Window function: rank over category
Last updated: March 2, 2026
Quick Overview
Use window functions to compute rank partitioned by user_id.
Instacart
Data Manipulation (SQL/Python)
Data Scientist
Instacart
March 2, 2026Data Scientist
Technical Screen
Data Manipulation (SQL/Python)
Medium
287
7
2,956 solved
Use window functions to compute rank partitioned by user_id.
This question from Instacart's Technical Screen 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
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
Data cleaning and transformation
Aggregate functions and GROUP BY
Index optimization and query performance
Common Table Expressions (CTEs)
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
- Can you rewrite this without using subqueries?
- How would you optimize this query for a table with 100 million rows?
- What indexes would you create to support this query?
- What would you do if this query needs to run every 5 minutes?
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Practice SQL ProblemsSample Answer
Problem Understanding
The goal is to compute the rank of items purchased by users, partitioned by user_id and ordered by the purchase amount within each user. The data involved includes a table (let's call it purchases...
Approach
- Identify Data: We will use the
purchasestable which contains user purchase information. - Define the Window Function: We will use the
RANK()window function to assign a rank to each i...
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