Problem:
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Priority Queue

A priority queue is a data structure which maintains a set $S$ of elements, each of with an associated value (key), and supports the following operations:

$insert(S, k)$: insert an element $k$ into the set $S$

$extractMax(S)$: remove and return the element of $S$ with the largest key

Write a program which performs the $insert(S, k)$ and $extractMax(S)$ operations to a priority queue $S$.
The priority queue manages a set of integers, which are also keys for the priority.

Input

Multiple operations to the priority queue $S$ are given. Each operation is given by "insert $k$", "extract" or "end" in a line. Here, $k$ represents an integer element to be inserted to the priority queue.

The input ends with "end" operation.

Output

For each "extract" operation, print the element extracted from the priority queue $S$ in a line.

Constraints

The number of operations $\leq 2,000,000$

$0 \leq k \leq 2,000,000,000$

Sample Input 1

insert 8
insert 2
extract
insert 10
extract
insert 11
extract
extract
end

Sample Output 1

8
10
11
2

Solution in JAVA (judge verdict: Accepted)


import java.util.Scanner;
public class Main {

    public static void main(String[] args) {
        Scanner in = new Scanner(System.in);
        Heap heap = new Heap();

        while (true){
            String action = in.next();
            int num = 0;
            if(action.equals("insert")){
                num = in.nextInt();
            }


            if(action.equals("insert")){
                heap.insert(num);
            } else if(action.equals("extract")){
                int popped = heap.extractMax();
                System.out.println(popped);
            } else{
                break;
            }
        }
    }
}

class Heap {
    private int [] heap;
    private int size;
    public Heap(){
        heap = new int[2000001];
        size = 0;
    }

    private int parent(int pos){
        if(pos == 1){
            return 1;
        }
        return pos/2;
    }

    private int leftChild(int pos){
            return (pos * 2);
    }

    private int rightChild(int pos){
        return (pos * 2)+1;
    }

    private boolean isLeaf(int pos) {
        if (pos>1 && pos >= (size / 2) && pos <= size) {
            return true;
        }
        return false;
    }
    //ta funcionando
    private void swap(int fpos, int spos){
        int tmp;
        tmp = this.heap[fpos];
        this.heap[fpos] = this.heap[spos];
        this.heap[spos] = tmp;

    }

    private void maxHeapify(int pos){
        if (isLeaf(pos)) {
            return;
        }
        if(heap[pos] < heap[leftChild(pos)] || heap[pos] < heap[rightChild(pos)]){
            if (heap[leftChild(pos)] > heap[rightChild(pos)]) {
                swap(pos, leftChild(pos));
                maxHeapify(leftChild(pos));
            }
            else {
                swap(pos, rightChild(pos));
                maxHeapify(rightChild(pos));
            }
        }
    }

    public void insert(int k){

        heap[size+1] = k;
        size++;

        int current = size;


        while (current>1 && heap[current]>heap[parent(current)]){
            swap(current, parent(current));
            current = parent(current);
        }


    }

    public int extractMax(){
        int popped = heap[1];
        heap[1] = heap[size];
        heap[size] = 0;
        size--;
        for (int i = 1; i <= size / 2; ) {
            if (heap[i * 2] > heap[(i * 2) + 1]) {
                if (heap[i] < heap[i * 2]) {
                    int aux3;
                    aux3 = heap[i];
                    heap[i] = heap[i * 2];
                    heap[i * 2] = aux3;
                    i = i * 2;
                } else {
                    break;
                }
            } else {
                if (heap[i] < heap[(i * 2) + 1]) {
                    int aux4;
                    aux4 = heap[i];
                    heap[i] = heap[(i * 2) + 1];
                    heap[(i * 2) + 1] = aux4;
                    i = (i * 2) + 1;
                } else {
                    break;
                }
            }
        }

        //maxHeapify(1);
        return popped;
    }
}