Merge sort is used in internal and external sorting.Merge sort is the best way to sort the linked list in comparison to another sorting algorithm.Merge sort is used in e-commerce application.It is slower when it comes to sorting smaller data sets.It requires an array of the same size as the original list to store the final sorted array which consumes the large memory space.It has the same running time complexity irrespective of case scenarios.Merge sort is a stable sorting algorithm.Merge sort can access data in sequence, hence the need for random access is low.Merge sort allows sorting large data set easily.The space complexity of the algorithm is O(n) where we need an array of size n to place the sorted element.
The running time complexity for best case, worst case, and average-case scenario is O(n*log n) where n is the number of elements to be sorted. The final sorted sequence of data is as givenī = c = d = 0 while b < len(l) and c < len(r): We will keep repeating the process until we find the final sorted sequence of the array Later, we will combine the two elements in the given sorted mannerĪgain, we will combine the two lists of two elements and convert them into a list of four elements after sorting. We keep dividing it until the subpart of the list consists of only one element We divide it into two halves as given below Here we take the given unsorted list of elements. ‘mergeSort’ separates the instance into two halves sized sub instances, solves them recursively, and then combines the two sorted half arrays to obtain the solution to the original instance. When the number of elements to be sorted is small, a relatively simple algorithm is used. The algorithm considers two temporary arrays U and V, into which the original array T is divided. These two parts are sorted by recursive calls and then merged with the solution of each part while preserving the order. The divide and conquer approach to sort n numbers using merge sort consists of separating the array T into two parts where the sizes are almost the same. This process keeps repeating by calling the function recursively until we get the final sorted list of elements. Again, the subpart containing two elements will be joined with the other two elements after sorting. Later, it will join these sub-parts of one element each into two elements by sorting them. It keeps repeating the process until each subpart of the list contains only one element. Basically, the principle working of merge sort is that it divides the list of data into two halves and again calls these subparts to further divide it into two halves. It is one of the best examples of applications for divide and conquers algorithms. Merge sort is very popular for its efficiency to sort the data in a small amount of time. Merge sort is one of the most important sorting algorithms based on the divide and conquer technique. In this article, our focus is on what is merge sort, and its algorithm to sort the large collection of data efficiently and in a very short amount of time. All these algorithms have their own techniques to sort the data, along with some advantages and disadvantages. There are many sorting algorithms possible to sort the data like the bubble sort, insertion sort, merge sort, quick sort, counting sort, etc. Therefore, we use certain sorting algorithms which help us to order the collection of data whether it’s worded in a dictionary or phone numbers on your mobile. Just imagine trying to find a meaning of the word in the dictionary, which is not ordered in alphabetical sequence! It's really time-consuming and not at all an effective process. Sorting is a technique to rearrange the collection of data into a specific order. So, let's get started! What is Sorting And How It Is Important? Also, we will learn the merge sort algorithm using an example along with its python code, and lastly the applications of merge sort in detail. Further, we will learn merge sort and its technique using the divide and conquer approach. In this article, we will study what is sorting and its importance in practical life.