Optimize a slow query on users

Last updated: September 28, 2025

Quick Overview

A query on users is running slowly. Identify the bottleneck and optimize it.

Adobe
Data Manipulation (SQL/Python)
Data Scientist
Adobe
September 28, 2025
Data Scientist
Onsite
Data Manipulation (SQL/Python)
Medium

29

7

483 solved


A query on users is running slowly. Identify the bottleneck and optimize it.

Data manipulation questions at Adobe test your ability to work with real-world datasets. This Onsite question evaluates your SQL proficiency, understanding of data modeling, and ability to derive insights from raw data.

What the Interviewer Expects
  • Use advanced SQL features: window functions, CTEs, subqueries
  • Write efficient queries that avoid common performance pitfalls
  • Handle complex data transformations with multiple joins and aggregations
  • Discuss indexing strategy and query optimization
  • Address data quality issues: duplicates, missing values, outliers
Key Topics to Cover
Date/time manipulation
NULL handling and COALESCE
Aggregate functions and GROUP BY
Subqueries and correlated subqueries
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
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.
Possible Follow-up Questions
  • How would you validate the correctness of your query results?
  • What indexes would you create to support this query?
  • What would you do if this query needs to run every 5 minutes?
  • How would you optimize this query for a table with 100 million rows?
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