Optimize a slow query on messages
Last updated: December 29, 2025
Quick Overview
A query on messages is running slowly. Identify the bottleneck and optimize it.
Instacart
December 29, 202510
6
755 solved
A query on messages is running slowly. Identify the bottleneck and optimize it.
This question from Instacart's Technical 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
- 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
- How would you validate the correctness of your query results?
- Can you rewrite this without using subqueries?
- How would you handle this if the data was spread across multiple databases?
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Practice SQL ProblemsSample Answer
Problem Understanding
In this scenario, we are tasked with optimizing a slow SQL query that retrieves messages from a database. The messages table likely contains columns like message_id, user_id, created_at, and pos...
Approach
To optimize the query, we can follow these steps:
- Analyze the Current Query: Review the existing SQL query to identify performance bottlenecks, such as inefficient JOINs, WHERE clause filters...
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