Optimize a slow query on transactions
Last updated: July 16, 2025
Quick Overview
A query on transactions is running slowly. Identify the bottleneck and optimize it.
Mastercard
July 16, 202533
7
4,177 solved
A query on transactions is running slowly. Identify the bottleneck and optimize it.
Data manipulation questions at Mastercard 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
- Write syntactically correct SQL with proper JOIN and WHERE clauses
- Use GROUP BY and aggregate functions appropriately
- Handle NULL values correctly in your queries
- Explain the query execution plan at a high level
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
- Can you rewrite this without using subqueries?
- What indexes would you create to support this query?
- How would you handle slowly changing dimensions in this scenario?
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