A heap is a complete binary tree where each parent orders before its children, giving O(log n) insert and remove and O(1) peek at the min or max. Priority queues are commonly implemented with heaps.
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A heap is a complete binary tree where each parent orders before its children, giving O(log n) insert and remove and O(1) peek at the min or max. Priority queues are commonly implemented with heaps.
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A min heap keeps the smallest element at the root; a max heap keeps the largest.
Insert and extract are O(log n) via sift-up and sift-down; peeking the top is O(1).
Top-K elements, merging sorted lists, and scheduling problems often use heaps.
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Use a heap for top-K problems, streaming medians, scheduling, and anytime you repeatedly need the min or max.
Insert and extract are O(log n); peeking the top element is O(1).
