我在一次面试中被问到这个问题。它们都是O(nlogn),但大多数人使用快速排序而不是归并排序。为什么呢?
当前回答
快速排序和合并排序的小增加。
它还可以依赖于排序项的类型。如果访问项、交换和比较不是简单的操作,就像比较平面内存中的整数一样,那么归并排序可能是更可取的算法。
例如,我们在远程服务器上使用网络协议对项目进行排序。
而且,在像“链表”这样的自定义容器中,也没有快速排序的好处。 1. 对链表进行归并排序,不需要额外的内存。 2. 快速排序中对元素的访问不是顺序的(在内存中)
其他回答
亩! 快速排序并不比归并排序更好,它非常适合于不同类型的应用。
归并排序是值得考虑的,如果速度是本质,糟糕的最差情况性能不能容忍,并且有额外的空间可用
你说他们«他们都是O(nlogn)[…]»。这是错误的。«快速排序使用大约n^2/2比较在最坏的情况下。
然而,根据我的经验,最重要的属性是在使用带有命令式范式的编程语言进行排序时,可以轻松实现顺序访问。
1 Sedgewick,算法
维基百科上关于快速排序的词条:
Quicksort also competes with mergesort, another recursive sort algorithm but with the benefit of worst-case Θ(nlogn) running time. Mergesort is a stable sort, unlike quicksort and heapsort, and can be easily adapted to operate on linked lists and very large lists stored on slow-to-access media such as disk storage or network attached storage. Although quicksort can be written to operate on linked lists, it will often suffer from poor pivot choices without random access. The main disadvantage of mergesort is that, when operating on arrays, it requires Θ(n) auxiliary space in the best case, whereas the variant of quicksort with in-place partitioning and tail recursion uses only Θ(logn) space. (Note that when operating on linked lists, mergesort only requires a small, constant amount of auxiliary storage.)
快速排序是在实践中最快的排序算法,但有一些病态的情况,可以使它的表现差到O(n2)。
堆排序保证在O(n*ln(n))中运行,并且只需要有限的额外存储空间。但是有许多真实世界的测试表明堆排序比快速排序平均要慢得多。
同时考虑时间和空间的复杂性。 归并排序: 时间复杂度:O(nlogn), 空间复杂度:O(nlogn)
快速排序: 时间复杂度:O(n²), 空间复杂度:O(n)
现在,他们各自在一个场景中获胜。 但是,使用随机枢轴,您几乎总是可以将快速排序的时间复杂度降低到O(nlogn)。
因此,在许多应用中,快速排序是首选,而不是归并排序。
That's hard to say.The worst of MergeSort is n(log2n)-n+1,which is accurate if n equals 2^k(I have already proved this).And for any n,it's between (n lg n - n + 1) and (n lg n + n + O(lg n)).But for quickSort,its best is nlog2n(also n equals 2^k).If you divide Mergesort by quickSort,it equals one when n is infinite.So it's as if the worst case of MergeSort is better than the best case of QuickSort,why do we use quicksort?But remember,MergeSort is not in place,it require 2n memeroy space.And MergeSort also need to do many array copies,which we don't include in the analysis of algorithm.In a word,MergeSort is really faseter than quicksort in theroy,but in reality you need to consider memeory space,the cost of array copy,merger is slower than quick sort.I once made an experiment where I was given 1000000 digits in java by Random class,and it took 2610ms by mergesort,1370ms by quicksort.