The tricky part is being precise about what counts as outgoing.
Clarify the data model and constraints first, then propose an efficient solution that precomputes outgoing totals per account and maintains a sorted structure for top-N queries. Discuss trade-offs between batch processing and real-time updates, and handle ties by account ID.
Pro tip: Mention that you would maintain a min-heap of size N for top-N queries to achieve O(M log N) time, but also consider that if N is small and queries are frequent, a sorted list with binary search might be simpler and faster in practice.
Ask about the scale of data, frequency of queries, and whether the method should be real-time or can be batch. Confirm that only outgoing transfers and payments count, and ties are broken by account ID ascending.
Propose maintaining a map from account ID to total outgoing amount, updated on each transaction. For top-N queries, consider a min-heap of size N or a sorted list, depending on query frequency and N size.
If using a heap: iterate through all accounts, push onto a min-heap of size N, and pop when size exceeds N. Then extract and sort the heap to return results in descending order of total, with ties broken by account ID.
Discuss time and space complexity: O(M log N) per query with M accounts, or O(1) query if pre-sorted. Compare with alternative approaches like sorting all accounts O(M log M) or using a balanced BST for dynamic updates.
Handle accounts with zero outgoing, N larger than number of accounts, and concurrent updates. Suggest caching or incremental updates if queries are frequent.
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