Jumped straight to a hash map keyed on (account_id, currency) and that part was fine.
Start by clarifying the problem constraints and edge cases, then outline a solution that sorts transactions chronologically and uses a hash map to aggregate balances per (account_id, currency). After processing, filter out zero balances and sort the results by account_id and currency.
Pro tip: Mention that you would use a composite key (account_id, currency) for the hash map and discuss how to handle floating-point precision for amounts, perhaps using integer cents or a decimal library.
Ask about input size, whether timestamps are unique, how to handle multiple transactions with the same timestamp, and the expected output format. Confirm that amounts can be positive or negative and that zero balances should be excluded.
Decide to sort transactions by timestamp (if not already sorted) and use a hash map with a composite key (account_id, currency) to accumulate balances. Consider using a balanced tree or sorting the keys at the end for ordered output.
Iterate through the sorted transactions, updating the balance for each (account_id, currency) pair by adding the amount. Ensure that the order of processing respects chronological order.
Remove any entries with a balance of exactly zero, then sort the remaining entries by account_id and then by currency. Return the list of (account_id, currency, balance) tuples.
State the time complexity: O(n log n) due to sorting, and space complexity O(n) for the hash map. Discuss potential optimizations if the input is already sorted or if we can use a streaming approach.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.