I went straight to conditional aggregation with CASE inside MIN and MAX, which was the right call.
Use conditional aggregation with MIN(CASE WHEN status = 'active' THEN date END) and MAX(CASE WHEN status = 'inactive' THEN date END), grouped by user. This single-pass approach is efficient and avoids multiple subqueries or joins.
Pro tip: Mention that this pattern scales well because it scans the table once, and note that if the table is partitioned by date, you can add a WHERE clause to limit the scan to relevant partitions.
Confirm the table name, column names (user_id, date, status), and that status only has 'active' and 'inactive' values. Ask if there are any edge cases like users with no active or no inactive records.
Decide between conditional aggregation (single query with CASE) versus separate subqueries for active and inactive dates. Conditional aggregation is more efficient and easier to read.
Use MIN(CASE WHEN status = 'active' THEN date END) AS earliest_active_date and MAX(CASE WHEN status = 'inactive' THEN date END) AS latest_inactive_date, grouped by user_id.
Explain that users without active or inactive records will have NULL for the respective column. Optionally, use COALESCE or filter to exclude such users if needed.
Mention indexing on (user_id, status, date) and partition pruning if the table is partitioned by date. Also note that the query can be extended to include other statuses.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.