Meta·Data Scientist·Onsite - Coding / Algorithms·Intermediate

IntermediatePrefer not to say

May 2026

Summary

Meta onsite for a Data Scientist role, SQL-heavy session using an Oculus dataset. One question but it had a real edge case baked in that made it less trivial than it looked.

Questions Asked (1)

Given a table of daily user scores, write a SQL query that returns exactly the top 10 users by score. What happens when the users at positions 10 and 11 have the same score, and how does your query handle that?

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I jumped straight to ROW_NUMBER and felt pretty good about it until they asked what happens at the boundary.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the table schema and the definition of 'top 10' (e.g., ties, ordering). Then write a query using a window function like ROW_NUMBER() or RANK() to handle ties, and explain how each function affects the result when positions 10 and 11 tie. Finally, discuss the trade-offs and potential business implications.

Pro tip: Mention that at Meta, interviewers often care about how you handle edge cases and whether you consider the business impact of ties (e.g., fairness, user experience). Also, be prepared to discuss performance implications of different window functions.

1. Clarify requirements and schema

Ask about the table structure (e.g., columns: user_id, date, score) and whether 'top 10' means exactly 10 rows or all users with scores in the top 10 ranks. Confirm if ties should be broken arbitrarily or if there's a secondary criterion.

2. Choose the appropriate window function

Decide between ROW_NUMBER(), RANK(), and DENSE_RANK() based on the tie-handling requirement. Explain that ROW_NUMBER() assigns unique numbers even for ties, RANK() gives the same rank to ties but skips subsequent ranks, and DENSE_RANK() gives the same rank without gaps.

3. Write the SQL query

Construct a query using a subquery or CTE with the chosen window function, ordering by score descending. Then filter for rank <= 10 (or row_number <= 10) to get the top 10.

4. Analyze tie scenario at positions 10 and 11

Explain what happens with each function: with ROW_NUMBER(), one of the tied users is arbitrarily included and the other excluded; with RANK(), both get rank 10, so both are included (resulting in 11 rows); with DENSE_RANK(), both get rank 10, but if there are other ties, the number of rows may vary.

5. Discuss trade-offs and business implications

Talk about the pros and cons of each approach: ROW_NUMBER() ensures exactly 10 rows but may be unfair; RANK() includes ties but may return more than 10 rows; DENSE_RANK() is similar but can include even more. Consider performance and whether the business prefers fairness or exact count.

Key Points to Mention

Difference between ROW_NUMBER(), RANK(), and DENSE_RANK() in SQL
How ties affect the result set size and fairness
The importance of clarifying the definition of 'top 10' with the interviewer
Performance considerations of window functions on large datasets
Potential business implications of including or excluding tied users
Alternative approaches using LIMIT with ORDER BY (but note that it doesn't handle ties explicitly)

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