3-way Merge Sort in Python

Last Updated : 12 Apr, 2024

Merge sort involves recursively splitting the array into 2 parts, sorting, and finally merging them. A variant of merge sort is called 3-way merge sort where instead of splitting the array into 2 parts we split it into 3 parts.

Examples:

Input: arr = [12, 11, 13, 5, 6, 7]
Output: [5, 6, 7, 11, 12, 13]

Input: arr = [38, 27, 43, 3, 9, 82, 10]
Output: [3, 9, 10, 27, 38, 43, 82]

Approach:

Merge sort recursively breaks down the arrays to subarrays of size half. Similarly, 3-way Merge sort breaks down the arrays to subarrays of size one third.

Step-by-step algorithm:

Divide the unsorted list into three sublists.
Recursively sort each sublist.
Merge the three sorted sublists to produce the final sorted list.

Below is the implementation of the above idea:

Python3

# Python Program to perform 3 way Merge Sort

""" Merge the sorted ranges [low, mid1), [mid1,mid2) 
and [mid2, high) mid1 is first midpoint 
index in overall range to merge mid2 is second 
midpoint index in overall range to merge"""


def merge(gArray, low, mid1, mid2, high, destArray):
    i = low
    j = mid1
    k = mid2
    l = low

    # Choose smaller of the smallest in the three ranges
    while ((i < mid1) and (j < mid2) and (k < high)):
        if(gArray[i] < gArray[j]):
            if(gArray[i] < gArray[k]):
                destArray[l] = gArray[i]
                l += 1
                i += 1
            else:
                destArray[l] = gArray[k]
                l += 1
                k += 1
        else:
            if(gArray[j] < gArray[k]):
                destArray[l] = gArray[j]
                l += 1
                j += 1
            else:
                destArray[l] = gArray[k]
                l += 1
                k += 1

    # Case where first and second ranges
    # have remaining values
    while ((i < mid1) and (j < mid2)):
        if(gArray[i] < gArray[j]):
            destArray[l] = gArray[i]
            l += 1
            i += 1
        else:
            destArray[l] = gArray[j]
            l += 1
            j += 1

    # case where second and third ranges
    # have remaining values
    while ((j < mid2) and (k < high)):
        if(gArray[j] < gArray[k]):
            destArray[l] = gArray[j]
            l += 1
            j += 1
        else:
            destArray[l] = gArray[k]
            l += 1
            k += 1

    # Case where first and third ranges have
    # remaining values
    while ((i < mid1) and (k < high)):
        if(gArray[i] < gArray[k]):
            destArray[l] = gArray[i]
            l += 1
            i += 1
        else:
            destArray[l] = gArray[k]
            l += 1
            k += 1

    # Copy remaining values from the first range
    while (i < mid1):
        destArray[l] = gArray[i]
        l += 1
        i += 1

    # Copy remaining values from the second range
    while (j < mid2):
        destArray[l] = gArray[j]
        l += 1
        j += 1

    # Copy remaining values from the third range
    while (k < high):
        destArray[l] = gArray[k]
        l += 1
        k += 1


""" Performing the merge sort algorithm on the 
given array of values in the rangeof indices 
[low, high). low is minimum index, high is 
maximum index (exclusive) """


def mergeSort3WayRec(gArray, low, high, destArray):
    # If array size is 1 then do nothing
    if (high - low < 2):
        return

    # Splitting array into 3 parts
    mid1 = low + ((high - low) // 3)
    mid2 = low + 2 * ((high - low) // 3) + 1

    # Sorting 3 arrays recursively
    mergeSort3WayRec(destArray, low, mid1, gArray)
    mergeSort3WayRec(destArray, mid1, mid2, gArray)
    mergeSort3WayRec(destArray, mid2, high, gArray)

    # Merging the sorted arrays
    merge(destArray, low, mid1, mid2, high, gArray)


def mergeSort3Way(gArray, n):
    # if array size is zero return null
    if (n == 0):
        return

    # creating duplicate of given array
    fArray = []

    # copying elements of given array into
    # duplicate array
    fArray = gArray.copy()

    # sort function
    mergeSort3WayRec(fArray, 0, n, gArray)

    # copy back elements of duplicate array
    # to given array
    gArray = fArray.copy()

    # return the sorted array
    return gArray


data = [45, -2, -45, 78, 30, -42, 10, 19, 73, 93]
data = mergeSort3Way(data, 10)
print("After 3 way merge sort: ", end="")
for i in range(10):
    print(f"{data[i]} ", end="")

Output

After 3 way merge sort: -45 -42 -2 10 19 30 45 73 78 93

Time Complexity: O(n log n)
Auxiliary Space: O(n)

Advantages of 3-way Merge Sort:

Efficiency: 3-way merge sort can be more efficient than traditional merge sort, especially when dealing with large datasets or arrays with many duplicate elements.
Reduced Number of Comparisons: By merging three sorted sub-arrays instead of two, the number of comparisons needed during merging is reduced, leading to potentially faster sorting.
Improved Performance: In certain scenarios, 3-way merge sort can outperform traditional merge sort, resulting in better overall performance.
Stable Sorting: Like traditional merge sort, 3-way merge sort is stable, meaning it preserves the relative order of equal elements in the sorted array.

Disadvantages of 3-way Merge Sort:

Extra Overhead: Implementing and managing the merging of three sub-arrays instead of two can introduce additional complexity and overhead, potentially impacting performance.
Increased Memory Usage: 3-way merge sort may require more memory compared to traditional merge sort due to the need to merge three sub-arrays instead of two, especially for larger datasets.
Limited Impact: The benefits of 3-way merge sort may not always be significant, particularly for small or already partially sorted arrays, where the overhead of managing three sub-arrays may outweigh any potential performance gains.

Merge two sorted arrays in Python using heapq

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