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The optimal approach uses SQL window functions such as ROW_NUMBER() to identify consecutive login dates for each user. By grouping rows based on the difference between the login date and row number, you can detect streaks and filter those with at least five consecutive days.
Yes, variations of consecutive activity or streak detection problems are common in data and SQL interviews at large tech companies. They test your ability to work with window functions, grouping logic, and time-based data analysis.
Window functions are particularly useful for this problem. Functions like ROW_NUMBER() combined with ORDER BY allow you to analyze sequential records and detect continuous date ranges efficiently.
The common technique is the "date minus row number" grouping trick. It groups consecutive dates into the same bucket, making it easy to count streak lengths using GROUP BY and HAVING clauses.