Calculate Distinct High-View Posts and Spam View-Prevalence

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Q: What difficulty level is this coding question?

This is a Medium difficulty Data Manipulation (SQL/Python) question, commonly asked during Technical Screen rounds at Meta.

Q: What role is this question designed for?

This question is commonly asked for Data Scientist candidates at Meta during technical interviews.

Question

content_views

| user_id | post_id | view_count | view_date |
| 101     | 572     | 3          | 2021-11-01 |
| 102     | 732     | 5          | 2021-11-02 |
| 103     | 153     | 12         | 2021-11-03 |
| 104     | 634     | 7          | 2021-11-01 |

​

violating_content

| post_id | violation_type | probability_violating |
| 572     | Spam           | 0.70                  |
| 732     | Scam           | 0.85                  |
| 153     | Nudity         | 0.95                  |
| 634     | Harassment     | 0.50                  |

##### Scenario

A social platform tracks harmful content and needs SQL reports for ops dashboards.

##### Question

Write SQL to return the count of distinct posts that accumulated more than 10 views within the past 7 days (inclusive). Write SQL to calculate the view-prevalence of Spam or Scam posts during the last 30 days (total Spam/Scam views ÷ total views).

##### Hints

Derive a rolling window from MAX(view_date); join violating_content; filter violation_type IN ('Spam','Scam'); aggregate as required.

PracHub · Accepted Answer

This question evaluates proficiency in SQL-based data manipulation and analytical querying, including joins, aggregation, time-window filtering, and proportion calculations for operational metrics.

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