Window function: lead/lag over user_id
Last updated: October 9, 2025
Quick Overview
Use window functions to compute running total partitioned by user_id.
Palantir
Data Manipulation (SQL/Python)
Data Scientist
Palantir
October 9, 2025Data Scientist
Phone Screen
Data Manipulation (SQL/Python)
Hard
239
9
1,459 solved
Use window functions to compute running total partitioned by user_id.
This question from Palantir's Phone 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
- 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
Data cleaning and transformation
JOIN types and when to use each
Subqueries and correlated subqueries
Pandas vectorized operations and groupby
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 optimize this query for a table with 100 million rows?
- Can you rewrite this without using subqueries?
- How would you handle this if the data was spread across multiple databases?
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Practice SQL ProblemsSample Answer
Problem Understanding
The dataset involved in this problem consists of a table (let’s call it user_activity) containing columns such as user_id, activity_date, and activity_value. The requirement is to compute a ru...
Approach
- Identify Data Types: Ensure that
activity_dateis in DATE format andactivity_valueis numeric. - Use Window Functions: Leverage the
SUM()window function combined with `PARTITION B...
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