Window function: running total over date
Last updated: October 7, 2025
Quick Overview
Use window functions to compute rank partitioned by user_id.
Google
Data Manipulation (SQL/Python)
Data Scientist
Data Scientist
Onsite
Data Manipulation (SQL/Python)
Hard
4
7
3,610 solved
Use window functions to compute rank partitioned by user_id.
Google 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
Common Table Expressions (CTEs)
Aggregate functions and GROUP BY
Pandas vectorized operations and groupby
JOIN types and when to use each
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?
- How would you optimize this query for a table with 100 million rows?
- What indexes would you create to support this query?
- How would you validate the correctness of your query results?
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Practice SQL ProblemsSample Answer
Problem Understanding
The problem requires us to compute a running total of a specific metric (e.g., sales, clicks) for each user, partitioned by user_id, over a date column. The data involved includes a table with at le...
Approach
- Identify the Columns: We will focus on the columns:
user_id,date, and the metric (e.g.,amount). - Choose the Window Function: Use the
SUM()function as a window function to calcu...
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