Optimize a slow query on products

Last updated: January 31, 2026

Quick Overview

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

Anduril
Data Manipulation (SQL/Python)
Data Scientist
Anduril
January 31, 2026
Data Scientist
Phone Screen
Data Manipulation (SQL/Python)
Medium

45

0

872 solved


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

Data manipulation questions at Anduril test your ability to work with real-world datasets. This Phone 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
Aggregate functions and GROUP BY
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
JOIN types and when to use each
Common Table Expressions (CTEs)
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 handle slowly changing dimensions in this scenario?
  • 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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