Optimize a slow query on clicks

Last updated: October 14, 2025

Quick Overview

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

Expedia
Data Manipulation (SQL/Python)
Data Scientist
Expedia
October 14, 2025
Data Scientist
Phone Screen
Data Manipulation (SQL/Python)
Medium

58

4

4,385 solved


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

This question from Expedia's Phone Screen tests practical data skills. The interviewer wants to see clean, efficient queries that handle edge cases like NULLs, duplicates, and large datasets.

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
JOIN types and when to use each
Subqueries and correlated subqueries
Pandas vectorized operations and groupby
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 optimize this query for a table with 100 million rows?
  • Can you rewrite this without using subqueries?
  • How would you handle slowly changing dimensions in this scenario?
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