The QUARTER() function was the part I had to think about for a second.
Start by clarifying the schema and expected output, then outline a query that LEFT JOINs coins to transactions and uses conditional aggregation (CASE WHEN) to pivot quarterly sums. Emphasize that the join must preserve all coins, and that COALESCE or IFNULL handles NULLs for zero-transaction coins.
Pro tip: Mention that you'd verify the quarter boundaries and date handling (e.g., using EXTRACT(QUARTER FROM transaction_date)) and consider performance implications of aggregating before joining if the transactions table is large.
Confirm the columns in coins (e.g., coin_id, name) and transactions (e.g., coin_id, amount, transaction_date), and the exact output format (coin name, Q1-Q4 sums, total count, total amount).
Use a LEFT JOIN from coins to transactions to ensure all coins appear, even those with no transactions.
Use SUM(CASE WHEN EXTRACT(QUARTER FROM transaction_date) = 1 THEN amount ELSE 0 END) for each quarter, and COUNT(transaction_id) for total count, SUM(amount) for total amount.
Wrap aggregates in COALESCE to return 0 instead of NULL for coins with no transactions, and GROUP BY coin name (and coin_id if needed).
Consider pre-aggregating transactions by coin and quarter in a subquery to reduce join size, and mentally test edge cases like coins with no transactions and transactions spanning multiple years.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.