00:00:00

Description

Editorial

Friend-Liked Page Suggestions

MEDIUM20 pts

A social discovery platform tracks user relationships and page likes in two relational tables.

Table: friendship

user1_id: one endpoint of a friendship pair
user2_id: the other endpoint of the friendship pair
each row means both users are direct friends

Table: likes

user_id: user who liked a page
page_id: page identifier
each row means the user liked that page

Task: Recommend pages for user_id = 1 using pages liked by their direct friends.

Recommendation rules:

Use only direct friends of user 1.
Collect all pages liked by those friends.
Exclude pages already liked by user 1.
Return each page exactly once.

Output requirements:

Return one column named recommended_page.
Result may be returned in any order.

Supported submission environments:

SQL (SQLite 3.27.2)
Pandas (Python)

Example

Input

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

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

Output

[
  {"recommended_page":23},
  {"recommended_page":24},
  {"recommended_page":33},
  {"recommended_page":77}
]

Explanation

Direct friends of user 1 are users 2, 3, and 4. Their liked pages are {23, 24, 33, 77}. Page 88 is excluded because user 1 already liked it.

Example

Input

friendship:
| user1_id | user2_id |
|----------|----------|
| 1        | 10       |

likes:
| user_id | page_id |
|---------|---------|
| 1       | 5       |
| 10      | 5       |

Output

[]

Explanation

Friend 10 liked only page 5, but user 1 already likes page 5, so there is no recommendation.

Example

Input

friendship:
| user1_id | user2_id |
|----------|----------|
| 2        | 1        |
| 3        | 1        |
| 6        | 7        |

likes:
| user_id | page_id |
|---------|---------|
| 2       | 900     |
| 3       | 901     |
| 6       | 902     |
| 1       | 999     |

Output

[
  {"recommended_page":900},
  {"recommended_page":901}
]

Explanation

Only direct friends of user 1 matter. User 6 is not directly connected to user 1, so page 902 is ignored.

Accepted0/0·0% Acceptance

Constraints

0 <= number of rows in friendship <= 200000
0 <= number of rows in likes <= 200000
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
Friendship is an undirected relationship represented by one row per pair
Recommend pages for user_id = 1 only
Exclude pages already liked by user 1
Return each recommended page exactly once
For SQL submissions, use SQLite 3.27.2 semantics
For Pandas submissions, return a DataFrame with one column: recommended_page

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

Loading problem...

101

00:00:00

Description

Editorial

Friend-Liked Page Suggestions

MEDIUM20 pts

A social discovery platform tracks user relationships and page likes in two relational tables.

Table: friendship

user1_id: one endpoint of a friendship pair
user2_id: the other endpoint of the friendship pair
each row means both users are direct friends

Table: likes

user_id: user who liked a page
page_id: page identifier
each row means the user liked that page

Task: Recommend pages for user_id = 1 using pages liked by their direct friends.

Recommendation rules:

Use only direct friends of user 1.
Collect all pages liked by those friends.
Exclude pages already liked by user 1.
Return each page exactly once.

Output requirements:

Return one column named recommended_page.
Result may be returned in any order.

Supported submission environments:

SQL (SQLite 3.27.2)
Pandas (Python)

Example

Input

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

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

Output

[
  {"recommended_page":23},
  {"recommended_page":24},
  {"recommended_page":33},
  {"recommended_page":77}
]

Explanation

Direct friends of user 1 are users 2, 3, and 4. Their liked pages are {23, 24, 33, 77}. Page 88 is excluded because user 1 already liked it.

Example

Input

friendship:
| user1_id | user2_id |
|----------|----------|
| 1        | 10       |

likes:
| user_id | page_id |
|---------|---------|
| 1       | 5       |
| 10      | 5       |

Output

[]

Explanation

Friend 10 liked only page 5, but user 1 already likes page 5, so there is no recommendation.

Example

Input

friendship:
| user1_id | user2_id |
|----------|----------|
| 2        | 1        |
| 3        | 1        |
| 6        | 7        |

likes:
| user_id | page_id |
|---------|---------|
| 2       | 900     |
| 3       | 901     |
| 6       | 902     |
| 1       | 999     |

Output

[
  {"recommended_page":900},
  {"recommended_page":901}
]

Explanation

Only direct friends of user 1 matter. User 6 is not directly connected to user 1, so page 902 is ignored.

Accepted0/0·0% Acceptance

Constraints

0 <= number of rows in friendship <= 200000
0 <= number of rows in likes <= 200000
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
Friendship is an undirected relationship represented by one row per pair
Recommend pages for user_id = 1 only
Exclude pages already liked by user 1
Return each recommended page exactly once
For SQL submissions, use SQLite 3.27.2 semantics
For Pandas submissions, return a DataFrame with one column: recommended_page

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

Friend-Liked Page Suggestions

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Friend-Liked Page Suggestions

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