I knew ROW_NUMBER() was the right move but fumbled for a second on whether to partition by just merchant_id or by both merchant_id and order_date.
Clarify the table schema and define 'first order' as the earliest order by timestamp (or order ID if timestamps tie). Use a window function like ROW_NUMBER() partitioned by merchant and date, ordered by order time, then filter to row number 1. Alternatively, use a correlated subquery or GROUP BY with MIN to get the earliest order per merchant per date.
Pro tip: Mention that if there are ties in order time, you need a deterministic tiebreaker (e.g., order_id) to ensure a single 'first' order; also discuss performance implications of window functions vs. self-joins on large datasets.
Ask about the exact columns, data types, and whether 'first order' means earliest by timestamp or by order ID. Confirm if ties are possible and how to handle them.
Decide between window functions (ROW_NUMBER), correlated subqueries, or GROUP BY with MIN. Window functions are typically most efficient and readable for this pattern.
Use ROW_NUMBER() OVER (PARTITION BY merchant_id, order_date ORDER BY order_time) to assign ranks, then filter WHERE rn = 1. Ensure order_date is derived from the timestamp if needed.
Consider ties, nulls, and time zones. Test with sample data to ensure each merchant-date returns exactly one row.
Discuss indexing on (merchant_id, order_date, order_time) and how the query scales. Mention alternative approaches and trade-offs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.