How to Perform Merge Sort in Java?

Ever heard about the term, “Divide and Conquer”? This article is quite specifically based on this approach. Merge Sort is a “divide and conquer” algorithm where we first divide the problem into subproblems and then merge them together to conquer our solution. Here is a complete overview of the concept of merge sort in Java.

• What is merge sort in Java?
• Working of merge sort
• Example: Diagram
• Implementation
• Complexity

Let’s begin!

What is merge sort in Java?

Merge sort is one of the popular sorting algorithms available and it follows a divide and conquer approach. A problem is divided into sub-problems and combined together to reach the final solution!

Now, what exactly happens during the working of merge sort? Let us understand in detail.

Working of merge sort

There are two steps followed by the merge sort during the process:

• Divide: In this step, the input array is divided into 2 halves, the pivot is the midpoint of the array. This step is carried out recursively for all the half arrays until there are no more half arrays to divide further.
• Conquer: In this step, we sort and merge the divided arrays from bottom to top and reach towards our sorted array.

This approach helps you to easily sort the sub parts of the problems first and hence, reach the solution.

Let me show you a pictorial representation of merge sort.

Example: Diagram

Here, you saw how does a merge sort look like. The main concept of merge sort is that it takes less time to sort. Now, moving on towards our implementation part!

Implementation

package MyPackage;
public class MergeSort
{
void merge(int arr[], int beg, int mid, int end)
{
int l = mid - beg + 1;
int r = end - mid;
int LeftArray[] = new int [l];
int RightArray[] = new int [r];
for (int i=0; i<l; ++i)
LeftArray[i] = arr[beg + i];
for (int j=0; j<r; ++j)
RightArray[j] = arr[mid + 1+ j];
int i = 0, j = 0;
int k = beg;
while (i<l&&j<r)
{
if (LeftArray[i] <= RightArray[j])
{
arr[k] = LeftArray[i];
i++;
}
else
{
arr[k] = RightArray[j];
j++;
}
k++;
}
while (i<l)
{
arr[k] = LeftArray[i];
i++;
k++;
}
while (j<r)
{
arr[k] = RightArray[j];
j++;
k++;
}
}
void sort(int arr[], int beg, int end)
{
if (beg<end)
{
int mid = (beg+end)/2;
sort(arr, beg, mid);
sort(arr , mid+1, end);
merge(arr, beg, mid, end);
}
}
public static void main(String args[])
{
int arr[] = {40,51,22,45,1,4,90,23,17,55};
MergeSort ob = new MergeSort();
ob.sort(arr, 0, arr.length-1);
System.out.println("nSorted array");
for(int i =0; i<arr.length;i++)
{
System.out.println(arr[i]+"");
}
}
}

Output:
Sorted array
1
4
17
22
23
40
45
51
55
90

This is how a Java code depicting merge sort looks like. Moving on towards the next segment.

Complexity

Complexity is bifurcated into two types: Time complexity and Space complexity. In the case of merge sort, the data is as shown below:

With this, I shall conclude this article. I hope the contents explained above added value to your Java knowledge. We will keep exploring the Java world together. Stay tuned!

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