Print K largest(or smallest) elements in an array
Last Updated :
29 Apr, 2024
Given an array arr[] of size N, the task is to printing K largest elements in an array.
Note: Elements in output array can be in any order
Examples:
Input: [1, 23, 12, 9, 30, 2, 50], K = 3
Output: 50, 30, 23
Input: [11, 5, 12, 9, 44, 17, 2], K = 2
Output: 44, 17
K largest elements in an array using Sorting:
Sort the input array in descending order so that the first K elements in the array are the K largest elements
Follow the below steps to solve the problem:
- Sort the elements in descending order
- Print the first K numbers of the sorted array
Below is the implementation of the above approach:
C++
// C++ code for K largest elements in an array
#include <bits/stdc++.h>
using namespace std;
void kLargest(int arr[], int n, int k)
{
// Sort the given array arr in reverse order.
sort(arr, arr + n, greater<int>());
// Print the first kth largest elements
for (int i = 0; i < k; i++)
cout << arr[i] << " ";
}
// Driver code
int main()
{
int arr[] = { 1, 23, 12, 9, 30, 2, 50 };
int n = sizeof(arr) / sizeof(arr[0]);
int k = 3;
kLargest(arr, n, k);
}
// This code is contributed by Aditya Kumar (adityakumar129)
C
// C code for k largest elements in an array
#include <stdio.h>
#include <stdlib.h>
// Compare function for qsort
int cmpfunc(const void* a, const void* b)
{
return (*(int*)b - *(int*)a);
}
void kLargest(int arr[], int n, int k)
{
// Sort the given array arr in reverse order.
qsort(arr, n, sizeof(int), cmpfunc);
// Print the first kth largest elements
for (int i = 0; i < k; i++)
printf("%d ", arr[i]);
}
// Driver code
int main()
{
int arr[] = { 1, 23, 12, 9, 30, 2, 50 };
int n = sizeof(arr) / sizeof(arr[0]);
int k = 3;
kLargest(arr, n, k);
}
// This code is contributed by Aditya Kumar (adityakumar129)
Java
// Java code for k largest elements in an array
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
class GFG {
public static void kLargest(Integer[] arr, int k)
{
// Sort the given array arr in reverse order
// This method doesn't work with primitive data
// types. So, instead of int, Integer type
// array will be used
Arrays.sort(arr, Collections.reverseOrder());
// Print the first kth largest elements
for (int i = 0; i < k; i++)
System.out.print(arr[i] + " ");
}
// This code is contributed by Niraj Dubey
public static ArrayList<Integer> kLargest(int[] arr,
int k)
{
// Convert using stream
Integer[] obj_array
= Arrays.stream(arr).boxed().toArray(
Integer[] ::new);
Arrays.sort(obj_array, Collections.reverseOrder());
ArrayList<Integer> list = new ArrayList<>(k);
for (int i = 0; i < k; i++)
list.add(obj_array[i]);
return list;
}
// Driver code
public static void main(String[] args)
{
Integer arr[]
= new Integer[] { 1, 23, 12, 9, 30, 2, 50 };
int k = 3;
kLargest(arr, k);
// This code is contributed by Niraj Dubey
// What if primitive datatype array is passed and
// wanted to return in ArrayList<Integer>
int[] prim_array = { 1, 23, 12, 9, 30, 2, 50 };
kLargest(prim_array, k);
}
}
// This code is contributed by Kamal Rawal
Python
''' Python3 code for k largest elements in an array'''
def kLargest(arr, k):
# Sort the given array arr in reverse
# order.
arr.sort(reverse=True)
# Print the first kth largest elements
for i in range(k):
print(arr[i], end=" ")
# Driver code
arr = [1, 23, 12, 9, 30, 2, 50]
# n = len(arr)
k = 3
kLargest(arr, k)
# This code is contributed by shreyanshi_arun.
C#
// C# code for k largest elements in an array
using System;
class GFG {
public static void kLargest(int[] arr, int k)
{
// Sort the given array arr in reverse order
// This method doesn't work with primitive data
// types. So, instead of int, Integer type
// array will be used
Array.Sort(arr);
Array.Reverse(arr);
// Print the first kth largest elements
for (int i = 0; i < k; i++)
Console.Write(arr[i] + " ");
}
// Driver code
public static void Main(String[] args)
{
int[] arr = new int[] { 1, 23, 12, 9, 30, 2, 50 };
int k = 3;
kLargest(arr, k);
}
}
// This code contributed by Rajput-Ji
Javascript
<script>
// JavaScript code for k largest
// elements in an array
function kLargest(arr, n, k)
{
// Sort the given array arr in reverse
// order.
arr.sort((a, b) => b - a);
// Print the first kth largest elements
for (let i = 0; i < k; i++)
document.write(arr[i] + " ");
}
// driver program
let arr = [ 1, 23, 12, 9, 30, 2, 50 ];
let n = arr.length;
let k = 3;
kLargest(arr, n, k);
// This code is contributed by Manoj.
</script>
PHP
<?php
// PHP code for k largest
// elements in an array
function kLargest(&$arr, $n, $k)
{
// Sort the given array arr
// in reverse order.
rsort($arr);
// Print the first kth
// largest elements
for ($i = 0; $i < $k; $i++)
echo $arr[$i] . " ";
}
// Driver Code
$arr = array(1, 23, 12, 9,
30, 2, 50);
$n = sizeof($arr);
$k = 3;
kLargest($arr, $n, $k);
// This code is contributed
// by ChitraNayal
?>
Time complexity: O(N * log(N))
Auxiliary Space: O(1)
K largest elements in an array using Binary Search:
The idea is to find the Kth largest element of the array and then print all the elements which are greater than or equal to Kth largest Element. The Kth largest element can be found using binary search by defining a search range based on the minimum and maximum values in the input array. In each iteration of binary search, count the larger than the midpoint and update the search range accordingly. This process continues until the range collapses to a single element, which is the kth largest element.
Follow the given steps to solve the problem:
- Initialize low and high to minimum and maximum element of the array denoting the range within which the answer lies.
- Apply Binary Search on this range.
- If the selected element by calculating mid has less than K elements lesser to it then increase the number that is low = mid + 1.
- Otherwise, Decrement the high pointer, i.e high = mid.
- The Binary Search will terminate when only one element remains in the answer space that would be the Kth largest element.
- Print all the elements which are greater than or equal to Kth largest element.
Below is the implementation of above approach:
C++
// C++ code to implement the binary search approach
#include <algorithm>
#include <climits>
#include <iostream>
using namespace std;
// Function to find the Kth largest element in the array
// using binary search
int findKthLargest(int arr[], int n, int k)
{
int low = INT_MAX, high = INT_MIN;
// Find the minimum and maximum elements in the array
for (int i = 0; i < n; i++) {
low = min(low, arr[i]);
high = max(high, arr[i]);
}
// Perform binary search on the range of elements
// between low and high
while (low <= high) {
int mid = low + (high - low) / 2;
int count = 0;
// Count the number of elements greater than mid in
// the array
for (int i = 0; i < n; i++) {
if (arr[i] > mid) {
count++;
}
}
// If there are at least K elements greater than
// mid, search the right half
if (count >= k) {
low = mid + 1;
}
// Otherwise, search the left half
else {
high = mid - 1;
}
}
// Return the Kth largest element
return high;
}
// Function to print the K largest elements in the array
void printKLargest(int arr[], int n, int k)
{
// Find the Kth largest element
int kthLargest = findKthLargest(arr, n, k);
// Print the K largest elements in decreasing order
for (int i = 0; i < n; i++) {
if (arr[i] >= kthLargest) {
cout << arr[i] << " ";
}
}
cout << endl;
}
// Driver code
int main()
{
int arr[] = { 12, 5, 787, 1, 23 };
int n = sizeof(arr) / sizeof(arr[0]);
int k = 2;
cout << "K largest elements: ";
printKLargest(arr, n, k);
return 0;
}
// This code is contributed by Veerendra_Singh_Rajpoot
Java
import java.io.*;
import java.util.*;
public class GFG {
public static int findKthLargest(int[] arr, int n,
int k)
{
int low = Integer.MAX_VALUE,
high = Integer.MIN_VALUE;
// Find the minimum and maximum elements in the
// array
for (int i : arr) {
low = Math.min(low, i);
high = Math.max(high, i);
}
// Perform binary search on the range of elements
// between low and high
while (low <= high) {
int mid = low + (high - low) / 2;
int count = 0;
// Count the number of elements greater than mid
// in the array
for (int i : arr) {
if (i > mid) {
count++;
}
}
// If there are at least K elements greater than
// mid, search the right half
if (count >= k) {
low = mid + 1;
}
// Otherwise, search the left half
else {
high = mid - 1;
}
}
// Return the Kth largest element
return high;
}
public static void printKLargest(int[] arr, int n,
int k)
{
// Find the Kth largest element
int kthLargest = findKthLargest(arr, n, k);
// Print the K largest elements in decreasing order
for (int i : arr) {
if (i >= kthLargest) {
System.out.print(" " + i);
}
}
}
public static void main(String[] args)
{
int[] arr = { 12, 5, 787, 1, 23 };
int n = arr.length;
int k = 2;
System.out.print("K largest elements:");
printKLargest(arr, n, k);
}
}
// This code is contributed by Rohit Singh
Python3
# Python code to implement the binary search approach
# Function to find the Kth largest element in the array using binary search
def findKthLargest(arr, n, k):
low = float('inf')
high = float('-inf')
# Find the minimum and maximum elements in the array
for i in range(n):
low = min(low, arr[i])
high = max(high, arr[i])
# Perform binary search on the range of elements between low and high
while low <= high:
mid = low + (high - low) // 2
count = 0
# Count the number of elements greater than mid in the array
for i in range(n):
if arr[i] > mid:
count += 1
# If there are at least K elements greater than mid, search the right half
if count >= k:
low = mid + 1
# Otherwise, search the left half
else:
high = mid - 1
# Return the Kth largest element
return high
# Function to print the K largest elements in the array
def printKLargest(arr, n, k):
# Find the Kth largest element
kthLargest = findKthLargest(arr, n, k)
# Print the K largest elements in decreasing order
print("K largest elements:", end=" ")
for i in range(n):
if arr[i] >= kthLargest:
print(arr[i], end=" ")
print()
# Driver code
if __name__ == '__main__':
arr = [12, 5, 787, 1, 23]
n = len(arr)
k = 2
printKLargest(arr, n, k)
# This code is contributed by Susobhan Akhuli
C#
using System;
namespace KthLargestElement
{
class Program
{
static int FindKthLargest(int[] arr, int n, int k)
{
int low = int.MaxValue;
int high = int.MinValue;
// Find the minimum and maximum elements in the array
foreach (int num in arr)
{
low = Math.Min(low, num);
high = Math.Max(high, num);
}
// Perform binary search on the range of elements between low and high
while (low <= high)
{
int mid = low + (high - low) / 2;
int count = 0;
// Count the number of elements greater than mid in the array
foreach (int num in arr)
{
if (num > mid)
{
count++;
}
}
// If there are at least K elements greater than mid, search the right half
if (count >= k)
{
low = mid + 1;
}
// Otherwise, search the left half
else
{
high = mid - 1;
}
}
// Return the Kth largest element
return high;
}
static void PrintKLargest(int[] arr, int n, int k)
{
// Find the Kth largest element
int kthLargest = FindKthLargest(arr, n, k);
// Print the K largest elements in decreasing order
foreach (int num in arr)
{
if (num >= kthLargest)
{
Console.Write(num + " ");
}
}
Console.WriteLine();
}
static void Main(string[] args)
{
int[] arr = { 12, 5, 787, 1, 23 };
int n = arr.Length;
int k = 2;
Console.Write("K largest elements: ");
PrintKLargest(arr, n, k);
}
}
}
Javascript
// Function to find the Kth largest element in the array using binary search
function findKthLargest(arr, k) {
let low = Number.POSITIVE_INFINITY;
let high = Number.NEGATIVE_INFINITY;
// Find the minimum and maximum elements in the array
for (let i = 0; i < arr.length; i++) {
low = Math.min(low, arr[i]);
high = Math.max(high, arr[i]);
}
// Perform binary search on the range of elements between low and high
while (low <= high) {
let mid = low + Math.floor((high - low) / 2);
let count = 0;
// Count the number of elements greater than mid in the array
for (let i = 0; i < arr.length; i++) {
if (arr[i] > mid) {
count++;
}
}
// If there are at least K elements greater than mid, search the right half
if (count >= k) {
low = mid + 1;
}
// Otherwise, search the left half
else {
high = mid - 1;
}
}
// Return the Kth largest element
return high;
}
// Function to print the K largest elements in the array
function printKLargest(arr, k) {
// Find the Kth largest element
const kthLargest = findKthLargest(arr, k);
// Print the K largest elements in decreasing order
process.stdout.write("K largest elements: ");
for (let i = 0; i < arr.length; i++) {
if (arr[i] >= kthLargest) {
process.stdout.write(arr[i] + " ");
}
}
console.log();
}
// Driver code
const arr = [12, 5, 787, 1, 23];
const k = 2;
printKLargest(arr, k);
OutputK largest elements: 787 23
Time complexity: O(n * log (mx-mn)), where mn be minimum and mx be maximum element of array.
Auxiliary Space: O(1)
This is an optimization over method 1, if QuickSort is used as a sorting algorithm in first step. In QuickSort, pick a pivot element, then move the pivot element to its correct position and partition the surrounding array. The idea is, not to do complete quicksort, but stop at the point where pivot itself is k’th largest element. Also, not to recur for both left and right sides of pivot, but recur for one of them according to the position of pivot.
Follow the given steps to solve the problem:
- Run quick sort algorithm on the input array
- In this algorithm pick a pivot element and move it to it’s correct position
- Now, if index of pivot is equal to K then return , else if the index of pivot is less than K, then recur for the right subarray, else recur for the left subarray.
- Repeat this process until the element at index K is not found.
Below is the implementation of the above approach:
C++
// c++ program for the above approach
#include <bits/stdc++.h>
using namespace std;
int partition(int arr[], int l, int r);
// This function stops at K'th largest element in arr[l..r]
// using QuickSort based method.
void KthLargest(int arr[], int l, int r, int K, int N)
{
// Partition the array around last element and get
// position of pivot element in sorted array
int pos = partition(arr, l, r);
// If position is same as k
if (pos - l == K - 1)
return;
// If position is less, recur
// for right subarray
else if (pos - l < K - 1)
return KthLargest(arr, pos + 1, r, K - pos + l - 1,
N);
// Else recur for left subarray
else
return KthLargest(arr, l, pos - 1, K, N);
}
void swap(int* a, int* b)
{
int temp = *a;
*a = *b;
*b = temp;
}
int partition(int arr[], int l, int r)
{
int x = arr[r], i = l;
for (int j = l; j <= r - 1; j++) {
if (arr[j] <= x) {
swap(&arr[i], &arr[j]);
i++;
}
}
swap(&arr[i], &arr[r]);
return i;
}
// Driver code
int main()
{
int arr[]
= { 11, 3, 2, 1, 15, 5, 4, 45, 88, 96, 50, 45 };
int N = sizeof(arr) / sizeof(arr[0]);
int k = 3;
// For Largest
KthLargest(arr, 0, N - 1, k, N);
// Print KLargest no.
cout << k << " largest elements are : ";
for (int i = N - 1; i >= N - k; i--)
cout << arr[i] << " ";
return 0;
}
C
#include <stdio.h>
// Function to swap two integers
void swap(int* a, int* b) {
int temp = *a;
*a = *b;
*b = temp;
}
// Partition the array around the last element and get the position of the pivot element in the sorted array
int partition(int arr[], int l, int r) {
int x = arr[r], i = l;
for (int j = l; j <= r - 1; j++) {
if (arr[j] <= x) {
swap(&arr[i], &arr[j]);
i++;
}
}
swap(&arr[i], &arr[r]);
return i;
}
// This function stops at the K'th largest element in arr[l..r] using QuickSort-based method
void KthLargest(int arr[], int l, int r, int K, int N) {
// Partition the array around the last element and get the position of the pivot element in the sorted array
int pos = partition(arr, l, r);
// If position is the same as K
if (pos - l == K - 1)
return;
// If position is less, recurse for the right subarray
else if (pos - l < K - 1)
return KthLargest(arr, pos + 1, r, K - pos + l - 1, N);
// Else, recurse for the left subarray
else
return KthLargest(arr, l, pos - 1, K, N);
}
int main() {
int arr[] = { 11, 3, 2, 1, 15, 5, 4, 45, 88, 96, 50, 45 };
int N = sizeof(arr) / sizeof(arr[0]);
int k = 3;
// For Largest
KthLargest(arr, 0, N - 1, k, N);
// Print K Largest numbers
printf("%d largest elements are: ", k);
for (int i = N - 1; i >= N - k; i--)
printf("%d ", arr[i]);
printf("\n");
return 0;
}
Java
public class KthLargestElements {
// Function to swap two integers
static void swap(int[] arr, int a, int b) {
int temp = arr[a];
arr[a] = arr[b];
arr[b] = temp;
}
// Partition the array around the last element and get the position of the pivot element in the sorted array
static int partition(int[] arr, int l, int r) {
int x = arr[r];
int i = l;
for (int j = l; j <= r - 1; j++) {
if (arr[j] <= x) {
swap(arr, i, j);
i++;
}
}
swap(arr, i, r);
return i;
}
// This function stops at the K'th largest element in arr[l..r] using QuickSort-based method
static void kthLargest(int[] arr, int l, int r, int k, int N) {
// Partition the array around the last element and get the position of the pivot element in the sorted array
int pos = partition(arr, l, r);
// If the position is the same as k
if (pos - l == k - 1)
return;
// If the position is less, recurse for the right subarray
else if (pos - l < k - 1)
kthLargest(arr, pos + 1, r, k - pos + l - 1, N);
// Else, recurse for the left subarray
else
kthLargest(arr, l, pos - 1, k, N);
}
public static void main(String[] args) {
int[] arr = { 11, 3, 2, 1, 15, 5, 4, 45, 88, 96, 50, 45 };
int N = arr.length;
int k = 3;
// For Largest
kthLargest(arr, 0, N - 1, k, N);
// Print K Largest numbers
System.out.print(k + " largest elements are: ");
for (int i = N - 1; i >= N - k; i--)
System.out.print(arr[i] + " ");
System.out.println();
}
}
Python3
def partition(arr, l, r):
x = arr[r] # Choose the last element as the pivot
i = l
# Iterate through the array and move elements smaller than the pivot to the left
for j in range(l, r):
if arr[j] <= x:
arr[i], arr[j] = arr[j], arr[i]
i += 1
# Swap the pivot element with the element at index 'i'
arr[i], arr[r] = arr[r], arr[i]
return i
def kthLargest(arr, l, r, k, N):
# Partition the array around the pivot
pos = partition(arr, l, r)
# If the position is the same as 'k', we have found the kth largest element
if pos - l == k - 1:
return
# If the position is less than 'k', recurse for the right subarray
elif pos - l < k - 1:
kthLargest(arr, pos + 1, r, k - pos + l - 1, N)
# Otherwise, recurse for the left subarray
else:
kthLargest(arr, l, pos - 1, k, N)
if __name__ == "__main__":
arr = [11, 3, 2, 1, 15, 5, 4, 45, 88, 96, 50, 45]
N = len(arr)
k = 3
# Find the kth largest elements
kthLargest(arr, 0, N - 1, k, N)
# Print K Largest numbers
print(f"{k} largest elements are:", end=" ")
for i in range(N - 1, N - k - 1, -1):
print(arr[i], end=" ")
print()
C#
using System;
public class KthLargestElements
{
// Function to swap two integers
static void Swap(int[] arr, int a, int b)
{
int temp = arr[a];
arr[a] = arr[b];
arr[b] = temp;
}
// Partition the array around the last element and get the position of the pivot element in the sorted array
static int Partition(int[] arr, int l, int r)
{
int x = arr[r];
int i = l;
for (int j = l; j <= r - 1; j++)
{
if (arr[j] <= x)
{
Swap(arr, i, j);
i++;
}
}
Swap(arr, i, r);
return i;
}
// This function stops at the K'th largest element in arr[l..r] using QuickSort-based method
static void KthLargest(int[] arr, int l, int r, int k, int N)
{
// Partition the array around the last element and get the position of the pivot element in the sorted array
int pos = Partition(arr, l, r);
// If the position is the same as k
if (pos - l == k - 1)
return;
// If the position is less than k, recurse for the right subarray
else if (pos - l < k - 1)
KthLargest(arr, pos + 1, r, k - pos + l - 1, N);
// Otherwise, recurse for the left subarray
else
KthLargest(arr, l, pos - 1, k, N);
}
public static void Main()
{
int[] arr = { 11, 3, 2, 1, 15, 5, 4, 45, 88, 96, 50, 45 };
int N = arr.Length;
int k = 3;
// For Largest
KthLargest(arr, 0, N - 1, k, N);
// Print K Largest numbers
Console.Write($"{k} largest elements are: ");
for (int i = N - 1; i >= N - k; i--)
Console.Write($"{arr[i]} ");
Console.WriteLine();
}
}
Javascript
using System;
public class KthLargestElements
{
// Function to swap two integers
static void Swap(int[] arr, int a, int b)
{
int temp = arr[a];
arr[a] = arr[b];
arr[b] = temp;
}
// Partition the array around the last element and get the position of the pivot element in the sorted array
static int Partition(int[] arr, int l, int r)
{
int x = arr[r];
int i = l;
for (int j = l; j <= r - 1; j++)
{
if (arr[j] <= x)
{
Swap(arr, i, j);
i++;
}
}
Swap(arr, i, r);
return i;
}
// This function stops at the K'th largest element in arr[l..r] using QuickSort-based method
static void KthLargest(int[] arr, int l, int r, int k, int N)
{
// Partition the array around the last element and get the position of the pivot element in the sorted array
int pos = Partition(arr, l, r);
// If the position is the same as k
if (pos - l == k - 1)
return;
// If the position is less than k, recurse for the right subarray
else if (pos - l < k - 1)
KthLargest(arr, pos + 1, r, k - pos + l - 1, N);
// Otherwise, recurse for the left subarray
else
KthLargest(arr, l, pos - 1, k, N);
}
public static void Main()
{
int[] arr = { 11, 3, 2, 1, 15, 5, 4, 45, 88, 96, 50, 45 };
int N = arr.Length;
int k = 3;
// For Largest
KthLargest(arr, 0, N - 1, k, N);
// Print K Largest numbers
Console.Write($"{k} largest elements are: ");
for (int i = N - 1; i >= N - k; i--)
Console.Write($"{arr[i]} ");
Console.WriteLine();
}
}
Output3 largest elements are : 88 50 96
Time Complexity: O(N2) in worst case(O(N) on average).
Auxiliary Space: O(N)
Note: We can improve on the standard quicksort algorithm by using the random() function. Instead of using the pivot element as the last element, we can randomly choose the pivot element randomly.
The intuition behind this approach is to maintain a minheap (priority queue) of size K while iterating through the array. Doing this ensures that the min heap always contains the K largest elements encountered so far. If the size of the min heap exceeds K, remove the smallest element this step ensures that the heap maintains the K largest elements encountered so far. In the end, the min heap contains the K largest elements of the array.
Follow the below steps to solve the problem:
- Initialize a min heap (priority queue) pq.
- For each element in the array:
- Push the element onto the min heap.
- If the size of the min heap exceeds K, pop (remove) the smallest element from the min heap. This step ensures that the min heap maintains the K largest elements encountered so far.
- After processing all elements, the min heap will contain the K largest elements of the array.
Below is the implementation of the above approach:
C++
// C++ code for k largest elements in an array
#include <bits/stdc++.h>
using namespace std;
// Function to find k largest array element
void kLargest(vector<int>& v, int N, int K)
{
// Implementation using
// a Priority Queue
priority_queue<int, vector<int>, greater<int> > pq;
for (int i = 0; i < N; ++i) {
// Insert elements into
// the priority queue
pq.push(v[i]);
// If size of the priority
// queue exceeds k
if (pq.size() > K) {
pq.pop();
}
}
// Print the k largest element
while (!pq.empty()) {
cout << pq.top() << " ";
pq.pop();
}
cout << endl;
}
// driver program
int main()
{
// Given array
vector<int> arr
= { 11, 3, 2, 1, 15, 5, 4, 45, 88, 96, 50, 45 };
// Size of array
int n = arr.size();
int k = 3;
cout << k << " largest elements are : ";
kLargest(arr, n, k);
}
Java
// Java code for k largest elements in an array
import java.util.*;
class GFG {
// Function to find k largest array element
static void kLargest(int a[], int n, int k)
{
// Implementation using
// a Priority Queue
PriorityQueue<Integer> pq
= new PriorityQueue<Integer>();
for (int i = 0; i < n; ++i) {
// Insert elements into
// the priority queue
pq.add(a[i]);
// If size of the priority
// queue exceeds k
if (pq.size() > k) {
pq.poll();
}
}
// Print the k largest element
while (!pq.isEmpty()) {
System.out.print(pq.peek() + " ");
pq.poll();
}
System.out.println();
}
// Driver Code
public static void main(String[] args)
{
int a[]
= { 11, 3, 2, 1, 15, 5, 4, 45, 88, 96, 50, 45 };
int n = a.length;
int k = 3;
System.out.print(k + " largest elements are : ");
// Function Call
kLargest(a, n, k);
}
};
Python3
# Python code for k largest elements in an array
import heapq
# Function to find k largest array element
def kLargest(v, N, K):
# Implementation using
# a Priority Queue
pq = []
heapq.heapify(pq)
for i in range(N):
# Insert elements into
# the priority queue
heapq.heappush(pq, v[i])
# If size of the priority
# queue exceeds k
if (len(pq) > K):
heapq.heappop(pq)
# Print the k largest element
while(len(pq) != 0):
print(heapq.heappop(pq), end=' ')
print()
# driver program
# Given array
arr = [11, 3, 2, 1, 15, 5, 4, 45, 88, 96, 50, 45]
# Size of array
n = len(arr)
k = 3
print(k, " largest elements are : ", end='')
kLargest(arr, n, k)
C#
using System;
using System.Linq;
using System.Collections.Generic;
class GFG
{
// Function to find k largest array element
static void kLargest(int[] a, int n, int k)
{
// Implementation using a SortedSet
SortedSet<int> pq = new SortedSet<int>();
for (int i = 0; i < n; ++i)
{
// Insert elements into the SortedSet
pq.Add(a[i]);
// If size of the SortedSet exceeds k
if (pq.Count > k) {
pq.Remove(pq.Min);
}
}
// Print the k largest element
while (pq.Count > 0) {
Console.Write(pq.Max + " ");
pq.Remove(pq.Max);
}
Console.WriteLine();
}
// Driver code
public static void Main(string[] args)
{
int[] a
= { 11, 3, 2, 1, 15, 5, 4, 45, 88, 96, 50, 45 };
int n = a.Length;
int k = 3;
Console.Write(k + " largest elements are : ");
// Function call
kLargest(a, n, k);
}
}
Javascript
// Function to find k largest array element
function kLargest(v, N, K) {
// Implementation using
// a Priority Queue
const pq = [];
v.forEach(val => pq.push(val));
pq.sort((a, b) => a - b);
// If size of the priority
// queue exceeds k
if (pq.length > K) {
pq.splice(0, pq.length - K);
}
// Print the k largest element
while (pq.length !== 0) {
console.log(pq.shift());
}
console.log();
}
// driver program
// Given array
const arr = [11, 3, 2, 1, 15, 5, 4, 45, 88, 96, 50, 45];
// Size of array
const n = arr.length;
const k = 3;
console.log(`${k} largest elements are: `);
kLargest(arr, n, k);
// This code is contributed by adityamaharshi21
Output3 largest elements are : 50 88 96
Time Complexity: O(N * log(K))
Auxiliary Space: O(K)
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