Optimize a slow query on orders
Last updated: December 1, 2025
Quick Overview
A query on orders is running slowly. Identify the bottleneck and optimize it.
HubSpot
December 1, 20250
6
2,938 solved
A query on orders is running slowly. Identify the bottleneck and optimize it.
Data manipulation questions at HubSpot test your ability to work with real-world datasets. This Technical Screen 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
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 handle this if the data was spread across multiple databases?
- What would you do if this query needs to run every 5 minutes?
- What indexes would you create to support this query?
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Practice SQL ProblemsSample Answer
Problem Understanding
The query involves an 'orders' table that likely contains information about customer orders, such as order ID, customer ID, order date, total amount, and order status. The goal is to optimize a query ...
Approach
To build the optimized query, I will follow these steps:
- Identify the joins needed: If there are multiple tables involved (like customers and orders), determine which fields to join on (e.g., c...
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