Binary Heap
Binary heap is the fundamental type of heap that forms the basis for many other heap structures. It is a complete binary tree with a unique property – the value of each node is either greater than or equal to (max-heap) or less than or equal to (min-heap) the values of its children. Binary heaps are often implemented as arrays, allowing for efficient manipulation and access.
- Characteristics:
- Efficiently represented as an array.
- Parent’s value is greater than or equal to (max heap) or less than or equal to (min heap) children’s values.
- Uses:
- Priority queues.
- Heap sort algorithm.
- Applications:
- Dijkstra’s shortest path algorithm.
- Huffman coding for data compression.
Problem | Description |
---|---|
Heap Sort | Sort an array using binary heap operations. |
Priority Queue Operations | Implement basic operations like insertion and extraction in a binary heap. |
Kth Smallest Element | Find the Kth smallest element in an array efficiently using a binary heap. |
Merge Two Heaps | Efficiently merge two binary heaps into a single heap. |
Heapify an Array | Convert an array into a binary heap efficiently. |
Types of Heap Data Structure
Different types of heap data structures include fundamental types like min heap and max heap, binary heap and many more. In this post, we will look into their characteristics, and their use cases. Understanding the characteristics and use cases of these heap data structures helps in choosing the most suitable one for a particular algorithm or application. Each type of heap has its own advantages and trade-offs, and the choice depends on the specific requirements of the problem at hand.
Table of Content
- 1. Binary Heap
- 2. Min Heap
- 3. Max Heap
- 4. Binomial Heap
- 5. Fibonacci Heap
- 6. D-ary Heap
- 7. Pairing Heap
- 8. Leftist Heap
- 9. Skew Heap
- 10. B-Heap
- Comparison between different types of Heap