Optimize a slow query on rides
Last updated: December 28, 2025
Quick Overview
A query on rides is running slowly. Identify the bottleneck and optimize it.
Capital One
December 28, 202556
11
3,291 solved
A query on rides is running slowly. Identify the bottleneck and optimize it.
This question from Capital One'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
- 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 indexes would you create to support this query?
- Can you rewrite this without using subqueries?
- How would you handle slowly changing dimensions in this scenario?
- How would you optimize this query for a table with 100 million rows?
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