与 QuickSort 一样，Merge Sort 是一种分而治之的算法。它将输入数组分成两半，为两半调用自己，然后合并已排序的两半。 merge()函数用于合并两半。 merge(arr, l, m, r) 是一个关键过程，它假设 arr[l..m] 和 arr[m+1..r] 已排序并将两个排序的子数组合并为一个。有关详细信息，请参阅以下 C 实现。
MergeSort(arr[], l, r)
If r > l
1. Find the middle point to divide the array into two halves:
middle m = l+ (r-l)/2
2. Call mergeSort for first half:
Call mergeSort(arr, l, m)
3. Call mergeSort for second half:
Call mergeSort(arr, m+1, r)
4. Merge the two halves sorted in step 2 and 3:
Call merge(arr, l, m, r)来自维基百科的下图显示了示例数组 {38, 27, 43, 3, 9, 82, 10} 的完整合并排序过程。如果我们仔细看图，我们可以看到数组被递归地分成两半，直到大小变为 1。一旦大小变为 1，合并过程开始起作用并开始合并数组，直到完整的数组合并。
C++
// C++ program for Merge Sort
#include
using namespace std;
// Merges two subarrays of array[].
// First subarray is arr[begin..mid]
// Second subarray is arr[mid+1..end]
void merge(int array[], int const left, int const mid, int const right)
{
auto const subArrayOne = mid - left + 1;
auto const subArrayTwo = right - mid;
// Create temp arrays
auto *leftArray = new int[subArrayOne],
*rightArray = new int[subArrayTwo];
// Copy data to temp arrays leftArray[] and rightArray[]
for (auto i = 0; i < subArrayOne; i++)
leftArray[i] = array[left + i];
for (auto j = 0; j < subArrayTwo; j++)
rightArray[j] = array[mid + 1 + j];
auto indexOfSubArrayOne = 0, // Initial index of first sub-array
indexOfSubArrayTwo = 0; // Initial index of second sub-array
int indexOfMergedArray = left; // Initial index of merged array
// Merge the temp arrays back into array[left..right]
while (indexOfSubArrayOne < subArrayOne && indexOfSubArrayTwo < subArrayTwo) {
if (leftArray[indexOfSubArrayOne] <= rightArray[indexOfSubArrayTwo]) {
array[indexOfMergedArray] = leftArray[indexOfSubArrayOne];
indexOfSubArrayOne++;
}
else {
array[indexOfMergedArray] = rightArray[indexOfSubArrayTwo];
indexOfSubArrayTwo++;
}
indexOfMergedArray++;
}
// Copy the remaining elements of
// left[], if there are any
while (indexOfSubArrayOne < subArrayOne) {
array[indexOfMergedArray] = leftArray[indexOfSubArrayOne];
indexOfSubArrayOne++;
indexOfMergedArray++;
}
// Copy the remaining elements of
// right[], if there are any
while (indexOfSubArrayTwo < subArrayTwo) {
array[indexOfMergedArray] = rightArray[indexOfSubArrayTwo];
indexOfSubArrayTwo++;
indexOfMergedArray++;
}
}
// begin is for left index and end is
// right index of the sub-array
// of arr to be sorted */
void mergeSort(int array[], int const begin, int const end)
{
if (begin >= end)
return; // Returns recursivly
auto mid = begin + (end - begin) / 2;
mergeSort(array, begin, mid);
mergeSort(array, mid + 1, end);
merge(array, begin, mid, end);
}
// UTILITY FUNCTIONS
// Function to print an array
void printArray(int A[], int size)
{
for (auto i = 0; i < size; i++)
cout << A[i] << " ";
}
// Driver code
int main()
{
int arr[] = { 12, 11, 13, 5, 6, 7 };
auto arr_size = sizeof(arr) / sizeof(arr[0]);
cout << "Given array is \n";
printArray(arr, arr_size);
mergeSort(arr, 0, arr_size - 1);
cout << "\nSorted array is \n";
printArray(arr, arr_size);
return 0;
}
// This code is contributed by Mayank Tyagi
// This code was revised by Joshua Estes C
/* C program for Merge Sort */
#include
#include
// Merges two subarrays of arr[].
// First subarray is arr[l..m]
// Second subarray is arr[m+1..r]
void merge(int arr[], int l, int m, int r)
{
int i, j, k;
int n1 = m - l + 1;
int n2 = r - m;
/* create temp arrays */
int L[n1], R[n2];
/* Copy data to temp arrays L[] and R[] */
for (i = 0; i < n1; i++)
L[i] = arr[l + i];
for (j = 0; j < n2; j++)
R[j] = arr[m + 1 + j];
/* Merge the temp arrays back into arr[l..r]*/
i = 0; // Initial index of first subarray
j = 0; // Initial index of second subarray
k = l; // Initial index of merged subarray
while (i < n1 && j < n2) {
if (L[i] <= R[j]) {
arr[k] = L[i];
i++;
}
else {
arr[k] = R[j];
j++;
}
k++;
}
/* Copy the remaining elements of L[], if there
are any */
while (i < n1) {
arr[k] = L[i];
i++;
k++;
}
/* Copy the remaining elements of R[], if there
are any */
while (j < n2) {
arr[k] = R[j];
j++;
k++;
}
}
/* l is for left index and r is right index of the
sub-array of arr to be sorted */
void mergeSort(int arr[], int l, int r)
{
if (l < r) {
// Same as (l+r)/2, but avoids overflow for
// large l and h
int m = l + (r - l) / 2;
// Sort first and second halves
mergeSort(arr, l, m);
mergeSort(arr, m + 1, r);
merge(arr, l, m, r);
}
}
/* UTILITY FUNCTIONS */
/* Function to print an array */
void printArray(int A[], int size)
{
int i;
for (i = 0; i < size; i++)
printf("%d ", A[i]);
printf("\n");
}
/* Driver code */
int main()
{
int arr[] = { 12, 11, 13, 5, 6, 7 };
int arr_size = sizeof(arr) / sizeof(arr[0]);
printf("Given array is \n");
printArray(arr, arr_size);
mergeSort(arr, 0, arr_size - 1);
printf("\nSorted array is \n");
printArray(arr, arr_size);
return 0;
} Java
/* Java program for Merge Sort */
class MergeSort
{
// Merges two subarrays of arr[].
// First subarray is arr[l..m]
// Second subarray is arr[m+1..r]
void merge(int arr[], int l, int m, int r)
{
// Find sizes of two subarrays to be merged
int n1 = m - l + 1;
int n2 = r - m;
/* Create temp arrays */
int L[] = new int[n1];
int R[] = new int[n2];
/*Copy data to temp arrays*/
for (int i = 0; i < n1; ++i)
L[i] = arr[l + i];
for (int j = 0; j < n2; ++j)
R[j] = arr[m + 1 + j];
/* Merge the temp arrays */
// Initial indexes of first and second subarrays
int i = 0, j = 0;
// Initial index of merged subarry array
int k = l;
while (i < n1 && j < n2) {
if (L[i] <= R[j]) {
arr[k] = L[i];
i++;
}
else {
arr[k] = R[j];
j++;
}
k++;
}
/* Copy remaining elements of L[] if any */
while (i < n1) {
arr[k] = L[i];
i++;
k++;
}
/* Copy remaining elements of R[] if any */
while (j < n2) {
arr[k] = R[j];
j++;
k++;
}
}
// Main function that sorts arr[l..r] using
// merge()
void sort(int arr[], int l, int r)
{
if (l < r) {
// Find the middle point
int m =l+ (r-l)/2;
// Sort first and second halves
sort(arr, l, m);
sort(arr, m + 1, r);
// Merge the sorted halves
merge(arr, l, m, r);
}
}
/* A utility function to print array of size n */
static void printArray(int arr[])
{
int n = arr.length;
for (int i = 0; i < n; ++i)
System.out.print(arr[i] + " ");
System.out.println();
}
// Driver code
public static void main(String args[])
{
int arr[] = { 12, 11, 13, 5, 6, 7 };
System.out.println("Given Array");
printArray(arr);
MergeSort ob = new MergeSort();
ob.sort(arr, 0, arr.length - 1);
System.out.println("\nSorted array");
printArray(arr);
}
}
/* This code is contributed by Rajat Mishra */Python3
# Python program for implementation of MergeSort
def mergeSort(arr):
if len(arr) > 1:
# Finding the mid of the array
mid = len(arr)//2
# Dividing the array elements
L = arr[:mid]
# into 2 halves
R = arr[mid:]
# Sorting the first half
mergeSort(L)
# Sorting the second half
mergeSort(R)
i = j = k = 0
# Copy data to temp arrays L[] and R[]
while i < len(L) and j < len(R):
if L[i] < R[j]:
arr[k] = L[i]
i += 1
else:
arr[k] = R[j]
j += 1
k += 1
# Checking if any element was left
while i < len(L):
arr[k] = L[i]
i += 1
k += 1
while j < len(R):
arr[k] = R[j]
j += 1
k += 1
# Code to print the list
def printList(arr):
for i in range(len(arr)):
print(arr[i], end=" ")
print()
# Driver Code
if __name__ == '__main__':
arr = [12, 11, 13, 5, 6, 7]
print("Given array is", end="\n")
printList(arr)
mergeSort(arr)
print("Sorted array is: ", end="\n")
printList(arr)
# This code is contributed by Mayank KhannaC#
// C# program for Merge Sort
using System;
class MergeSort {
// Merges two subarrays of []arr.
// First subarray is arr[l..m]
// Second subarray is arr[m+1..r]
void merge(int[] arr, int l, int m, int r)
{
// Find sizes of two
// subarrays to be merged
int n1 = m - l + 1;
int n2 = r - m;
// Create temp arrays
int[] L = new int[n1];
int[] R = new int[n2];
int i, j;
// Copy data to temp arrays
for (i = 0; i < n1; ++i)
L[i] = arr[l + i];
for (j = 0; j < n2; ++j)
R[j] = arr[m + 1 + j];
// Merge the temp arrays
// Initial indexes of first
// and second subarrays
i = 0;
j = 0;
// Initial index of merged
// subarry array
int k = l;
while (i < n1 && j < n2) {
if (L[i] <= R[j]) {
arr[k] = L[i];
i++;
}
else {
arr[k] = R[j];
j++;
}
k++;
}
// Copy remaining elements
// of L[] if any
while (i < n1) {
arr[k] = L[i];
i++;
k++;
}
// Copy remaining elements
// of R[] if any
while (j < n2) {
arr[k] = R[j];
j++;
k++;
}
}
// Main function that
// sorts arr[l..r] using
// merge()
void sort(int[] arr, int l, int r)
{
if (l < r) {
// Find the middle
// point
int m = l+ (r-l)/2;
// Sort first and
// second halves
sort(arr, l, m);
sort(arr, m + 1, r);
// Merge the sorted halves
merge(arr, l, m, r);
}
}
// A utility function to
// print array of size n */
static void printArray(int[] arr)
{
int n = arr.Length;
for (int i = 0; i < n; ++i)
Console.Write(arr[i] + " ");
Console.WriteLine();
}
// Driver code
public static void Main(String[] args)
{
int[] arr = { 12, 11, 13, 5, 6, 7 };
Console.WriteLine("Given Array");
printArray(arr);
MergeSort ob = new MergeSort();
ob.sort(arr, 0, arr.Length - 1);
Console.WriteLine("\nSorted array");
printArray(arr);
}
}
// This code is contributed by Princi SinghJavascript
输出
Given array is
12 11 13 5 6 7
Sorted array is
5 6 7 11 12 13时间复杂度：在不同机器上对数组进行排序。归并排序是一种递归算法，时间复杂度可以表示为以下递归关系。
T(n) = 2T(n/2) + θ(n)
上述递归可以使用递归树方法或主方法来解决。它属于 Master Method 的 case II，递归的解是 θ(nLogn)。归并排序的时间复杂度在所有 3 种情况下(最差、平均和最好)都是 θ(nLogn)，因为归并排序总是将数组分成两半，并且需要线性时间来合并两半。
辅助空间： O(n)
算法范式：分而治之
就地排序：在典型实现中没有
稳定：是
归并排序的应用
- 合并排序对于在 O(nLogn) 时间内对链表进行排序很有用。在链表的情况下，情况不同主要是由于数组和链表的内存分配不同。与数组不同，链表节点在内存中可能不相邻。与数组不同，在链表中，我们可以在 O(1) 额外空间和 O(1) 时间内在中间插入项目。因此，归并排序的归并操作可以在不给链表额外空间的情况下实现。
在数组中，我们可以进行随机访问，因为元素在内存中是连续的。假设我们有一个整数(4 字节)数组 A，让 A[0] 的地址为 x，然后访问 A[i]，我们可以直接访问 (x + i*4) 处的内存。与数组不同，我们不能在链表中进行随机访问。快速排序需要大量此类访问。在访问第 i 个索引的链表中，由于没有连续的内存块，我们必须从头到第 i 个节点遍历每个节点。因此，快速排序的开销会增加。归并排序顺序访问数据，随机访问的需求低。 - 倒数问题
- 用于外部排序
归并排序的缺点
- 与用于较小任务的其他排序算法相比，速度较慢。
- 归并排序算法需要额外的 0(n) 内存空间用于临时数组。
- 即使数组已排序，它也会经历整个过程。
- 归并排序的最新文章
- 排序的编码实践。
- 归并排序测验
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