Optimize a slow query on sessions

Last updated: May 6, 2026

Quick Overview

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

HubSpot
Data Manipulation (SQL/Python)
Data Scientist
HubSpot
May 6, 2026
Data Scientist
Take-home Project
Data Manipulation (SQL/Python)
Hard

20

5

3,982 solved


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

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

What the Interviewer Expects
  • Solve complex analytical problems with elegant, readable SQL
  • Optimize queries for large-scale datasets with partitioning and indexing
  • Use recursive CTEs, lateral joins, and advanced window functions
  • Design the data model alongside the query solution
  • Discuss trade-offs between SQL and programmatic approaches (Python/pandas)
  • Consider the operational aspects: query scheduling, incremental processing
Key Topics to Cover
Aggregate functions and GROUP BY
Subqueries and correlated subqueries
Date/time manipulation
JOIN types and when to use each
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?
  • How would you optimize this query for a table with 100 million rows?
  • How would you handle slowly changing dimensions in this scenario?
  • What indexes would you create to support this query?
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