Min Heap in Java

A Min-Heap is a complete binary tree in which the value in each internal node is greater than or equal to the values in the children of that node.
Mapping the elements of a heap into an array is trivial: if a node is stored a index k, then its left child is stored at index 2k + 1 and its right child at index 2k + 2.

Example of Min Heap:

            5                      13
         /      \               /       \  
       10        15           16         31 
      /                      /  \        /  \
    30                     41    51    100   41

How is Min Heap represented?
A Min Heap is a Complete Binary Tree. A Min heap is typically represented as an array. The root element will be at Arr[0]. For any ith node, i.e., Arr[i]:

  • Arr[(i -1) / 2] returns its parent node.
  • Arr[(2 * i) + 1] returns its left child node.
  • Arr[(2 * i) + 2] returns its right child node.

Operations on Min Heap:

  1. getMin(): It returns the root element of Min Heap. Time Complexity of this operation is O(1).
  2. extractMin(): Removes the minimum element from MinHeap. Time Complexity of this Operation is O(Log n) as this operation needs to maintain the heap property (by calling heapify()) after removing root.
  3. insert(): Inserting a new key takes O(Log n) time. We add a new key at the end of the tree. If new key is larger than its parent, then we don’t need to do anything. Otherwise, we need to traverse up to fix the violated heap property.

Below is the implementation of Min Heap in Java



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// Java implementation of Min Heap
public class MinHeap {
    private int[] Heap;
    private int size;
    private int maxsize;
  
    private static final int FRONT = 1;
  
    public MinHeap(int maxsize)
    {
        this.maxsize = maxsize;
        this.size = 0;
        Heap = new int[this.maxsize + 1];
        Heap[0] = Integer.MIN_VALUE;
    }
  
    // Function to return the position of 
    // the parent for the node currently 
    // at pos
    private int parent(int pos)
    {
        return pos / 2;
    }
  
    // Function to return the position of the 
    // left child for the node currently at pos
    private int leftChild(int pos)
    {
        return (2 * pos);
    }
  
    // Function to return the position of 
    // the right child for the node currently 
    // at pos
    private int rightChild(int pos)
    {
        return (2 * pos) + 1;
    }
  
    // Function that returns true if the passed 
    // node is a leaf node
    private boolean isLeaf(int pos)
    {
        if (pos >= (size / 2) && pos <= size) {
            return true;
        }
        return false;
    }
  
    // Function to swap two nodes of the heap
    private void swap(int fpos, int spos)
    {
        int tmp;
        tmp = Heap[fpos];
        Heap[fpos] = Heap[spos];
        Heap[spos] = tmp;
    }
  
    // Function to heapify the node at pos
    private void minHeapify(int pos)
    {
  
        // If the node is a non-leaf node and greater
        // than any of its child
        if (!isLeaf(pos)) {
            if (Heap[pos] > Heap[leftChild(pos)]
                || Heap[pos] > Heap[rightChild(pos)]) {
  
                // Swap with the left child and heapify
                // the left child
                if (Heap[leftChild(pos)] < Heap[rightChild(pos)]) {
                    swap(pos, leftChild(pos));
                    minHeapify(leftChild(pos));
                }
  
                // Swap with the right child and heapify 
                // the right child
                else {
                    swap(pos, rightChild(pos));
                    minHeapify(rightChild(pos));
                }
            }
        }
    }
  
    // Function to insert a node into the heap
    public void insert(int element)
    {
        Heap[++size] = element;
        int current = size;
  
        while (Heap[current] < Heap[parent(current)]) {
            swap(current, parent(current));
            current = parent(current);
        }
    }
  
    // Function to print the contents of the heap
    public void print()
    {
        for (int i = 1; i <= size / 2; i++) {
            System.out.print(" PARENT : " + Heap[i]
                     + " LEFT CHILD : " + Heap[2 * i]
                   + " RIGHT CHILD :" + Heap[2 * i + 1]);
            System.out.println();
        }
    }
  
    // Function to build the min heap using 
    // the minHeapify
    public void minHeap()
    {
        for (int pos = (size / 2); pos >= 1; pos--) {
            minHeapify(pos);
        }
    }
  
    // Function to remove and return the minimum
    // element from the heap
    public int remove()
    {
        int popped = Heap[FRONT];
        Heap[FRONT] = Heap[size--];
        minHeapify(FRONT);
        return popped;
    }
  
    // Driver code
    public static void main(String[] arg)
    {
        System.out.println("The Min Heap is ");
        MinHeap minHeap = new MinHeap(15);
        minHeap.insert(5);
        minHeap.insert(3);
        minHeap.insert(17);
        minHeap.insert(10);
        minHeap.insert(84);
        minHeap.insert(19);
        minHeap.insert(6);
        minHeap.insert(22);
        minHeap.insert(9);
        minHeap.minHeap();
  
        minHeap.print();
        System.out.println("The Min val is " + minHeap.remove());
    }
}

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Output:

The Min Heap is 
 PARENT : 3 LEFT CHILD : 5 RIGHT CHILD :6
 PARENT : 5 LEFT CHILD : 9 RIGHT CHILD :84
 PARENT : 6 LEFT CHILD : 19 RIGHT CHILD :17
 PARENT : 9 LEFT CHILD : 22 RIGHT CHILD :10
The Min val is 3

Using Library Functions
We use PriorityQueue class to implement Heaps in Java. By default Min Heap is implemented by this class.

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// Java program to demonstrate working of PriorityQueue
import java.util.*;
  
class Example {
  
    // Driver code
    public static void main(String args[])
    {
        // Creating empty priority queue
        PriorityQueue<Integer> pQueue = new PriorityQueue<Integer>();
  
        // Adding items to the pQueue using add()
        pQueue.add(10);
        pQueue.add(30);
        pQueue.add(20);
        pQueue.add(400);
  
        // Printing the most priority element
        System.out.println("Head value using peek function:" + pQueue.peek());
  
        // Printing all elements
        System.out.println("The queue elements:");
        Iterator itr = pQueue.iterator();
        while (itr.hasNext())
            System.out.println(itr.next());
  
        // Removing the top priority element (or head) and
        // printing the modified pQueue using poll()
        pQueue.poll();
        System.out.println("After removing an element "
                           + "with poll function:");
        Iterator<Integer> itr2 = pQueue.iterator();
        while (itr2.hasNext())
            System.out.println(itr2.next());
  
        // Removing 30 using remove()
        pQueue.remove(30);
        System.out.println("after removing 30 with"
                           + " remove function:");
        Iterator<Integer> itr3 = pQueue.iterator();
        while (itr3.hasNext())
            System.out.println(itr3.next());
  
        // Check if an element is present using contains()
        boolean b = pQueue.contains(20);
        System.out.println("Priority queue contains 20 "
                           + "or not?: " + b);
  
        // Getting objects from the queue using toArray()
        // in an array and print the array
        Object[] arr = pQueue.toArray();
        System.out.println("Value in array: ");
        for (int i = 0; i < arr.length; i++)
            System.out.println("Value: " + arr[i].toString());
    }
}

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Output:

Head value using peek function:10
The queue elements:
10
30
20
400
After removing an element with poll function:
20
30
400
after removing 30 with remove function:
20
400
Priority queue contains 20 or not?: true
Value in array: 
Value: 20
Value: 400


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