Optimize a slow query on products
Last updated: April 9, 2026
Quick Overview
A query on products is running slowly. Identify the bottleneck and optimize it.
Lyft
April 9, 202617
5
3,626 solved
A query on products is running slowly. Identify the bottleneck and optimize it.
This question from Lyft'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 handle slowly changing dimensions in this scenario?
- How would you handle this if the data was spread across multiple databases?
- How would you optimize this query for a table with 100 million rows?
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Practice SQL ProblemsSample Answer
Problem Understanding
The task involves optimizing a slow SQL query that retrieves product data from a database. The primary data involved includes product details such as product ID, name, price, category, and timestamps ...
Approach
To optimize the query, I will take the following steps:
- Identify the Slow Query: Analyze the current query to identify bottlenecks such as unnecessary joins or missing indexes.
- **Use Common ...
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