如何使用java中Arrays.sort()

import java.util.Arrays;
import java.util.Comparator;

/**
 * Arrays.sort()排序
 */
public class SortTest
{
  public static void main(String []args)
  {
    int[] ints=new int[]{2,324,4,57,1};

    System.out.println("增序排序后顺序");
    Arrays.sort(ints);
    for (int i=0;i()
    {
      /*
      * 此处与c++的比较函数构成不一致
      * c++返回bool型,而Java返回的为int型
      * 当返回值>0时
      * 进行交换，即排序(源码实现为两枢轴快速排序)
       */
      public int compare(Integer o1, Integer o2)
      {
        return o2-o1;
      }


      public boolean equals(Object obj)
      {
        return false;
      }
    });
    for (Integer integer:integers)
    {
      System.out.print(integer+" ");
    }

    System.out.println("\n对部分排序后顺序");
    int[] ints2=new int[]{212,43,2,324,4,4,57,1};
    //对数组的[2,6)位进行排序

    Arrays.sort(ints2,2,6);
    for (int i=0;i

 public static void sort(int[] a) {
    DualPivotQuicksort.sort(a, 0, a.length - 1, null, 0, 0);
  }

 public static void sort(int[] a, int fromIndex, int toIndex) {
    rangeCheck(a.length, fromIndex, toIndex);
    DualPivotQuicksort.sort(a, fromIndex, toIndex - 1, null, 0, 0);
  }

static void sort(int[] a, int left, int right,
           int[] work, int workBase, int workLen) {
    // Use Quicksort on small arrays
    if (right - left < QUICKSORT_THRESHOLD) {
      sort(a, left, right, true);
      return;
    }

    /*
     * Index run[i] is the start of i-th run
     * (ascending or descending sequence).
     */
    int[] run = new int[MAX_RUN_COUNT + 1];
    int count = 0; run[0] = left;

    // Check if the array is nearly sorted
    for (int k = left; k < right; run[count] = k) {
      if (a[k] < a[k + 1]) { // ascending
        while (++k <= right && a[k - 1] <= a[k]);
      } else if (a[k] > a[k + 1]) { // descending
        while (++k <= right && a[k - 1] >= a[k]);
        for (int lo = run[count] - 1, hi = k; ++lo < --hi; ) {
          int t = a[lo]; a[lo] = a[hi]; a[hi] = t;
        }
      } else { // equal
        for (int m = MAX_RUN_LENGTH; ++k <= right && a[k - 1] == a[k]; ) {
          if (--m == 0) {
            sort(a, left, right, true);
            return;
          }
        }
      }

      /*
       * The array is not highly structured,
       * use Quicksort instead of merge sort.
       */
      if (++count == MAX_RUN_COUNT) {
        sort(a, left, right, true);
        return;
      }
    }

    // Check special cases
    // Implementation note: variable "right" is increased by 1.
    if (run[count] == right++) { // The last run contains one element
      run[++count] = right;
    } else if (count == 1) { // The array is already sorted
      return;
    }

    // Determine alternation base for merge
    byte odd = 0;
    for (int n = 1; (n <<= 1) < count; odd ^= 1);

    // Use or create temporary array b for merging
    int[] b;         // temp array; alternates with a
    int ao, bo;       // array offsets from 'left'
    int blen = right - left; // space needed for b
    if (work == null || workLen < blen || workBase + blen > work.length) {
      work = new int[blen];
      workBase = 0;
    }
    if (odd == 0) {
      System.arraycopy(a, left, work, workBase, blen);
      b = a;
      bo = 0;
      a = work;
      ao = workBase - left;
    } else {
      b = work;
      ao = 0;
      bo = workBase - left;
    }

    // Merging
    for (int last; count > 1; count = last) {
      for (int k = (last = 0) + 2; k <= count; k += 2) {
        int hi = run[k], mi = run[k - 1];
        for (int i = run[k - 2], p = i, q = mi; i < hi; ++i) {
          if (q >= hi || p < mi && a[p + ao] <= a[q + ao]) {
            b[i + bo] = a[p++ + ao];
          } else {
            b[i + bo] = a[q++ + ao];
          }
        }
        run[++last] = hi;
      }
      if ((count & 1) != 0) {
        for (int i = right, lo = run[count - 1]; --i >= lo;
          b[i + bo] = a[i + ao]
        );
        run[++last] = right;
      }
      int[] t = a; a = b; b = t;
      int o = ao; ao = bo; bo = o;
    }
  }

/**
 * This class implements the Dual-Pivot Quicksort algorithm by
 * Vladimir Yaroslavskiy, Jon Bentley, and Josh Bloch. The 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.
 *
 * All exposed methods are package-private, designed to be invoked
 * from public methods (in class Arrays) after performing any
 * necessary array bounds checks and expanding parameters into the
 * required forms.
 *
 * @author Vladimir Yaroslavskiy
 * @author Jon Bentley
 * @author Josh Bloch
 *
 * @version 2011.02.11 m765.827.12i:5\7pm
 * @since 1.7
 */