Optimize a slow query on clicks

Last updated: September 17, 2025

Quick Overview

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

HubSpot
Data Manipulation (SQL/Python)
Data Scientist
HubSpot
September 17, 2025
Data Scientist
Phone Screen
Data Manipulation (SQL/Python)
Medium

118

6

211 solved


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

HubSpot asks this during the Phone Screen because data engineering skills are critical for the role. You should be comfortable with complex joins, window functions, CTEs, and performance optimization.

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
Aggregate functions and GROUP BY
JOIN types and when to use each
Date/time manipulation
Common Table Expressions (CTEs)
NULL handling and COALESCE
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
  • Can you rewrite this without using subqueries?
  • 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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