Clarify the join key and the speed formula, then propose a hash join to merge the datasets on animal name. Filter for animals with exactly two walking legs, compute speed using both leg and tail fields, and sort the results in descending order.
Pro tip: Discuss trade-offs: a hash join is O(n+m) time and O(n) space, but if data is already sorted or memory is constrained, a sort-merge join might be preferable. Also, confirm the speed formula and edge cases like missing data or ties.
Ask about the join key (likely animal name), the exact speed formula (e.g., speed = leg_count * tail_length), and how to handle missing or inconsistent data. Confirm that 'walking leg count' is the field to filter on for two-legged animals.
Propose using a hash map to index one dataset by name for efficient lookups, or a sort-merge join if data is sorted. Consider memory constraints and whether to load the smaller dataset into memory.
Iterate through the datasets, join on name, and filter for animals where walking leg count equals 2. Compute speed using the derived formula from both leg and tail fields.
Collect the speeds into a list and sort in descending order. If multiple animals have the same speed, decide on a tie-breaking rule (e.g., alphabetical by name) or mention that it's unspecified.
State the time and space complexity (e.g., O(n+m) for hash join, O(k log k) for sorting). Discuss edge cases: missing names, null values, negative speeds, and large datasets that don't fit in memory.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.