Window function: lead/lag over user_id

Last updated: April 5, 2026

Quick Overview

Use window functions to compute running total partitioned by user_id.

Datadog

Data Manipulation (SQL/Python)

Data Scientist

Datadog

April 5, 2026

Data Scientist

Onsite

Data Manipulation (SQL/Python)

Hard

715 solved

Use window functions to compute running total partitioned by user_id.

This question from Datadog's Onsite 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

Aggregate functions and GROUP BY

Subqueries and correlated subqueries

Common Table Expressions (CTEs)

Index optimization and query performance

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 this if the data was spread across multiple databases?
How would you validate the correctness of your query results?
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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Sample Answer

Problem Understanding

The goal is to compute a running total of a specific metric (e.g., sales, clicks) partitioned by user_id. The data involved includes a table with at least the following columns: user_id, `timestam...

Approach

Identify the Table Structure: We'll assume there is a table named user_activity with columns user_id, timestamp, and amount.
Use Window Functions: We will utilize the SUM() fun...

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