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Arrays.sort如何实现降序排序

目录
  • Arrays.sort实现降序排序
    • 1.Collections的reverseorder
    • 2.利用Comparator接口复写compare
  • Arrays.sort底层原理
    • 概述
    • 案例
  • 总结

    Arrays.sort实现降序排序

    在调用Arrays.sort()对数组进行排序时,默认是升序排序的,如果想让数组降序排序,有下面两种方法:

    1.Collections的reverseOrder

    import Java.util.*;
    
    public class Main {
      public static void main(String[] args) {
    //    注意这里是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接口复写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。作用是检查下面的方法名是不是父类中所有的
      public int compare(Integer a,Integer b){
    //    两种都可以,升序排序的话反过来就行
    //    return a-b<0?1:-1;
        return b-a;
      }
    }

    注意:如果需要改变默认的排列方式,不能使用基本类型(int,char等)定义变量,而应该用对应的类

    Arrays.sort底层原理

    概述

    Collections.sort()方法底层调用的也是Arrays.sort()方法,下面我们通过测试用例debug,探究一下其源码,首先说一下结果,使用到了插入排序,双轴快排,归并排序

    双轴快排(DualPivotQuicksort): 顾名思义有两个轴元素pivot1,pivot2,且pivot ≤

    pivot2,将序列分成三段:x < pivot1、pivot1 ≤ x ≤ pivot2、x >pivot2,然后分别对三段进行递归。这个算法通常会比传统的快排效率更高,也因此被作为Arrays.java中给基本类型的数据排序的具体实现。

    大致流程:

    Arrays.sort如何实现降序排序

    快速排序部分展开

    Arrays.sort如何实现降序排序

    Arrays.sort如何实现降序排序

    Arrays.sort如何实现降序排序

    案例

    	public static void main(String[] args) {
    js        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);
    
        }

    运行结果

    Arrays.sort如何实现降序排序

    1 进入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);
        }

    Arrays.sort如何实现降序排序

    方法上的注释

    Arrays.sort如何实现降序排序

    2 进入DualPivotQuicksort类内部的静态方法sort

    方法上的注释

    Arrays.sort如何实现降序排序

    3 走sort的流程

    Arrays.sort如何实现降序排序

    Arrays.sort如何实现降序排序

    1. 排序范围小于286的数组使用快速排序

     	// Use Quicksort on small arrays
        if (right - left < QUICKSORT_THRESHOLD) {
                sort(a, left, right, true);
                return;
        }
        // Merge sort
        ......

    2. 进入sort方法,判断数组长度是否小于47,小于则直接采用插入排序,否则执行3。

    Arrays.sort如何实现降序排序

    Arrays.sort如何实现降序排序

    	 // Use insertion sort on tiny arrays
        if (length < INSERTION_SORT_THRESHOLD) {
    	   // Insertion sort
    	   ......
        }

    3. 用公式length/8+length/64+1近似计算出数组长度的1/7。

    // Inexpensive approximation of length / 7
    int seventh = (length >> 3) + (length >> 6) + 1;

    4. 取5个根据经验得出的等距点。

    Arrays.sort如何实现降序排序

    		/*
             * 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.将这5个元素进行插入排序

    		// 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;
                  开发者_Go开发  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. 选取a[e2],a[e4]分别作为pivot1,pivot2。由于步骤5进行了排序,所以必有pivot1 <=pivot2。定义两个指针less和great,less从最左边开始向右遍历,一直找到第一个不小于pivot1的元素,great从右边开始向左遍历,一直找到第一个不大于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. 接着定义指针k从less-1开始向右遍历至great,把小于pivot1的元素移动到less左边,大于pivot2的元素移动到great右边。这里要注意,我们已知great处的元素小于pivot2,但是它于pivot1的大小关系,还需要进行判断,如果比pivot1还小,需要移动到到less左边,否则只需要交换到k处。

    			/*
                 * 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
                 *       python       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--] android= b;" due to performance issue.
                         */
                        a[great] = ak;
                        --great;
                    }
                }

    8. 将枢轴交换到它们的最终位置

    	// 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. 递归排序左右部分,不包括已知的枢轴

    		// Sort left and right parts recursively, excluding known pivots
            sort(a, left, less - 2, leftmost);
            sort(a, great + 2, right, false);

    10. 对于中间的部分,如果大于4/7的数组长度,递归中间部分

    			/*
                 * 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 (gjsreat, *) == 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] = jsak;
                            --great;
                        }
                    }
                }
    
                // Sort center part recursively
                sort(a, less, great, false);

    4 小结

    Arrays.sort对升序数组、降序数组和重复数组的排序效率有了很大的提升,这里面有几个重大的优化。

    • 对于小数组来说,插入排序效率更高,每次递归到小于47的大小时,用插入排序代替快排,明显提升了性能。
    • 双轴快排使用两个pivot,每轮把数组分成3段,在没有明显增加比较次数的情况下巧妙地减少了递归次数。
    • pivot的选择上增加了随机性,却没有带来随机数的开销。
    • 对重复数据进行了优化处理,避免了不必要交换和递归。

    总结

    以上为个人经验,希望能给大家一个参考,也希望大家多多支持我们。

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