Priority Queue in Data Structure

Earlier in we have seen Min-Heap and Max-Heap Implementation. Priority Queue is its built-in implementation in Java.

In this article we will see how to perform Min-Heap and Max-Heap using Priority Queue.

Brief:

A priority queue is an abstract data type where each element has a “priority” assigned to it. So the element with the higher priority is served before the other elements. Click here to know in detail about max-Heap and min-Heap. (Source : Wiki)

Return Type	Method	Description
boolean	offer(E e)	Inserts the specified element into this priority queue.
E	peek()	Retrieves, but does not remove, the head of this queue, or returns null if this queue is empty.
E	poll()	Retrieves and removes the head of this queue, or returns null if this queue is empty.
int	size()	Returns the number of elements in this collection.
void	clear()	Removes all of the elements from this priority queue.
boolean	contains(Object o)	Returns true if this queue contains the specified element.
Iterator<E>	iterator()	Returns an iterator over the elements in this queue.
boolean	remove(Object o)	Removes a single instance of the specified element from this queue, if it is present.
Comparator<? super E>	comparator()	Returns the comparator used to order the elements in this queue, or null if this queue is sorted according to the natural ordering of its elements.

Min-Heap using Priority Queue:

	import java.util.PriorityQueue;

	public class MinHeap_PQ {
	PriorityQueue<Integer> pq;

	public MinHeap_PQ() {
	pq = new PriorityQueue<Integer>();
	}

	public void insert(int[] x) {
	for (int i = 0; i < x.length; i++) {
	pq.offer(x[i]);
	}
	}

	public int peek() {
	return pq.peek();
	}

	public int extractMin() {
	return pq.poll();
	}

	public int getSize() {
	return pq.size();
	}

	public void print() {
	System.out.println(pq);
	}

	public static void main(String[] args) {
	int[] arrA = { 1, 6, 2, 9, 4, 3, 8 };
	MinHeap_PQ i = new MinHeap_PQ();
	i.insert(arrA);
	i.print();
	System.out.println("Min Element in the Priority Queue: "
	+ i.extractMin());
	System.out.println("Min Element in the Priority Queue: "
	+ i.extractMin());
	System.out.println("Min Element in the Priority Queue: "
	+ i.extractMin());
	System.out.println("Priority Queue Size: " + i.getSize());
	}
	}

view raw

MinHeap_PQ.java

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Output:
[1, 4, 2, 9, 6, 3, 8]
Min Element in the Priority Queue: 1
Min Element in the Priority Queue: 2
Min Element in the Priority Queue: 3
Priority Queue Size: 4

Max-Heap using Priority Queue:

This gets bit tricky here. By default the Priority Queue works as min-Heap. To implement the max-Heap we need to change the way priority queue works internally by overriding the Comparator.

Complete Code:

	import java.util.Comparator;
	import java.util.PriorityQueue;

	public class MaxHeap_PQ {

	PriorityQueue<Integer> pq;

	public MaxHeap_PQ() {
	pq = new PriorityQueue<Integer>(10, new Comparator<Integer>() {

	@Override
	public int compare(Integer o1, Integer o2) {
	// TODO Auto-generated method stub
	return o2 – o1;
	}
	});
	}

	public void insert(int[] x) {
	for (int i = 0; i < x.length; i++) {
	pq.offer(x[i]);
	}
	}

	public int extractMax() {
	return pq.poll();
	}

	public void display() {
	System.out.println(pq);
	}

	public int getSize() {
	return pq.size();
	}

	public void print() {
	System.out.println(pq);
	}

	public static void main(String[] args) {
	int[] arrA = { 1, 6, 2, 9, 4, 3, 8 };
	MaxHeap_PQ i = new MaxHeap_PQ();
	i.insert(arrA);
	i.print();
	System.out.println("Max Element in the Priority Queue: "
	+ i.extractMax());
	System.out.println("Max Element in the Priority Queue: "
	+ i.extractMax());
	System.out.println("Max Element in the Priority Queue: "
	+ i.extractMax());
	System.out.println("Priority Queue Size: " + i.getSize());
	}
	}

view raw

MaxHeap_PQ.java

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Output:
[9, 6, 8, 1, 4, 2, 3]
Max Element in the Priority Queue: 9
Max Element in the Priority Queue: 8
Max Element in the Priority Queue: 6
Priority Queue Size: 4

Reference : https://docs.oracle.com/javase/7/docs/api/java/util/PriorityQueue.html

Priority Queue in Data Structure

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