Optimize a slow query on rides
Last updated: August 22, 2025
Quick Overview
A query on rides is running slowly. Identify the bottleneck and optimize it.
Shopify
Data Manipulation (SQL/Python)
Data Scientist
Shopify
August 22, 2025Data Scientist
Onsite
Data Manipulation (SQL/Python)
Medium
47
6
1,458 solved
A query on rides is running slowly. Identify the bottleneck and optimize it.
This question from Shopify'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
Subqueries and correlated subqueries
Common Table Expressions (CTEs)
Index optimization and query performance
Data cleaning and transformation
Aggregate functions and GROUP BY
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 would you do if this query needs to run every 5 minutes?
- Can you rewrite this without using subqueries?
- What indexes would you create to support this query?
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Practice SQL ProblemsSample Answer
Problem Understanding
The query involves a dataset of rides, which likely includes columns such as ride_id, user_id, driver_id, start_time, end_time, distance, and fare. The goal is to identify the bottleneck causing slow ...
Approach
- Analyze the Current Query: Start by reviewing the existing SQL query to identify any inefficient patterns such as unnecessary subqueries, lack of indexing, or extensive joins.
- **Identify B...
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