Window function: rank over user_id
Last updated: March 10, 2026
Quick Overview
Use window functions to compute rank partitioned by date.
Cloudflare
Data Manipulation (SQL/Python)
Data Scientist
Cloudflare
March 10, 2026Data Scientist
Technical Screen
Data Manipulation (SQL/Python)
Medium
135
11
3,051 solved
Use window functions to compute rank partitioned by date.
Data manipulation questions at Cloudflare test your ability to work with real-world datasets. This Technical Screen question evaluates your SQL proficiency, understanding of data modeling, and ability to derive insights from raw data.
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
Date/time manipulation
Pandas vectorized operations and groupby
JOIN types and when to use each
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
Index optimization and query performance
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 this if the data was spread across multiple databases?
- What would you do if this query needs to run every 5 minutes?
- How would you optimize this query for a table with 100 million rows?
- What indexes would you create to support this query?
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Practice SQL ProblemsSample Answer
Problem Understanding
In this problem, we need to compute the rank of users based on their activity on specific dates. The data involved includes a table with at least the following columns: user_id, activity_date, and...
Approach
- Data Selection: Start by selecting the relevant columns from the user activity table, ensuring to include
user_id,activity_date, andactivity_score. - Window Function: Use a window ...
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