Optimize a slow query on products
Last updated: July 6, 2025
Quick Overview
A query on products is running slowly. Identify the bottleneck and optimize it.
Adobe
July 6, 2025116
14
4,254 solved
A query on products is running slowly. Identify the bottleneck and optimize it.
This question from Adobe'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
- 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
- How would you validate the correctness of your query results?
- Can you rewrite this without using subqueries?
- How would you handle this if the data was spread across multiple databases?
- What would you do if this query needs to run every 5 minutes?
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