The question itself is pretty clean once you pin down the requirements.
Clarify the requirements first: what defines a group, which aggregation function to use, sort direction, and tie-breaking rules. Then propose an efficient algorithm using a hash map to aggregate and sort the results, discussing time and space complexity. Finally, walk through an example and consider edge cases like empty input or ties.
Pro tip: Explicitly state your assumptions about tie-breaking and sort direction, and ask the interviewer if they have a preference—this shows attention to detail and avoids ambiguity. Also, mention that you would use a stable sort or a custom comparator to handle ties consistently.
Ask questions to confirm the grouping key, aggregation function (count, sum, average, etc.), sort order (ascending/descending), and tie-breaking rules (e.g., alphabetical by key).
Use a hash map to group entries by key and compute the aggregate. Then extract the groups and sort them using a custom comparator that considers the aggregate and tie-breaker.
State the time complexity: O(n) for aggregation and O(k log k) for sorting, where n is number of entries and k is number of groups. Space complexity is O(k).
Choose a small example to demonstrate the process, showing how groups are formed, aggregates computed, and sorting applied with tie-breaking.
Mention handling of empty input, all entries in one group, ties, and potential optimizations like using a heap for top-k if only top results are needed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.