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
Data Manipulation (SQL/Python)
Data Scientist
MongoDB
April 2, 2026
Data Scientist
Onsite
Data Manipulation (SQL/Python)
Medium

16

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
Aggregate functions and GROUP BY
JOIN types and when to use each
Pandas vectorized operations and groupby
Subqueries and correlated subqueries
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
  • 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?
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