Heap sort is a comparison based sorting technique based on Binary Heap data structure. It is similar to selection sort where we first find the maximum element and place the maximum element at the end. We repeat the same process for remaining element.
What is Binary Heap?
Let us first define a Complete Binary Tree. A complete binary tree is a binary tree in which every level, except possibly the last, is completely filled, and all nodes are as far left as possible (Source Wikipedia)
A Binary Heap is a Complete Binary Tree where items are stored in a special order such that value in a parent node is greater(or smaller) than the values in its two children nodes. The former is called as max heap and the latter is called min heap. The heap can be represented by binary tree or array.
Why array based representation for Binary Heap?
Since a Binary Heap is a Complete Binary Tree, it can be easily represented as array and array based representation is space efficient. If the parent node is stored at index I, the left child can be calculated by 2 * I + 1 and right child by 2 * I + 2 (assuming the indexing starts at 0).
Heap Sort Algorithm for sorting in increasing order:
1. Build a max heap from the input data.
2. At this point, the largest item is stored at the root of the heap. Replace it with the last item of the heap followed by reducing the size of heap by 1. Finally, heapify the root of tree.
3. Repeat above steps while size of heap is greater than 1.
How to build the heap?
Heapify procedure can be applied to a node only if its children nodes are heapified. So the heapification must be performed in the bottom up order.
Lets understand with the help of an example:
Input data: 4, 10, 3, 5, 1 4(0) / \ 10(1) 3(2) / \ 5(3) 1(4) The numbers in bracket represent the indices in the array representation of data. Applying heapify procedure to index 1: 4(0) / \ 10(1) 3(2) / \ 5(3) 1(4) Applying heapify procedure to index 0: 10(0) / \ 5(1) 3(2) / \ 4(3) 1(4) The heapify procedure calls itself recursively to build heap in top down manner.
Sorted array is 5 6 7 11 12 13
Here is previous C code for reference.
Heap sort is an in-place algorithm.
Its typical implementation is not stable, but can be made stable (See this)
Time Complexity: Time complexity of heapify is O(Logn). Time complexity of createAndBuildHeap() is O(n) and overall time complexity of Heap Sort is O(nLogn).
Heap sort algorithm has limited uses because Quicksort and Mergesort are better in practice. Nevertheless, the Heap data structure itself is enormously used. See Applications of Heap Data Structure
Other Sorting Algorithms on GeeksforGeeks/GeeksQuiz:
QuickSort, Selection Sort, Bubble Sort, Insertion Sort, Merge Sort, Heap Sort, QuickSort, Radix Sort, Counting Sort, Bucket Sort, ShellSort, Comb Sort, Pigeonhole Sort
Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.
- Iterative HeapSort
- Find the minimum number of rectangles left after inserting one into another
- Largest number not greater than N which can become prime after rearranging its digits
- Product of all Subsequences of size K except the minimum and maximum Elements
- Sum of elements in 1st array such that number of elements less than or equal to them in 2nd array is maximum
- Building Heap from Array
- Insertion and Deletion in Heaps
- Print 2-D co-ordinate points in ascending order followed by their frequencies
- Oracle Interview Experience (2 Years Experienced)
- Delete odd and even numbers at alternate step such that sum of remaining elements is minimized
- Split the array elements into strictly increasing and decreasing sequence
- Divide array into two parts with equal sum according to the given constraints
- Minimize the sum calculated by repeatedly removing any two elements and inserting their sum to the Array
- Shell-Metzner Sort