Optimize a slow query on transactions

Last updated: February 19, 2026

Quick Overview

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

Oracle
Data Manipulation (SQL/Python)
Data Scientist
Oracle
February 19, 2026
Data Scientist
Take-home Project
Data Manipulation (SQL/Python)
Hard

1

7

3,930 solved


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

Data manipulation questions at Oracle 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
  • Solve complex analytical problems with elegant, readable SQL
  • Optimize queries for large-scale datasets with partitioning and indexing
  • Use recursive CTEs, lateral joins, and advanced window functions
  • Design the data model alongside the query solution
  • Discuss trade-offs between SQL and programmatic approaches (Python/pandas)
  • Consider the operational aspects: query scheduling, incremental processing
Key Topics to Cover
Index optimization and query performance
NULL handling and COALESCE
Window functions (ROW_NUMBER, RANK, LAG, LEAD)
Subqueries and correlated subqueries
Common Table Expressions (CTEs)
JOIN types and when to use each
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
  • What would you do if this query needs to run every 5 minutes?
  • Can you rewrite this without using subqueries?
  • How would you optimize this query for a table with 100 million rows?
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