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In computer science, Merge Sort (also commonly spelled as mergesort and as merge-sort [2]) is an efficient, general-purpose, and comparison-based sorting algorithm. Most implementations produce a stable sort , which means that the relative order of equal elements is the same in the input and output.
Repeatedly merge sublists to create a new sorted sublist until the single list contains all elements. The single list is the sorted list. The merge algorithm is used repeatedly in the merge sort algorithm. An example merge sort is given in the illustration. It starts with an unsorted array of 7 integers. The array is divided into 7 partitions ...
The divide-and-conquer technique is the basis of efficient algorithms for many problems, such as sorting (e.g., quicksort, merge sort), multiplying large numbers (e.g., the Karatsuba algorithm), finding the closest pair of points, syntactic analysis (e.g., top-down parsers), and computing the discrete Fourier transform . [1]
However, it has additional O(n) space complexity, and involves a large number of copies in simple implementations. Merge sort has seen a relatively recent surge in popularity for practical implementations, due to its use in the sophisticated algorithm Timsort, which is used for the standard sort routine in the programming languages Python [25 ...
Block sort, or block merge sort, is a sorting algorithm combining at least two merge operations with an insertion sort to arrive at O(n log n) (see Big O notation) in-place stable sorting time. It gets its name from the observation that merging two sorted lists, A and B , is equivalent to breaking A into evenly sized blocks , inserting each A ...
The simple parallel merge sort of CLRS is a fork–join algorithm. [5]mergesort(A, lo, hi): if lo < hi: // at least one element of input mid = ⌊lo + (hi - lo) / 2⌋ fork mergesort(A, lo, mid) // process (potentially) in parallel with main task mergesort(A, mid, hi) // main task handles second recursion join merge(A, lo, mid, hi)
Timsort is a hybrid, stable sorting algorithm, derived from merge sort and insertion sort, designed to perform well on many kinds of real-world data. It was implemented by Tim Peters in 2002 for use in the Python programming language. The algorithm finds subsequences of the data that are already ordered (runs) and uses them to sort the ...
k-way merge algorithms usually take place in the second stage of external sorting algorithms, much like they do for merge sort. A multiway merge allows for the files outside of memory to be merged in fewer passes than in a binary merge. If there are 6 runs that need be merged then a binary merge would need to take 3 merge passes, as opposed to ...