Window function: rank over sessions

Last updated: October 15, 2025

Quick Overview

Use window functions to compute rank partitioned by user_id over sessions.

Walmart
Data Manipulation (SQL/Python)
Data Scientist
Walmart
October 15, 2025
Data Scientist
Technical Screen
Data Manipulation (SQL/Python)
Medium

685

15

2,515 solved


Use window functions to compute rank partitioned by user_id over sessions.

How to Approach This
  1. Clarify the schema and expected output format before writing queries.
  2. Use CTEs (WITH clauses) to break complex queries into readable steps.
  3. Consider window functions (ROW_NUMBER, RANK, LAG, LEAD) for ranking and sequential analysis.
  4. Watch for NULLs, duplicates, and edge cases in JOINs and GROUP BY.
  5. For pandas, prefer vectorized operations over row-by-row iteration.
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Problem Understanding

In this problem, we are tasked with analyzing user sessions data to compute a ranking of sessions for each user. The data involved likely includes fields such as user_id, session_id, `session_star...

Approach
  1. Identify the relevant columns from the session data: user_id, session_id, and potentially a metric for ranking such as session_start_time or duration.
  2. Use a window function to rank the s...

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