Join messages and impressions to find rolling 7-day average
Last updated: April 2, 2026
Quick Overview
Write a query joining messages and orders to produce the combined rolling 7-day average.
MongoDB
April 2, 202616
3
1,873 solved
Write a query joining messages and orders to produce the combined rolling 7-day average.
Data manipulation questions at MongoDB test your ability to work with real-world datasets. This Onsite question evaluates your SQL proficiency, understanding of data modeling, and ability to derive insights from raw data.
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
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 handle slowly changing dimensions in this scenario?
- Can you rewrite this without using subqueries?
- How would you handle this if the data was spread across multiple databases?
- How would you optimize this query for a table with 100 million rows?
Sharpen Your Skills on Codemia
Practice similar problems with our interactive workspace, get AI feedback, and track your progress.
Practice SQL ProblemsSample Answer
Approach
Break the problem into logical steps before writing SQL. Think about: 1. What tables do I need to join and on which keys? 2. What filtering (WHERE) d...
Solution Pattern
```sql WITH filtered_data AS ( SELECT * FROM main_table WHERE condition = 'value' AND date_col >= '2024-01-01' ), aggregated AS ( SELECT ...