Optimize a slow query on products
Last updated: June 4, 2026
Quick Overview
A query on products is running slowly. Identify the bottleneck and optimize it.
Tesla
June 4, 202637
7
1,879 solved
A query on products is running slowly. Identify the bottleneck and optimize it.
This question from Tesla's Phone Screen 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
- Can you rewrite this without using subqueries?
- What indexes would you create to support this query?
- What would you do if this query needs to run every 5 minutes?
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Practice SQL ProblemsSample Answer
Problem Understanding
In this scenario, we are dealing with a products database for Tesla. The goal is to optimize a slow-running SQL query that retrieves product information. The data involved includes various attributes ...
Approach
To optimize the slow query, I would follow these steps: 1. Analyze the Current Query: Identify the existing query structure and performance bottlenecks (e.g., slow joins, missing indexes). 2. **Us...
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