Answers for "heap implementation java"

heap in java

In Java PriorityQueue can be used as a Heap.

Min Heap
PriorityQueue<Integer> minHeap = new PriorityQueue<>();


Max Heap:
PriorityQueue<Integer> maxHeap = new PriorityQueue<>(Comparator.reverseOrder());

use Java NetBeans to write code to implement the list [5, 3, 17, 10, 84, 19, 6, 22, 9] in a Max Heap data structure. For each parent node, display the left and right child of the node.

The Max Heap is 
 PARENT : 52 LEFT CHILD : 21 RIGHT CHILD :23
 PARENT : 21 LEFT CHILD : 15 RIGHT CHILD :13
 PARENT : 23 LEFT CHILD : 7 RIGHT CHILD :16
 PARENT : 15 LEFT CHILD : 5 RIGHT CHILD :9
The max val is 52

heaps in java

public class BinaryHeap {
     
    private static final int d= 2;
    private int[] heap;
    private int heapSize;
     
    /**
     * This will initialize our heap with default size. 
     */
    public BinaryHeap(int capacity){
        heapSize = 0;
        heap = new int[ capacity+1];
        Arrays.fill(heap, -1);
         
    }
     
    /**
     *  This will check if the heap is empty or not
     *  Complexity: O(1)
     */
    public boolean isEmpty(){
        return heapSize==0;
    }
     
    /**
     *  This will check if the heap is full or not
     *  Complexity: O(1)
     */
    public boolean isFull(){
        return heapSize == heap.length;
    }
     
     
    private int parent(int i){
        return (i-1)/d;
    }
     
    private int kthChild(int i,int k){
        return d*i  +k;
    }
     
    /**
     *  This will insert new element in to heap
     *  Complexity: O(log N)
     *  As worst case scenario, we need to traverse till the root
     */
    public void insert(int x){
        if(isFull())
            throw new NoSuchElementException("Heap is full, No space to insert new element");
        heap[heapSize++] = x;
        heapifyUp(heapSize-1);
    }
     
    /**
     *  This will delete element at index x
     *  Complexity: O(log N)
     * 
     */
    public int delete(int x){
        if(isEmpty())
            throw new NoSuchElementException("Heap is empty, No element to delete");
        int key = heap[x];
        heap[x] = heap[heapSize -1];
        heapSize--;
        heapifyDown(x);
        return key;
    }
 
    /**
     *  This method used to maintain the heap property while inserting an element.
     *  
     */
    private void heapifyUp(int i) {
        int temp = heap[i];
        while(i>0 && temp > heap[parent(i)]){
            heap[i] = heap[parent(i)];
            i = parent(i);
        }
        heap[i] = temp;
    }
     
    /**
     *  This method used to maintain the heap property while deleting an element.
     *  
     */
    private void heapifyDown(int i){
        int child;
        int temp = heap[i];
        while(kthChild(i, 1) < heapSize){
            child = maxChild(i);
            if(temp < heap[child]){ heap[i] = heap[child]; }else break; i = child; } heap[i] = temp; } private int maxChild(int i) { int leftChild = kthChild(i, 1); int rightChild = kthChild(i, 2); return heap[leftChild]>heap[rightChild]?leftChild:rightChild;
    }
     
    /**
     *  This method used to print all element of the heap
     *  
     */
    public void printHeap()
        {
            System.out.print("nHeap = ");
            for (int i = 0; i < heapSize; i++)
                System.out.print(heap[i] +" ");
            System.out.println();
        }
    /**
     *  This method returns the max element of the heap.
     *  complexity: O(1)
     */
     public int findMax(){
         if(isEmpty())
             throw new NoSuchElementException("Heap is empty.");
         return heap[0];
     }
      
     public static void main(String[] args){
         BinaryHeap maxHeap = new BinaryHeap(10);
         maxHeap.insert(10);
         maxHeap.insert(4);
         maxHeap.insert(9);
         maxHeap.insert(1);
         maxHeap.insert(7);
         maxHeap.insert(5);
         maxHeap.insert(3);
          
         maxHeap.printHeap();
         maxHeap.delete(5);
         maxHeap.printHeap();
          
     }
}

heap and stack memory in java

Whenever an object is created, it’s always stored in the Heap space, and stack
memory contains the reference to it. Stack memory only contains local
primitive variables and reference variables to objects in heap space.
Objects stored in the heap are globally accessible whereas stack memory can’t 
be accessed by other threads.
Memory management in stack is done in LIFO manner whereas it’s more complex in
Heap memory because it’s used globally.
Stack memory is short-lived whereas heap memory lives from the start till the
end of application execution.
Heap memory is used by all the parts of the application, stack memory is used
only by one thread of execution.
When stack memory is full, Java runtime throws
java.lang.StackOverFlowError When heap memory is full, it throws
java.lang.OutOfMemoryError: Java Heap Space error.
Stack memory is faster than heap memory.