker |
+-------------+--------------+
Users table:
+-------------+--------------+
| user\_id | name |
+-------------+--------------+
| 1 | Daniel |
| 2 | Monica |
| 3 | Maria |
| 4 | James |
+-------------+--------------+
Movie\_Rating table:
+-------------+--------------+--------------+-------------+
| movie\_id | user\_id | rating | created\_at |
+-------------+--------------+--------------+-------------+
| 1 | 1 | 3 | 2020-01-12 |
| 1 | 2 | 4 | 2020-02-11 |
| 1 | 3 | 2 | 2020-02-12 |
| 1 | 4 | 1 | 2020-01-01 |
| 2 | 1 | 5 | 2020-02-17 |
| 2 | 2 | 2 | 2020-02-01 |
| 2 | 3 | 2 | 2020-03-01 |
| 3 | 1 | 3 | 2020-02-22 |
| 3 | 2 | 4 | 2020-02-25 |
+-------------+--------------+--------------+-------------+
Result table:
+--------------+
| results |
+--------------+
| Daniel |
| Frozen 2 |
+--------------+
Daniel and Monica have rated 3 movies ("Avengers", "Frozen 2" and "Joker") but Daniel is smaller lexicographically.
Frozen 2 and Joker have a rating average of 3.5 in February but Frozen 2 is smaller lexicographically.