Find the Second Largest Element in an Array using JavaScript?

In this tutorial, we will learn how to find the second largest element in an array using JavaScript.

Given an array of integers, our task is to write an efficient JavaScript program that finds the second largest element in the given array.

For example:

Input: [12, 11, 5, 19, 26, 2, 13]
Output: The second largest element is 19

Input: [12, 11, 12]
Output: The second largest element is 11 

Input: [13, 13, 13]
Output: The second largest element doesn't exist 

There can be several approaches to solve this problem. However, we will discuss only the most efficient and commonly used ones.


Approach 1:

In this approach, we will traverse the whole array using a for loop and keep track of the largest and the second largest element at each iteration.

We will use the below algorithm:

  1. Create two variables largest and secondLargest and initialize them with the minimum possible value i.e -Infinity.
  2. Start traversing the array from the very first element:
    • Check if the current element is greater than the value stored in the largest variable. If yes, copy the value of largest into secondLargest and update the largest to current element i.e. secondLargest = largest and largest = currentElement.
    • If the current element is greater than the value stored in secondLargest and less than the largest, update the value of the secondLargest to current element.
  3. If secondLargest is not equal to -Infinity, it means the second largest exists in the array. Print its value.

Below is the implementation of the above algorithm:

// Find second largest element in an array

const numbers = [12, 11, 5, 19, 26, 2, 13];

let largest = -Infinity, secondLargest = -Infinity;

for(let i=0; i<numbers.length;i++){
    if(numbers[i]>largest){
        secondLargest = largest;
        largest = numbers[i];
    }
    else if(numbers[i]<largest && numbers[i]>secondLargest){
        secondLargest = numbers[i];
    }
}

if(secondLargest!==-Infinity){
    console.log(`Second largest element is ${secondLargest}`);
}
else{
    console.log("Second largest element doesn't exist.");
}

Output:

Second largest element is 19

The time complexity of the above program is O(n).


Approach 2 –

The basic idea of this approach is to sort the array in ascending order. This will put the largest element at the end of the array.

But, the second largest element can either be at the second last position(if it is not equal to the last element) or somewhere before the second last element if the array contains duplicates.

For example:

Input: [12, 11, 5, 19, 26, 2, 13]
Sorted: [2, 5, 11, 12, 13, 19, 26]
Output: Second largest element is 19(second last element)

Input: [12, 26, 5, 19, 26, 2, 13]
Sorted: [2, 5, 12, 13, 19, 26, 26]
Output: Second largest element is 19(third last element)

So, after sorting, we have to basically find that element from the end of the array which is not equal to the last element(largest) of the array.

If no such element exists, it means the array does not have the second largest.

Below is the implementation of the above algorithm:

// Find second largest element in an array

const numbers = [12, 11, 5, 19, 26, 2, 13];

// Sort the array in ascending order
numbers.sort((x,y)=>x-y);

let secondLargest = -Infinity;

for(let i=numbers.length-2; i>=0;i--){
    // If the current element is not equal 
    // to the last(largest) element
    if(numbers[i]!==numbers[numbers.length-1]){
        secondLargest = numbers[i];
        break;
    }
}

if(secondLargest!==-Infinity){
    console.log(`Second largest element is ${secondLargest}`);
}
else{
    console.log("Second largest element doesn't exist.");
}

Output:

Second largest element is 19

The time complexity of the above algorithm will be same as the sort() method’s time complexity which is O(nlogn).

Thanks for reading.


Author

  • Manoj Kumar

    Hi, My name is Manoj Kumar. I am a full-stack developer with a passion for creating robust and efficient web applications. I have hands-on experience with a diverse set of technologies, including but not limited to HTML, CSS, JavaScript, TypeScript, Angular, Node.js, Express, React, and MongoDB.