Arrays.sort如何實現(xiàn)降序排序
Arrays.sort實現(xiàn)降序排序
在調(diào)用Arrays.sort()對數(shù)組進行排序時,默認是升序排序的,如果想讓數(shù)組降序排序,有下面兩種方法:
1.Collections的reverseOrder
import java.util.*;
?
public class Main {
? ? public static void main(String[] args) {
// ? ? ? ?注意這里是Integer,不是int
? ? ? ? Integer[] arr={9,8,7,6,5,4,3,2,1};
? ? ? ? Arrays.sort(arr,Collections.reverseOrder());
? ? ? ? for(int i:arr){
? ? ? ? ? ? System.out.println(i);
? ? ? ? }
? ? }
}2.利用Comparator接口復(fù)寫compare
import java.util.*;
?
public class Main {
? ? public static void main(String[] args) {
? ? ? ? Integer[] arr={9,8,7,6,5,4,3,2,1};
? ? ? ? Comparator cmp=new CMP();
? ? ? ? Arrays.sort(arr,cmp);
? ? ? ? for(int i:arr){
? ? ? ? ? ? System.out.println(i);
? ? ? ? }
? ? }
}
class CMP implements Comparator<Integer>{
? ? @Override //可以去掉。作用是檢查下面的方法名是不是父類中所有的
? ? public int compare(Integer a,Integer b){
// ? ? ? ?兩種都可以,升序排序的話反過來就行
// ? ? ? ?return a-b<0?1:-1;
? ? ? ? return b-a;
? ? }
}注意:如果需要改變默認的排列方式,不能使用基本類型(int,char等)定義變量,而應(yīng)該用對應(yīng)的類
Arrays.sort底層原理
概述
Collections.sort()方法底層調(diào)用的也是Arrays.sort()方法,下面我們通過測試用例debug,探究一下其源碼,首先說一下結(jié)果,使用到了插入排序,雙軸快排,歸并排序
雙軸快排(DualPivotQuicksort): 顧名思義有兩個軸元素pivot1,pivot2,且pivot ≤
pivot2,將序列分成三段:x < pivot1、pivot1 ≤ x ≤ pivot2、x >pivot2,然后分別對三段進行遞歸。這個算法通常會比傳統(tǒng)的快排效率更高,也因此被作為Arrays.java中給基本類型的數(shù)據(jù)排序的具體實現(xiàn)。
大致流程:

快速排序部分展開



案例
public static void main(String[] args) {
int[] nums = new int[]{6,5,4,3,2,1};
List<Integer> list = Arrays.asList(6, 5, 4, 3, 2, 1);
Arrays.sort(nums);
Collections.sort(list);
System.out.println(Arrays.toString(nums));
System.out.println(list);
}運行結(jié)果

1 進入Arrays.sort()方法
/**
* Sorts the specified array into ascending numerical order.
*
* <p>Implementation note: The sorting algorithm is a Dual-Pivot Quicksort
* by Vladimir Yaroslavskiy, Jon Bentley, and Joshua Bloch. This algorithm
* offers O(n log(n)) performance on many data sets that cause other
* quicksorts to degrade to quadratic performance, and is typically
* faster than traditional (one-pivot) Quicksort implementations.
*
* @param a the array to be sorted
*/
public static void sort(int[] a) {
DualPivotQuicksort.sort(a, 0, a.length - 1, null, 0, 0);
}
方法上的注釋

2 進入DualPivotQuicksort類內(nèi)部的靜態(tài)方法sort
方法上的注釋

3 走sort的流程


1. 排序范圍小于286的數(shù)組使用快速排序
// Use Quicksort on small arrays
if (right - left < QUICKSORT_THRESHOLD) {
sort(a, left, right, true);
return;
}
// Merge sort
......2. 進入sort方法,判斷數(shù)組長度是否小于47,小于則直接采用插入排序,否則執(zhí)行3。


// Use insertion sort on tiny arrays
if (length < INSERTION_SORT_THRESHOLD) {
// Insertion sort
......
}3. 用公式length/8+length/64+1近似計算出數(shù)組長度的1/7。
// Inexpensive approximation of length / 7 int seventh = (length >> 3) + (length >> 6) + 1;
4. 取5個根據(jù)經(jīng)驗得出的等距點。

/*
* Sort five evenly spaced elements around (and including) the
* center element in the range. These elements will be used for
* pivot selection as described below. The choice for spacing
* these elements was empirically determined to work well on
* a wide variety of inputs.
*/
int e3 = (left + right) >>> 1; // The midpoint
int e2 = e3 - seventh;
int e1 = e2 - seventh;
int e4 = e3 + seventh;
int e5 = e4 + seventh;5.將這5個元素進行插入排序
// Sort these elements using insertion sort
if (a[e2] < a[e1]) { long t = a[e2]; a[e2] = a[e1]; a[e1] = t; }
if (a[e3] < a[e2]) { long t = a[e3]; a[e3] = a[e2]; a[e2] = t;
if (t < a[e1]) { a[e2] = a[e1]; a[e1] = t; }
}
if (a[e4] < a[e3]) { long t = a[e4]; a[e4] = a[e3]; a[e3] = t;
if (t < a[e2]) { a[e3] = a[e2]; a[e2] = t;
if (t < a[e1]) { a[e2] = a[e1]; a[e1] = t; }
}
}
if (a[e5] < a[e4]) { long t = a[e5]; a[e5] = a[e4]; a[e4] = t;
if (t < a[e3]) { a[e4] = a[e3]; a[e3] = t;
if (t < a[e2]) { a[e3] = a[e2]; a[e2] = t;
if (t < a[e1]) { a[e2] = a[e1]; a[e1] = t; }
}
}
}6. 選取a[e2],a[e4]分別作為pivot1,pivot2。由于步驟5進行了排序,所以必有pivot1 <=pivot2。定義兩個指針less和great,less從最左邊開始向右遍歷,一直找到第一個不小于pivot1的元素,great從右邊開始向左遍歷,一直找到第一個不大于pivot2的元素。
/*
* Use the second and fourth of the five sorted elements as pivots.
* These values are inexpensive approximations of the first and
* second terciles of the array. Note that pivot1 <= pivot2.
*/
int pivot1 = a[e2];
int pivot2 = a[e4];
/*
* The first and the last elements to be sorted are moved to the
* locations formerly occupied by the pivots. When partitioning
* is complete, the pivots are swapped back into their final
* positions, and excluded from subsequent sorting.
*/
a[e2] = a[left];
a[e4] = a[right];
/*
* Skip elements, which are less or greater than pivot values.
*/
while (a[++less] < pivot1);
while (a[--great] > pivot2);7. 接著定義指針k從less-1開始向右遍歷至great,把小于pivot1的元素移動到less左邊,大于pivot2的元素移動到great右邊。這里要注意,我們已知great處的元素小于pivot2,但是它于pivot1的大小關(guān)系,還需要進行判斷,如果比pivot1還小,需要移動到到less左邊,否則只需要交換到k處。
/*
* Partitioning:
*
* left part center part right part
* +--------------------------------------------------------------+
* | < pivot1 | pivot1 <= && <= pivot2 | ? | > pivot2 |
* +--------------------------------------------------------------+
* ^ ^ ^
* | | |
* less k great
*
* Invariants:
*
* all in (left, less) < pivot1
* pivot1 <= all in [less, k) <= pivot2
* all in (great, right) > pivot2
*
* Pointer k is the first index of ?-part.
*/
outer:
for (int k = less - 1; ++k <= great; ) {
short ak = a[k];
if (ak < pivot1) { // Move a[k] to left part
a[k] = a[less];
/*
* Here and below we use "a[i] = b; i++;" instead
* of "a[i++] = b;" due to performance issue.
*/
a[less] = ak;
++less;
} else if (ak > pivot2) { // Move a[k] to right part
while (a[great] > pivot2) {
if (great-- == k) {
break outer;
}
}
if (a[great] < pivot1) { // a[great] <= pivot2
a[k] = a[less];
a[less] = a[great];
++less;
} else { // pivot1 <= a[great] <= pivot2
a[k] = a[great];
}
/*
* Here and below we use "a[i] = b; i--;" instead
* of "a[i--] = b;" due to performance issue.
*/
a[great] = ak;
--great;
}
}8. 將樞軸交換到它們的最終位置
// Swap pivots into their final positions
a[left] = a[less - 1]; a[less - 1] = pivot1;
a[right] = a[great + 1]; a[great + 1] = pivot2;9. 遞歸排序左右部分,不包括已知的樞軸
// Sort left and right parts recursively, excluding known pivots
sort(a, left, less - 2, leftmost);
sort(a, great + 2, right, false);10. 對于中間的部分,如果大于4/7的數(shù)組長度,遞歸中間部分
/*
* If center part is too large (comprises > 4/7 of the array),
* swap internal pivot values to ends.
*/
if (less < e1 && e5 < great) {
/*
* Skip elements, which are equal to pivot values.
*/
while (a[less] == pivot1) {
++less;
}
while (a[great] == pivot2) {
--great;
}
/*
* Partitioning:
*
* left part center part right part
* +----------------------------------------------------------+
* | == pivot1 | pivot1 < && < pivot2 | ? | == pivot2 |
* +----------------------------------------------------------+
* ^ ^ ^
* | | |
* less k great
*
* Invariants:
*
* all in (*, less) == pivot1
* pivot1 < all in [less, k) < pivot2
* all in (great, *) == pivot2
*
* Pointer k is the first index of ?-part.
*/
outer:
for (int k = less - 1; ++k <= great; ) {
short ak = a[k];
if (ak == pivot1) { // Move a[k] to left part
a[k] = a[less];
a[less] = ak;
++less;
} else if (ak == pivot2) { // Move a[k] to right part
while (a[great] == pivot2) {
if (great-- == k) {
break outer;
}
}
if (a[great] == pivot1) { // a[great] < pivot2
a[k] = a[less];
/*
* Even though a[great] equals to pivot1, the
* assignment a[less] = pivot1 may be incorrect,
* if a[great] and pivot1 are floating-point zeros
* of different signs. Therefore in float and
* double sorting methods we have to use more
* accurate assignment a[less] = a[great].
*/
a[less] = pivot1;
++less;
} else { // pivot1 < a[great] < pivot2
a[k] = a[great];
}
a[great] = ak;
--great;
}
}
}
// Sort center part recursively
sort(a, less, great, false);4 小結(jié)
Arrays.sort對升序數(shù)組、降序數(shù)組和重復(fù)數(shù)組的排序效率有了很大的提升,這里面有幾個重大的優(yōu)化。
- 對于小數(shù)組來說,插入排序效率更高,每次遞歸到小于47的大小時,用插入排序代替快排,明顯提升了性能。
- 雙軸快排使用兩個pivot,每輪把數(shù)組分成3段,在沒有明顯增加比較次數(shù)的情況下巧妙地減少了遞歸次數(shù)。
- pivot的選擇上增加了隨機性,卻沒有帶來隨機數(shù)的開銷。
- 對重復(fù)數(shù)據(jù)進行了優(yōu)化處理,避免了不必要交換和遞歸。
總結(jié)
以上為個人經(jīng)驗,希望能給大家一個參考,也希望大家多多支持腳本之家。
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