Optimize a slow query on rides

Last updated: November 29, 2025

Quick Overview

A query on rides is running slowly. Identify the bottleneck and optimize it.

Uber
Data Manipulation (SQL/Python)
Data Scientist
Uber
November 29, 2025
Data Scientist
Technical Screen
Data Manipulation (SQL/Python)
Easy

134

5

2,583 solved


A query on rides is running slowly. Identify the bottleneck and optimize it.

Uber 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
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
Aggregate functions and GROUP BY
Index optimization and query performance
Pandas vectorized operations and groupby
JOIN types and when to use each
NULL handling and COALESCE
How to Approach This
  1. Clarify the schema and expected output format before writing queries.
  2. Use CTEs (WITH clauses) to break complex queries into readable steps.
  3. Consider window functions (ROW_NUMBER, RANK, LAG, LEAD) for ranking and sequential analysis.
  4. Watch for NULLs, duplicates, and edge cases in JOINs and GROUP BY.
  5. For pandas, prefer vectorized operations over row-by-row iteration.
Possible Follow-up Questions
  • What indexes would you create to support this query?
  • How would you optimize this query for a table with 100 million rows?
  • Can you rewrite this without using subqueries?
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