Window function: rank over category
Last updated: October 21, 2025
Quick Overview
Use window functions to compute rank partitioned by user_id.
Twitter/X
Data Manipulation (SQL/Python)
Data Scientist
Twitter/X
October 21, 2025Data Scientist
Technical Screen
Data Manipulation (SQL/Python)
Easy
16
6
1,609 solved
Use window functions to compute rank partitioned by user_id.
Twitter/X 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
Common Table Expressions (CTEs)
JOIN types and when to use each
Date/time manipulation
Data cleaning and transformation
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 validate the correctness of your query results?
- What indexes would you create to support this query?
- How would you handle this if the data was spread across multiple databases?
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Problem Understanding
In this problem, we are tasked with calculating the rank of tweets for each user based on a specific metric (e.g., likes, retweets) using SQL window functions. The data involved includes a table named...
Approach
- Identify the Base Table: Start with the
tweetstable, which contains the relevant columns. - Use Window Functions: Implement the SQL
RANK()function to assign ranks to tweets within ...
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