My first instinct was to just filter by year and group by coin, which got me the totals fine.
Use a LEFT JOIN from the coins table to the transactions table, filtering transactions to the given year in the join condition. Then use conditional aggregation with CASE statements to sum amounts per quarter, count transactions, and sum total amounts, ensuring coins with no transactions show zeros via COALESCE or COALESCE(SUM(...), 0).
Pro tip: Always put the year filter in the JOIN condition, not the WHERE clause, to preserve coins with no transactions in that year. Also, use COALESCE or IFNULL to handle NULLs from the LEFT JOIN and return zeros as required.
Identify the columns in coins (e.g., coin_id) and transactions (e.g., coin_id, transaction_date, amount). Clarify that the output should have one row per coin, with quarterly sums, total count, and total amount for a specific year, including coins with no transactions.
Use a LEFT JOIN from coins to transactions to keep all coins. Place the year filter in the ON clause of the join to avoid filtering out coins with no transactions in that year.
Use CASE statements inside SUM to calculate quarterly amounts: SUM(CASE WHEN QUARTER(transaction_date) = 1 THEN amount ELSE 0 END) AS Q1, etc. Also compute COUNT(transaction_id) for total count and SUM(amount) for total amount.
Wrap aggregate results with COALESCE(..., 0) to convert NULLs to zeros. Group by coin_id (and any other coin attributes if needed).
Assemble the full SQL query, ensuring correct syntax and aliases. Mentally test with sample data to confirm coins with no transactions appear with zeros.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.