Trending September 2023 # Heap Sort In Data Structure # Suggested October 2023 # Top 17 Popular | Lanphuongmhbrtower.com

# Trending September 2023 # Heap Sort In Data Structure # Suggested October 2023 # Top 17 Popular

You are reading the article Heap Sort In Data Structure updated in September 2023 on the website Lanphuongmhbrtower.com. We hope that the information we have shared is helpful to you. If you find the content interesting and meaningful, please share it with your friends and continue to follow and support us for the latest updates. Suggested October 2023 Heap Sort In Data Structure

Introduction to Heap sort in data structure

Hadoop, Data Science, Statistics & others

Working of heapsort

The heap sort technique involves the comparison that is made between the nodes, and it uses the technique of data structure called a binary heap. The heap sort works similar to the selection sort, where we find the smallest element and then the smallest element is placed at the beginning. After that, the same process is carried out for the remaining nodes or elements of the supplied array.

The most used data structure is the binary heap. To understand this, we first need to know what is a complete binary tree has all the levels completely occupied with an allowed exception of the last level. Also, all the elements or nodes in the complete binary tree are placed as left as possible. The binary heap is also one type of special case of a complete binary tree in which the parent node will have the value either greater than both of its child nodes or smaller than both of its child nodes. In the first case, it is called a max heap, while in the latter case, it is referred to as the min-heap. The representation of the heap is done using the binary tree or the array.

Steps for hear sort

The algorithm of heap sort involves the following steps –

Whatever the supplied input array of data is done, create a max heap from that data.

Consider that the largest value is stored at the root node of the heap for now. After this, keep on replacing the root node with the last node and decreasing the heap’s size by 1. The last step will be to prepare the heap (heapify) for the root of the tree.

Follow step 2 unless the heap size is greater than 1.

Note that we can perform the heapify process for a particular node only if all the child nodes of that node are heaped. Hence, while doing this process, the bottom-up approach is followed.

Consider the following heap shown in the diagram –

The index of each node is represented in parenthesis after the value of the node. When we carry out the heaping process on the node with index 1, the tree will look as follows –

We have to keep on repeating the above process of creating the heap recursively in the top-down approach to create a sorted heap out of it.

Example of Heap sort in data structure

Let us consider an example of how the heap sort actually works using the C++ programming language.

The output of the execution of the above program in C++ language is as shown below –

Time complexity

The time complexity of the heap sort is O(nlogn). On the other hand, when the individual heapify process of creating a new heap with a particular node is considered, then the time complexity for it is O(logn).

Conclusion – Heap sort in data structure

The heap sort works internally in the binary heap, which is a completely balanced binary tree that either has the largest value or the smallest value at its node. Thus, the heapify process is carried out recursively to get the sorted array, as shown in the above example.

Recommended Articles

This is a guide to Heap sort in data structure. Here we discuss the working of heap sort along with its implementation in the C++ language. You may also look at the following articles to learn more –

You're reading Heap Sort In Data Structure

Update the detailed information about Heap Sort In Data Structure on the Lanphuongmhbrtower.com website. We hope the article's content will meet your needs, and we will regularly update the information to provide you with the fastest and most accurate information. Have a great day!