Concept of Heaps Explained in 1 Minute | Heap Data Structures | Priority Queue | Min Heap #shorts
In data structures and algorithms, a heap is a specialized binary tree-based data structure where each parent node has a value less than or equal to (in a ma...
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In data structures and algorithms, a heap is a specialized binary tree-based data structure where each parent node has a value less than or equal to (in a max heap) or greater than or equal to (in a min heap) the values of its children.
Heaps are commonly used to implement priority queues, where the highest (or lowest) priority element can be efficiently retrieved. The shape property ensures that the tree is a complete binary tree, while the heap property ensures that the priority relationship between parent and child nodes is maintained. Operations such as insertion, deletion, and peeking at the highest (or lowest) priority element can be performed efficiently in logarithmic time complexity, making heaps a fundamental tool for various applications in computer science.
Heaps are efficient tree-based data structures used in computer science primarily for priority queue operations. They adhere to two key properties: the shape property, ensuring the tree remains complete, and the heap property, where the priority relationship between parent and child nodes is maintained. Heaps can be implemented as arrays, with the root node at index 0, and each element's children at indices 2i+1 and 2i+2 for a node at index i. This structure allows for logarithmic time complexity operations such as insertion, deletion, and finding the highest (or lowest) priority element, making heaps indispensable for tasks requiring efficient handling of prioritized data.
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