Optimize a slow query on users
Last updated: November 3, 2025
Quick Overview
A query on users is running slowly. Identify the bottleneck and optimize it.
OpenAI
Data Manipulation (SQL/Python)
Data Scientist
OpenAI
November 3, 2025Data Scientist
Technical Screen
Data Manipulation (SQL/Python)
Medium
38
5
1,100 solved
A query on users is running slowly. Identify the bottleneck and optimize it.
Data manipulation questions at OpenAI test your ability to work with real-world datasets. This Technical Screen question evaluates your SQL proficiency, understanding of data modeling, and ability to derive insights from raw data.
What the Interviewer Expects
- Use advanced SQL features: window functions, CTEs, subqueries
- Write efficient queries that avoid common performance pitfalls
- Handle complex data transformations with multiple joins and aggregations
- Discuss indexing strategy and query optimization
- Address data quality issues: duplicates, missing values, outliers
Key Topics to Cover
Date/time manipulation
Pandas vectorized operations and groupby
Common Table Expressions (CTEs)
NULL handling and COALESCE
Aggregate functions and GROUP BY
How to Approach This
- Clarify the schema and expected output format before writing queries.
- Use CTEs (WITH clauses) to break complex queries into readable steps.
- Consider window functions (ROW_NUMBER, RANK, LAG, LEAD) for ranking and sequential analysis.
- Watch for NULLs, duplicates, and edge cases in JOINs and GROUP BY.
- For pandas, prefer vectorized operations over row-by-row iteration.
Possible Follow-up Questions
- How would you handle slowly changing dimensions in this scenario?
- How would you validate the correctness of your query results?
- What would you do if this query needs to run every 5 minutes?
- Can you rewrite this without using subqueries?
Sharpen Your Skills on Codemia
Practice similar problems with our interactive workspace, get AI feedback, and track your progress.
Practice SQL ProblemsSample Answer
Problem Understanding
The dataset involves a 'users' table that contains user information, including fields such as user_id, created_at (timestamp of user registration), last_login (timestamp of last user login), and possi...
Approach
- Analyze the Existing Query: Start by reviewing the slow query to identify potential bottlenecks such as inefficient joins, excessive data, or lack of proper indexing.
- **Use Common Table Expr...
Submit Your Answer
Markdown supported