Optimize a slow query on users
Last updated: December 31, 2025
Quick Overview
A query on users is running slowly. Identify the bottleneck and optimize it.
Compass
December 31, 202515
5
1,537 solved
A query on users is running slowly. Identify the bottleneck and optimize it.
This question from Compass's Onsite tests practical data skills. The interviewer wants to see clean, efficient queries that handle edge cases like NULLs, duplicates, and large datasets.
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
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 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?
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