Window function: rank over category
Last updated: September 21, 2025
Quick Overview
Use window functions to compute running total partitioned by date.
Brex
Data Manipulation (SQL/Python)
Data Scientist
Brex
September 21, 2025Data Scientist
Onsite
Data Manipulation (SQL/Python)
Hard
28
6
3,151 solved
Use window functions to compute running total partitioned by date.
Brex 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
- Solve complex analytical problems with elegant, readable SQL
- Optimize queries for large-scale datasets with partitioning and indexing
- Use recursive CTEs, lateral joins, and advanced window functions
- Design the data model alongside the query solution
- Discuss trade-offs between SQL and programmatic approaches (Python/pandas)
- Consider the operational aspects: query scheduling, incremental processing
Key Topics to Cover
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
Aggregate functions and GROUP BY
Subqueries and correlated subqueries
NULL handling and COALESCE
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?
- 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 are dealing with a dataset that includes transaction records, likely with fields such as transaction_id, amount, transaction_date, and potentially a category. The objective...
Approach
- Identify the Table: Determine the relevant table, e.g.,
transactions, that contains the necessary fields. - Select Necessary Fields: We need to select
transaction_dateandamountto ...
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