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, 2025Data 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
- 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 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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Practice SQL ProblemsSample Answer
Problem Understanding
The query involves a dataset containing user information, which may include user IDs, timestamps of their activities, and other relevant details. The goal is to optimize a slow-running query that aggr...
Approach
- Identify the Bottleneck: First, run an EXPLAIN plan on the existing query to see where the performance issues arise (e.g., slow joins, full table scans).
- **Use Common Table Expressions (CT...
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