00:00:00

Description

Editorial

Social Page Recommendations with Friend Signals

MEDIUM20 pts

A social platform stores friendship relationships and page-like events in relational tables.

Table: friendship

user1_id: one endpoint of a friendship pair
user2_id: the other endpoint of the pair
each row represents a direct friendship link between two users

Table: likes

user_id: user who liked a page
page_id: page identifier
each row represents one like action

Task: For every user that appears in the friendship graph, generate page recommendations from direct-friend behavior.

A page p is recommended to user u when:

at least one direct friend of u liked p
user u did not like p

For each recommendation, also return how many of u's direct friends liked that page.

Output requirements:

Return columns: user_id, page_id, friends_likes
friends_likes is the count of direct friends who liked page_id
Return each (user_id, page_id) at most once
Output order may be arbitrary

Supported submission environments:

SQL (SQLite 3.27.2)
Pandas (Python)

Example

Input

friendship:
| user1_id | user2_id |
|----------|----------|
| 1        | 2        |
| 1        | 3        |
| 1        | 4        |
| 2        | 3        |
| 2        | 5        |
| 6        | 1        |

likes:
| user_id | page_id |
|---------|---------|
| 1       | 88      |
| 2       | 23      |
| 3       | 24      |
| 4       | 56      |
| 5       | 11      |
| 6       | 33      |
| 2       | 77      |
| 3       | 77      |
| 6       | 88      |

Output

[
  {"user_id":1,"page_id":23,"friends_likes":1},
  {"user_id":1,"page_id":24,"friends_likes":1},
  {"user_id":1,"page_id":33,"friends_likes":1},
  {"user_id":1,"page_id":56,"friends_likes":1},
  {"user_id":1,"page_id":77,"friends_likes":2},
  {"user_id":2,"page_id":24,"friends_likes":1},
  {"user_id":2,"page_id":56,"friends_likes":1},
  {"user_id":2,"page_id":88,"friends_likes":1},
  {"user_id":3,"page_id":23,"friends_likes":1},
  {"user_id":3,"page_id":88,"friends_likes":1},
  {"user_id":4,"page_id":23,"friends_likes":1},
  {"user_id":4,"page_id":24,"friends_likes":1},
  {"user_id":4,"page_id":77,"friends_likes":1},
  {"user_id":4,"page_id":88,"friends_likes":1},
  {"user_id":5,"page_id":23,"friends_likes":1},
  {"user_id":5,"page_id":77,"friends_likes":1}
]

Explanation

For each user, gather pages liked by direct friends, remove pages already liked by that user, and count how many friends support each remaining page.

Example

Input

friendship:
| user1_id | user2_id |
|----------|----------|
| 10       | 11       |
| 10       | 12       |
| 11       | 12       |
| 12       | 13       |

likes:
| user_id | page_id |
|---------|---------|
| 10      | 1       |
| 11      | 2       |
| 11      | 3       |
| 12      | 1       |
| 12      | 2       |
| 12      | 4       |
| 13      | 4       |

Output

[
  {"user_id":10,"page_id":2,"friends_likes":2},
  {"user_id":10,"page_id":3,"friends_likes":1},
  {"user_id":10,"page_id":4,"friends_likes":1},
  {"user_id":11,"page_id":1,"friends_likes":2},
  {"user_id":11,"page_id":4,"friends_likes":1},
  {"user_id":12,"page_id":3,"friends_likes":1},
  {"user_id":13,"page_id":1,"friends_likes":1},
  {"user_id":13,"page_id":2,"friends_likes":1}
]

Explanation

A recommendation score increases when multiple direct friends like the same page. Pages already liked by the target user are excluded even if many friends liked them.

Example

Input

friendship:
| user1_id | user2_id |
|----------|----------|
| 21       | 22       |
| 22       | 23       |

likes:
| user_id | page_id |
|---------|---------|
| 21      | 5       |
| 22      | 5       |
| 23      | 5       |

Output

[]

Explanation

All candidate pages are already liked by the target users, so no recommendation rows remain.

Accepted0/0·0% Acceptance

Constraints

0 <= number of rows in friendship <= 250000
0 <= number of rows in likes <= 250000
1 <= user1_id, user2_id, user_id, page_id <= 1000000000
(user1_id, user2_id) is unique in friendship
(user_id, page_id) is unique in likes
Each friendship row connects two distinct users
Treat friendship as an undirected relationship
Recommendations are generated for users appearing in friendship
Exclude pages already liked by the target user
friends_likes counts direct friends who liked the recommended page
Return unique (user_id, page_id) rows with friends_likes
For SQL submissions, use SQLite 3.27.2 semantics
For Pandas submissions, return a DataFrame with columns user_id, page_id, friends_likes

Code

Visualizer

Solutions

14px

Test Cases3

Results

Submissions

likes =

[{"user_id":1,"page_id":88},{"user_id":2,"page_id":23},{"user_id":3,"page_id":24},{"user_id":4,"page_id":56},{"user_id":5,"page_id":11},{"user_id":6,"page_id":33},{"user_id":2,"page_id":77},{"user_id":3,"page_id":77},{"user_id":6,"page_id":88}]

friendship =

[{"user1_id":1,"user2_id":2},{"user1_id":1,"user2_id":3},{"user1_id":1,"user2_id":4},{"user1_id":2,"user2_id":3},{"user1_id":2,"user2_id":5},{"user1_id":6,"user2_id":1}]

Loading problem...

101

00:00:00

Description

Editorial

Social Page Recommendations with Friend Signals

MEDIUM20 pts

A social platform stores friendship relationships and page-like events in relational tables.

Table: friendship

user1_id: one endpoint of a friendship pair
user2_id: the other endpoint of the pair
each row represents a direct friendship link between two users

Table: likes

user_id: user who liked a page
page_id: page identifier
each row represents one like action

Task: For every user that appears in the friendship graph, generate page recommendations from direct-friend behavior.

A page p is recommended to user u when:

at least one direct friend of u liked p
user u did not like p

For each recommendation, also return how many of u's direct friends liked that page.

Output requirements:

Return columns: user_id, page_id, friends_likes
friends_likes is the count of direct friends who liked page_id
Return each (user_id, page_id) at most once
Output order may be arbitrary

Supported submission environments:

SQL (SQLite 3.27.2)
Pandas (Python)

Example

Input

friendship:
| user1_id | user2_id |
|----------|----------|
| 1        | 2        |
| 1        | 3        |
| 1        | 4        |
| 2        | 3        |
| 2        | 5        |
| 6        | 1        |

likes:
| user_id | page_id |
|---------|---------|
| 1       | 88      |
| 2       | 23      |
| 3       | 24      |
| 4       | 56      |
| 5       | 11      |
| 6       | 33      |
| 2       | 77      |
| 3       | 77      |
| 6       | 88      |

Output

[
  {"user_id":1,"page_id":23,"friends_likes":1},
  {"user_id":1,"page_id":24,"friends_likes":1},
  {"user_id":1,"page_id":33,"friends_likes":1},
  {"user_id":1,"page_id":56,"friends_likes":1},
  {"user_id":1,"page_id":77,"friends_likes":2},
  {"user_id":2,"page_id":24,"friends_likes":1},
  {"user_id":2,"page_id":56,"friends_likes":1},
  {"user_id":2,"page_id":88,"friends_likes":1},
  {"user_id":3,"page_id":23,"friends_likes":1},
  {"user_id":3,"page_id":88,"friends_likes":1},
  {"user_id":4,"page_id":23,"friends_likes":1},
  {"user_id":4,"page_id":24,"friends_likes":1},
  {"user_id":4,"page_id":77,"friends_likes":1},
  {"user_id":4,"page_id":88,"friends_likes":1},
  {"user_id":5,"page_id":23,"friends_likes":1},
  {"user_id":5,"page_id":77,"friends_likes":1}
]

Explanation

For each user, gather pages liked by direct friends, remove pages already liked by that user, and count how many friends support each remaining page.

Example

Input

friendship:
| user1_id | user2_id |
|----------|----------|
| 10       | 11       |
| 10       | 12       |
| 11       | 12       |
| 12       | 13       |

likes:
| user_id | page_id |
|---------|---------|
| 10      | 1       |
| 11      | 2       |
| 11      | 3       |
| 12      | 1       |
| 12      | 2       |
| 12      | 4       |
| 13      | 4       |

Output

[
  {"user_id":10,"page_id":2,"friends_likes":2},
  {"user_id":10,"page_id":3,"friends_likes":1},
  {"user_id":10,"page_id":4,"friends_likes":1},
  {"user_id":11,"page_id":1,"friends_likes":2},
  {"user_id":11,"page_id":4,"friends_likes":1},
  {"user_id":12,"page_id":3,"friends_likes":1},
  {"user_id":13,"page_id":1,"friends_likes":1},
  {"user_id":13,"page_id":2,"friends_likes":1}
]

Explanation

A recommendation score increases when multiple direct friends like the same page. Pages already liked by the target user are excluded even if many friends liked them.

Example

Input

friendship:
| user1_id | user2_id |
|----------|----------|
| 21       | 22       |
| 22       | 23       |

likes:
| user_id | page_id |
|---------|---------|
| 21      | 5       |
| 22      | 5       |
| 23      | 5       |

Output

[]

Explanation

All candidate pages are already liked by the target users, so no recommendation rows remain.

Accepted0/0·0% Acceptance

Constraints

0 <= number of rows in friendship <= 250000
0 <= number of rows in likes <= 250000
1 <= user1_id, user2_id, user_id, page_id <= 1000000000
(user1_id, user2_id) is unique in friendship
(user_id, page_id) is unique in likes
Each friendship row connects two distinct users
Treat friendship as an undirected relationship
Recommendations are generated for users appearing in friendship
Exclude pages already liked by the target user
friends_likes counts direct friends who liked the recommended page
Return unique (user_id, page_id) rows with friends_likes
For SQL submissions, use SQLite 3.27.2 semantics
For Pandas submissions, return a DataFrame with columns user_id, page_id, friends_likes

Code

Visualizer

Solutions

14px

Test Cases3

Results

Submissions

likes =

friendship =

[{"user1_id":1,"user2_id":2},{"user1_id":1,"user2_id":3},{"user1_id":1,"user2_id":4},{"user1_id":2,"user2_id":3},{"user1_id":2,"user2_id":5},{"user1_id":6,"user2_id":1}]

Social Page Recommendations with Friend Signals

Hints

Social Page Recommendations with Friend Signals

Hints