Calculate percentile rank per date
Last updated: September 10, 2025
Quick Overview
Write a query to compute percentile rank grouped by user, handling edge cases like nulls and duplicates.
Snapchat
September 10, 2025587
7
1,451 solved
Write a query to compute percentile rank grouped by user, handling edge cases like nulls and duplicates.
Snapchat asks this during the Onsite 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
- 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 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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Practice SQL ProblemsSample Answer
Problem Understanding
The task is to compute the percentile rank of users based on some metric (e.g., engagement score or activity count) for each date. The data involved includes user identifiers, dates, and the metric fo...
Approach
- Identify the Data: Determine the tables needed, typically a user activity table containing user IDs, dates, and the metric.
- Data Cleaning: Use COALESCE to handle NULL values in the met...
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