Calculate retention rate per date
Last updated: April 11, 2026
Quick Overview
Write a query to compute retention rate grouped by user, handling edge cases like nulls and duplicates.
Grubhub
April 11, 20267
7
3,764 solved
Write a query to compute retention rate grouped by user, handling edge cases like nulls and duplicates.
This question from Grubhub'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 optimize this query for a table with 100 million rows?
- How would you validate the correctness of your query results?
- Can you rewrite this without using subqueries?
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