Join transactions and clicks to find DAU/MAU ratio
Last updated: February 13, 2026
Quick Overview
Write a query joining transactions and sessions to produce the combined DAU/MAU ratio.
Airbnb
Data Manipulation (SQL/Python)
Data Scientist
Airbnb
February 13, 2026Data Scientist
Onsite
Data Manipulation (SQL/Python)
Hard
46
6
966 solved
Write a query joining transactions and sessions to produce the combined DAU/MAU ratio.
Airbnb asks this during the Onsite because data engineering skills are critical for the role. You should be comfortable with complex joins, window functions, CTEs, and performance optimization.
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
Date/time manipulation
Aggregate functions and GROUP BY
Pandas vectorized operations and groupby
Common Table Expressions (CTEs)
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?
- How would you validate the correctness of your query results?
- What would you do if this query needs to run every 5 minutes?
- How would you optimize this query for a table with 100 million rows?
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Practice SQL ProblemsSample Answer
Problem Understanding
To calculate the Daily Active Users (DAU) and Monthly Active Users (MAU) ratio for Airbnb, we need to join two datasets: transactions and sessions. The transactions table contains records of com...
Approach
- Identify Key Fields: Determine the necessary fields from both tables. We will primarily need user IDs and timestamps (session date for DAU and transactions date for MAU).
- **Aggregate Unique ...
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