Choose the Most Prolific Reviewer and February’s Best-Rated Movie

### Problem Return the available component rows in a column named results: first the name of the user who rated the most movies overall, breaking a count tie by lexicographically smaller name; then the title of the movie with the highest average rating during February 2020, breaking an average tie by lexicographically smaller title. Preserve the user-then-movie order when both components are present, including duplicate result values. In a tie on review count or mean rating, a missing name or title sorts after all recorded names or titles. ### Missing values The original statement does not define the result when a component has no eligible candidate. This adapted exercise omits that component's row. User activity counts matching rating records, including records whose rating value is NULL; a user is eligible when it has at least one such record. For the movie component, compute each February mean from known, non-NULL ratings only. A movie is eligible only if it has at least one known February rating; an all-NULL February group has no defined mean and contributes no candidate. This missing-rating/undefined-mean rule is an additional curator clarification, not a source NOT NULL or nonempty-population guarantee. Return the qualifying user row before the qualifying movie row when both exist, one row when only one exists, and no rows when neither exists. Do not invent a nonempty-cohort guarantee or emit a NULL placeholder for an absent component. This omission policy is our curator clarification, not an original-source fact. ### Tables Table: `Movies` ```text +---------------+---------+ | Column Name | Type | +---------------+---------+ | movie_id | int | | title | varchar | +---------------+---------+ movie_id is the primary key (column with unique values) for this table. title is the name of the movie. Each movie has a unique title. ``` Table: `Users` ```text +---------------+---------+ | Column Name | Type | +---------------+---------+ | user_id | int | | name | varchar | +---------------+---------+ user_id is the primary key (column with unique values) for this table. The column 'name' has unique values. ``` Table: `MovieRating` ```text +---------------+---------+ | Column Name | Type | +---------------+---------+ | movie_id | int | | user_id | int | | rating | int | | created_at | date | +---------------+---------+ (movie_id, user_id) is the primary key (column with unique values) 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. ``` ### Example ```text Movies (movie_id,title): (1,Aurora), (2,Bay) Users (user_id,name): (1,Ada), (2,Bo) MovieRating (movie_id,user_id,rating,created_at): (1,1,4,2020-02-01), (2,1,5,2020-02-02), (1,2,2,2020-02-03), (2,2,1,2020-02-04) Output (results): (Ada), (Aurora) Both users rated2 movies; both movies average3 in February. ``` ### Clarification example ```text Using the same Movies and Users as above, replace MovieRating by: (movie_id,user_id,rating,created_at): (1,1,4,2020-01-15) Output (results): (Ada) ``` Ada is the eligible reviewer winner; no movie has a February rating, so the movie component contributes no row. ### Missing-rating clarification example ```text Using the same Movies and Users, replace MovieRating by: (movie_id,user_id,rating,created_at): (1,1,NULL,2020-02-10), (2,1,5,2020-02-11) Output (results): (Ada), (Bay) ``` Ada has two rating records. Aurora has no known February rating, while Bay's known-rating mean is 5. If both rating values were NULL, Ada would still be the user result and the movie component would be omitted. ### What a Strong Answer Covers - Determine the two winners from their respective review populations and apply the stated tie-breaks. - Return the results in component order, preserving equal values and omitting absent components. ### Follow-up Questions - How would you return the top three results for each component? - How would you report the winners for every calendar month?