Top K Frequent Elements
Count, then select the k largest — a heap or bucket sort beats a full sort.
Approach
Tally frequencies with a hash map. To pick the top k, either push counts into a size-k min-heap (O(n log k)) or bucket-sort by frequency into indices 0..n and read from the top (O(n)). Bucket sort wins when k approaches n.
Time complexity
O(n)
Space complexity
O(n)
Common mistake
Sorting all counts (O(n log n)) when you only need the top k — a heap or buckets is asymptotically better.
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