Meta·Data Scientist·Technical Phone Screen·Intermediate

Intermediate

May 2024

Summary

Meta DS interview with a SQL question focused on deduplication logic. Pretty straightforward problem but the business framing around feed quality made it feel more real than a typical leetcode-style thing.

Questions Asked (1)

Given a posts table with columns for post ID, user ID, timestamp, and content, write a SQL query that returns the user ID, content, and a count of duplicates for cases where the same user posted identical content on the same calendar day, filtering to only groups with two or more posts.

Product Analytics & MetricsData Modeling

Author's notes

The core logic isn't hard once you realize you need to group on three things: user, content, and the date part of the timestamp.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the table schema and the definition of 'same calendar day' (e.g., using DATE(timestamp)). Then write a query that groups by user_id, content, and the date, counts the rows, and filters with HAVING COUNT(*) >= 2. Finally, select the required columns: user_id, content, and the duplicate count.

Pro tip: Mention that you would handle potential NULLs in content or user_id and consider timezone implications for the calendar day, as these are common pitfalls in production data.

1. Clarify requirements and schema

Confirm the exact column names and data types, and define what 'same calendar day' means (e.g., based on timestamp date). Ask if duplicates should be counted per user per day or across all users.

2. Group and count duplicates

Use GROUP BY on user_id, content, and the extracted date from timestamp. Apply COUNT(*) to get the number of posts in each group.

3. Filter groups with duplicates

Use HAVING COUNT(*) >= 2 to keep only groups where the same user posted identical content on the same day at least twice.

4. Select and format output

Return user_id, content, and the count as duplicate_count. Optionally include the date for clarity, but the question asks for user ID, content, and count.

5. Consider edge cases and performance

Discuss handling NULLs, timezone conversion, and indexing strategies for large datasets. Mention that the query might need to be adapted for different SQL dialects.

Key Points to Mention

Use of DATE() or CAST(timestamp AS DATE) to extract calendar day
GROUP BY on user_id, content, and date
HAVING clause to filter groups with COUNT(*) >= 2
Handling NULL values in content or user_id
Timezone considerations for timestamp to date conversion
Performance implications and indexing on (user_id, content, date)

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.