Optimize a slow query on products
Last updated: August 9, 2025
Quick Overview
A query on products is running slowly. Identify the bottleneck and optimize it.
Figma
August 9, 202510
6
3,540 solved
A query on products is running slowly. Identify the bottleneck and optimize it.
Figma asks this during the Technical Screen because data engineering skills are critical for the role. You should be comfortable with complex joins, window functions, CTEs, and performance optimization.
What the Interviewer Expects
- Write syntactically correct SQL with proper JOIN and WHERE clauses
- Use GROUP BY and aggregate functions appropriately
- Handle NULL values correctly in your queries
- Explain the query execution plan at a high level
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
- What would you do if this query needs to run every 5 minutes?
- How would you handle slowly changing dimensions in this scenario?
- How would you handle this if the data was spread across multiple databases?
- What indexes would you create to support this query?
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Solution Pattern
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