Window function: running total over user_id

Last updated: March 6, 2026

Quick Overview

Use window functions to compute rank partitioned by date.

xAI

Data Manipulation (SQL/Python)

Data Scientist

xAI

March 6, 2026

Data Scientist

Take-home Project

Data Manipulation (SQL/Python)

Hard

1,618 solved

Use window functions to compute rank partitioned by date.

xAI asks this during the Take-home Project 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

Date/time manipulation

Pandas vectorized operations and groupby

Data cleaning and transformation

NULL handling and COALESCE

Index optimization and query performance

JOIN types and when to use each

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 handle slowly changing dimensions in this scenario?
How would you validate the correctness of your query results?
How would you handle this if the data was spread across multiple databases?

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Practice SQL Problems

Sample Answer

Problem Understanding

The task requires us to compute a running total (or rank) over user IDs, partitioned by date. The data involved likely includes at least two columns: user_id and date. The output should provide th...

Approach

Identify Data Structure: Assume a table user_activity with columns user_id, activity_date, and activity_value (e.g., number of sessions).
Window Function: Use a window function ...

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