Optimize a slow query on orders
Last updated: May 3, 2026
Quick Overview
A query on orders is running slowly. Identify the bottleneck and optimize it.
CrowdStrike
Data Manipulation (SQL/Python)
Data Scientist
CrowdStrike
May 3, 2026Data Scientist
Phone Screen
Data Manipulation (SQL/Python)
Medium
598
7
4,292 solved
A query on orders is running slowly. Identify the bottleneck and optimize it.
This question from CrowdStrike'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
NULL handling and COALESCE
Date/time manipulation
Data cleaning and transformation
Pandas vectorized operations and groupby
Common Table Expressions (CTEs)
Aggregate functions and GROUP BY
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
- What indexes would you create to support this query?
- How would you handle this if the data was spread across multiple databases?
- Can you rewrite this without using subqueries?
- How would you validate the correctness of your query results?
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Practice SQL ProblemsSample Answer
Problem Understanding
The query focuses on the 'orders' table, which contains various fields such as order_id, customer_id, order_date, total_amount, and status. The goal is to generate a report that summarizes the total s...
Approach
- Identify the required fields: We need customer_id, total sales (sum of total_amount), and order count.
- Use a Common Table Expression (CTE): Create a CTE to filter orders by date and stat...
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