Optimize a slow query on messages

Last updated: May 15, 2026

Quick Overview

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

Adobe
Data Manipulation (SQL/Python)
Data Scientist
Adobe
May 15, 2026
Data Scientist
Take-home Project
Data Manipulation (SQL/Python)
Medium

42

7

1,937 solved


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

This question from Adobe's Take-home Project 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
  • 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
Subqueries and correlated subqueries
Data cleaning and transformation
NULL handling and COALESCE
JOIN types and when to use each
Pandas vectorized operations and groupby
Aggregate functions and GROUP BY
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
  • What indexes would you create to support this query?
  • How would you optimize this query for a table with 100 million rows?
  • What would you do if this query needs to run every 5 minutes?
  • How would you validate the correctness of your query results?
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