Write a query to find rolling 7-day average from messages
Last updated: March 28, 2026
Quick Overview
Write a SQL query to calculate rolling 7-day average from the messages table, considering nulls and duplicates.
CrowdStrike
March 28, 2026282
3
3,950 solved
Write a SQL query to calculate rolling 7-day average from the messages table, considering nulls and duplicates.
CrowdStrike 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
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?
- How would you handle slowly changing dimensions in this scenario?
- Can you rewrite this without using subqueries?
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Practice SQL ProblemsSample Answer
Problem Understanding
The task is to calculate the rolling 7-day average of messages from the 'messages' table. This table likely contains a 'timestamp' column indicating when each message was sent and possibly a 'message_...
Approach
- Identify Relevant Columns: Focus on the timestamp of the messages. We will assume a 'message_id' column exists for counting unique messages.
- Group by Date: Create a daily summary of the...
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