Break the problem into two stages: first, compute the total borrowed duration per book by joining copies and checkouts, filtering for completed checkouts (return_date IS NOT NULL), and summing the day-level date differences; second, filter books with more than 10 distinct copies, sort by total duration descending and book_id ascending, and limit to top 3. Use a subquery or CTE to aggregate durations and counts separately, then join or filter as needed.
Pro tip: Explicitly state your assumptions about date difference calculation (e.g., DATEDIFF(day, checkout_date, return_date) in SQL Server or return_date - checkout_date in PostgreSQL) and clarify that 'completed checkouts' means return_date is not null. Also, mention that you would validate the query with edge cases like books with exactly 10 copies or ties in duration.
Confirm the definition of 'total borrowed duration' (sum of day-level differences for completed checkouts only) and 'more than 10 distinct copies' (count of distinct copy_id per book). Ask about date difference semantics (inclusive/exclusive) and handling of NULL return dates.
Join copies and checkouts on copy_id, filter for completed checkouts (return_date IS NOT NULL), and compute the sum of date differences per book_id. Use a CTE or subquery to isolate this aggregation.
From the copies table, count distinct copy_id per book_id to identify books with more than 10 distinct copies. This can be done in a separate CTE or combined with the duration aggregation.
Join the duration and copy-count results, filter for books with >10 distinct copies, then order by total duration descending and book_id ascending. Limit to top 3.
Check for potential performance issues (e.g., large joins) and suggest indexes on copy_id and book_id. Discuss alternative approaches like window functions if needed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.