Implementation code examples of various sorting algorithms in Java

This article mainly introduces code examples of various sorting algorithms implemented in Java. It is relatively comprehensive and can be used for personal testing. If there are any shortcomings, please leave a message to point out.

Half Insertion Sort

Half Insertion Sort is a simple improvement on direct insertion sort. The half insertion introduced here is actually to quickly determine the
insertion position of the i-th element by continuously folding in half. This is actually a search algorithm: half search. The binarySearch() method in Java's Arrays class is the implementation of binary search. It is used to find the specified element from the specified array, provided that the array is already in an ordered state. The effect is the same as direct insertion sorting, except that it is faster, because
is half insertion sorting which can determine the insertion position of the i-th element faster

Code:

package interview; 
/** 
 * @author Administrator 
 * 折半插入排序 
 */ 
public class BinaryInsertSort { 
  public static void binaryInsertSort(DataWrap[] data) { 
    System.out.println("开始排序"); 
    int arrayLength = data.length; 
    for (int i = 1; i < arrayLength; i++) { 
      DataWrap temp = data[i]; 
      int low = 0; 
      int high = i - 1; 
      while (low <= high) { 
        int mid = (low + high) / 2; 
        if (temp.compareTo(data[mid]) > 0) { 
          low = mid + 1; 
        } else { 
          high = mid - 1; 
        } 
      } 
      for (int j = i; j > low; j--) { 
        data[j] = data[j - 1]; 
      } 
      data[low] = temp; 
      System.out.println(java.util.Arrays.toString(data)); 
    } 
  } 
  public static void main(String[] args) { 
    DataWrap[] data = { new DataWrap(9, ""), new DataWrap(-16, ""), 
        new DataWrap(21, "*"), new DataWrap(23, ""), 
        new DataWrap(-30, ""), new DataWrap(-49, ""), 
        new DataWrap(21, ""), new DataWrap(30, "*"), 
        new DataWrap(30, "")}; 
    System.out.println("排序之前：\n" + java.util.Arrays.toString(data)); 
    binaryInsertSort(data); 
    System.out.println("排序之后：\n" + java.util.Arrays.toString(data)); 
  } 
}

Result:

排序之前：
[9, -16, 21*, 23, -30, -49, 21, 30*, 30]
开始排序
[-16, 9, 21*, 23, -30, -49, 21, 30*, 30]
[-16, 9, 21*, 23, -30, -49, 21, 30*, 30]
[-16, 9, 21*, 23, -30, -49, 21, 30*, 30]
[-30, -16, 9, 21*, 23, -49, 21, 30*, 30]
[-49, -30, -16, 9, 21*, 23, 21, 30*, 30]
[-49, -30, -16, 9, 21, 21*, 23, 30*, 30]
[-49, -30, -16, 9, 21, 21*, 23, 30*, 30]
[-49, -30, -16, 9, 21, 21*, 23, 30, 30*]
排序之后：
[-49, -30, -16, 9, 21, 21*, 23, 30, 30*]

Bubble sort

Code:

package interview; 
/** 
 * @author Administrator 
 * 冒泡排序 
 */ 
public class BubbleSort { 
  public static void bubbleSort(DataWrap[] data) { 
    System.out.println("开始排序"); 
    int arrayLength = data.length; 
    for (int i = 0; i < arrayLength - 1; i++) { 
      boolean flag = false; 
      for (int j = 0; j < arrayLength - 1 - i; j++) { 
        if (data[j].compareTo(data[j + 1]) > 0) { 
          DataWrap temp = data[j + 1]; 
          data[j + 1] = data[j]; 
          data[j] = temp; 
          flag = true; 
        } 
      } 
      System.out.println(java.util.Arrays.toString(data)); 
      if (!flag) 
        break; 
    } 
  } 
  public static void main(String[] args) { 
    DataWrap[] data = { new DataWrap(9, ""), new DataWrap(-16, ""), 
        new DataWrap(21, "*"), new DataWrap(23, ""), 
        new DataWrap(-30, ""), new DataWrap(-49, ""), 
        new DataWrap(21, ""), new DataWrap(30, "*"), 
        new DataWrap(30, "")}; 
    System.out.println("排序之前：\n" + java.util.Arrays.toString(data)); 
    bubbleSort(data); 
    System.out.println("排序之后：\n" + java.util.Arrays.toString(data)); 
  } 
}

Running result:

排序之前：
[9, -16, 21*, 23, -30, -49, 21, 30*, 30]
开始排序
[-16, 9, 21*, -30, -49, 21, 23, 30*, 30]
[-16, 9, -30, -49, 21*, 21, 23, 30*, 30]
[-16, -30, -49, 9, 21*, 21, 23, 30*, 30]
[-30, -49, -16, 9, 21*, 21, 23, 30*, 30]
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
排序之后：
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]

Bucket sort

The time efficiency of the algorithm: extremely high time efficiency, it only takes two rounds of traversal. The space efficiency of the algorithm: space The overhead is large and two arrays are needed to complete. The stability of the algorithm

: stable
Code:

package interview; 
import java.util.Arrays; 
/** 
 * @author Administrator 
 * 桶式排序 
 */ 
public class BucketSort { 
  public static void bucketSort(DataWrap[] data, int min, int max) { 
    System.out.println("开始排序"); 
    int arrayLength = data.length; 
    DataWrap[] temp = new DataWrap[arrayLength]; 
    int[] buckets = new int[max - min]; 
    for (int i = 0; i < arrayLength; i++) { 
      buckets[data[i].data - min]++; 
    } 
    System.out.println(Arrays.toString(buckets)); 
    for (int i = 1; i < max - min; i++) { 
      buckets[i] = buckets[i] + buckets[i - 1]; 
    } 
    System.out.println(Arrays.toString(buckets)); 
    System.arraycopy(data, 0, temp, 0, arrayLength); 
    for (int k = arrayLength - 1; k >= 0; k--) { 
      data[--buckets[temp[k].data - min]] = temp[k]; 
    } 
  } 
  public static void main(String[] args) { 
    DataWrap[] data = { new DataWrap(9, ""), new DataWrap(5, ""), 
        new DataWrap(-1, ""), new DataWrap(8, ""), 
        new DataWrap(5, "*"), new DataWrap(7, ""), 
        new DataWrap(3, ""), new DataWrap(-3, ""), 
        new DataWrap(1, ""),new DataWrap(3, "*")}; 
    System.out.println("排序之前：\n" + java.util.Arrays.toString(data)); 
    bucketSort(data, -3, 10); 
    System.out.println("排序之后：\n" + java.util.Arrays.toString(data)); 
  } 
}

Result

排序之前：
[9, 5, -1, 8, 5*, 7, 3, -3, 1, 3*]
开始排序
[1, 0, 1, 0, 1, 0, 2, 0, 2, 0, 1, 1, 1]
[1, 1, 2, 2, 3, 3, 5, 5, 7, 7, 8, 9, 10]
排序之后：
[-3, -1, 1, 3, 3*, 5, 5*, 7, 8, 9]

Heap sort

Code:

package interview; 
/** 
 * @author Administrator 
 * 堆排序 
 */ 
public class HeapSort { 
  public static void heapSort(DataWrap[] data) { 
    System.out.println("开始排序"); 
    int arrayLength = data.length; 
    // 循环建堆 
    for (int i = 0; i < arrayLength - 1; i++) { 
      // 建堆 
      builMaxdHeap(data, arrayLength - 1 - i); 
      // 交换堆顶和最后一个元素 
      swap(data, 0, arrayLength - 1 - i); 
      System.out.println(java.util.Arrays.toString(data)); 
    } 
  } 
  // 对data数组从0到lastIndex建大顶堆 
  private static void builMaxdHeap(DataWrap[] data, int lastIndex) { 
    // 从lastIndex处节点（最后一个节点）的父节点开始 
    for (int i = (lastIndex - 1) / 2; i >= 0; i--) { 
      // k保存当前正在判断的节点 
      int k = i; 
      // 如果当前k节点的子节点存在 
      while (k * 2 + 1 <= lastIndex) { 
        // k节点的左子节点的索引 
        int biggerIndex = 2 * k + 1; 
        // 如果biggerIndex小于lastIndex，即biggerIndex +1 
        // 代表k节点的右子节点存在 
        if (biggerIndex < lastIndex) { 
          // 如果右子节点的值较大 
          if (data[biggerIndex].compareTo(data[biggerIndex + 1]) < 0) { 
            // biggerIndex总是记录较大子节点的索引 
            biggerIndex++; 
          } 
        } 
        // 如果k节点的值小于其较大子节点的值 
        if (data[k].compareTo(data[biggerIndex]) < 0) { 
          // 交换它们 
          swap(data, k, biggerIndex); 
          // 将biggerIndex赋给k，开始while循环的下一次循环 
          // 重新保证k节点的值大于其左、右节点的值 
          k = biggerIndex; 
        } else { 
          break; 
        } 
      } 
    } 
  } 
  // 交换data数组中i、j两个索引处的元素 
  private static void swap(DataWrap[] data, int i, int j) { 
    DataWrap temp = data[i]; 
    data[i] = data[j]; 
    data[j] = temp; 
  } 
  public static void main(String[] args) { 
    DataWrap[] data = { new DataWrap(9, ""), new DataWrap(-16, ""), 
        new DataWrap(21, "*"), new DataWrap(23, ""), 
        new DataWrap(-30, ""), new DataWrap(-49, ""), 
        new DataWrap(21, ""), new DataWrap(30, "*"), 
        new DataWrap(30, "")}; 
    System.out.println("排序之前：\n" + java.util.Arrays.toString(data)); 
    heapSort(data); 
    System.out.println("排序之后：\n" + java.util.Arrays.toString(data)); 
  } 
}

Result:

排序之前：
[9, -16, 21*, 23, -30, -49, 21, 30*, 30]
开始排序
[-16, 30, 21*, 23, -30, -49, 21, 9, 30*]
[-16, 23, 21*, 9, -30, -49, 21, 30, 30*]
[21, 9, 21*, -16, -30, -49, 23, 30, 30*]
[-49, 9, 21*, -16, -30, 21, 23, 30, 30*]
[-30, 9, -49, -16, 21*, 21, 23, 30, 30*]
[-30, -16, -49, 9, 21*, 21, 23, 30, 30*]
[-49, -30, -16, 9, 21*, 21, 23, 30, 30*]
[-49, -30, -16, 9, 21*, 21, 23, 30, 30*]
排序之后：
[-49, -30, -16, 9, 21*, 21, 23, 30, 30*]

Direct insertion sort

package interview;
public class InsertSort {
	public static void insertSort(DataWrap[] data){ 
	  System.out.println("开始排序"); 
	  int arrayLength = data.length; 
	  for(int i = 1;i < arrayLength;i++){ 
	    DataWrap temp = data[i]; 
	    if(data[i].compareTo(data[i-1]) < 0){ 
	      int j = i -1; 
	      for(;j >= 0 && data[j].compareTo(temp) > 0;j--){ 
	        data[j +1] = data[j]; 
	      } 
	      data[j + 1] = temp; 
	    } 
	    System.out.println(java.util.Arrays.toString(data)); 
	  } 
	} 
	public static void main(String[] args) { 
	  DataWrap[] data = { new DataWrap(9, ""), new DataWrap(-16, ""), 
	      new DataWrap(21, "*"), new DataWrap(23, ""), 
	      new DataWrap(-30, ""), new DataWrap(-49, ""), 
	      new DataWrap(21, ""), new DataWrap(30, "*"), 
	      new DataWrap(30, "")}; 
	  System.out.println("排序之前：\n" + java.util.Arrays.toString(data)); 
	  insertSort(data); 
	  System.out.println("排序之后：\n" + java.util.Arrays.toString(data)); 
	} 
}

Result

排序之前：
[9, -16, 21*, 23, -30, -49, 21, 30*, 30]
开始排序
[-16, 9, 21*, 23, -30, -49, 21, 30*, 30]
[-16, 9, 21*, 23, -30, -49, 21, 30*, 30]
[-16, 9, 21*, 23, -30, -49, 21, 30*, 30]
[-30, -16, 9, 21*, 23, -49, 21, 30*, 30]
[-49, -30, -16, 9, 21*, 23, 21, 30*, 30]
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
排序之后：
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]

Merge sort

Time efficiency of the algorithm: The merge algorithm needs to be decomposed and merged recursively. Each time the merge sort is performed, the merge() method is required once. Each execution of

merge() requires n times of comparison, which is poor. An auxiliary sequence of the same size as the original sequence is required. Stability of the algorithm: Stable
Code:

package interview; 
/** 
 * @author Administrator 
 * 归并排序 
 */ 
public class MergeSort { 
  public static void mergeSort(DataWrap[] data) { 
    // 归并排序 
    sort(data, 0, data.length - 1); 
  } 
  // 将索引从left到right范围的数组元素进行归并排序 
  private static void sort(DataWrap[] data, int left, int right) { 
    if(left < right){ 
      //找出中间索引 
      int center = (left + right)/2; 
      sort(data,left,center); 
      sort(data,center+1,right); 
      //合并 
      merge(data,left,center,right); 
    } 
  } 
  // 将两个数组进行归并，归并前两个数组已经有序，归并后依然有序 
  private static void merge(DataWrap[] data, int left, int center, int right) { 
    DataWrap[] tempArr = new DataWrap[data.length]; 
    int mid = center + 1; 
    int third = left; 
    int temp = left; 
    while (left <= center && mid <= right) { 
      if (data[left].compareTo(data[mid]) <= 0) { 
        tempArr[third++] = data[left++]; 
      } else { 
        tempArr[third++] = data[mid++]; 
      } 
    } 
    while (mid <= right) { 
      tempArr[third++] = data[mid++]; 
    } 
    while (left <= center) { 
      tempArr[third++] = data[left++]; 
    } 
    while (temp <= right) { 
      data[temp] = tempArr[temp++]; 
    } 
  } 
  public static void main(String[] args) { 
    DataWrap[] data = { new DataWrap(9, ""), new DataWrap(-16, ""), 
        new DataWrap(21, "*"), new DataWrap(23, ""), 
        new DataWrap(-30, ""), new DataWrap(-49, ""), 
        new DataWrap(21, ""), new DataWrap(30, "*"), 
        new DataWrap(30, "") }; 
    System.out.println("排序之前：\n" + java.util.Arrays.toString(data)); 
    mergeSort(data); 
    System.out.println("排序之后：\n" + java.util.Arrays.toString(data)); 
  } 
}

Result:

排序之前：
[9, -16, 21*, 23, -30, -49, 21, 30*, 30]
排序之后：
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]

Radix sort

Radix sort is no longer a conventional sorting method, it is more like the application of a sorting method. Radix sort must rely on another sorting method.

The general idea of ​​radix sorting is to split the data to be sorted into multiple keywords for sorting. In other words, the essence of radix sorting is multi-keyword sorting.
The idea of ​​multi-keyword sorting is to split the sorting keywords in the data to be sorted into multiple sorting keywords: the 1st sub-keyword, the 2nd sub-keyword, and the 3rd sub-
keyword. . . Then, sort the data to be sorted according to the sub-keywords. There are two solutions when performing multi-keyword sorting:

Highest digit first method MSDLowest digit first method LSD

Compare the MSD method and the LSD method. Generally speaking, the LSD method is simpler than the MSD method because the LSD method distributes and collects several times from beginning to end. The number of executions

depends on the constituent keywords. What are the components of the value? The MSD rule may be more complicated to deal with the independent sorting of each sequence and subsequence.

Code:

package interview; 
 
import java.util.Arrays; 
 
/** 
 * @author Administrator 
 * 基数排序 
 */ 
public class MultiKeyRadixSort { 
  public static void radixSort(int[] data, int radix, int d) { 
    System.out.println("开始排序："); 
    int arrayLength = data.length; 
    int[] temp = new int[arrayLength]; 
    int[] buckets = new int[radix]; 
    for (int i = 0, rate = 1; i < d; i++) { 
      // 重置count数组，开始统计第二个关键字 
      Arrays.fill(buckets, 0); 
      // 当data数组的元素复制到temp数组中进行缓存 
      System.arraycopy(data, 0, temp, 0, arrayLength); 
      for (int j = 0; j < arrayLength; j++) { 
        int subKey = (temp[j] / rate) % radix; 
        buckets[subKey]++; 
      } 
      for (int j = 1; j < radix; j++) { 
        buckets[j] = buckets[j] + buckets[j - 1]; 
      } 
      for (int m = arrayLength - 1; m >= 0; m--) { 
        int subKey = (temp[m] / rate) % radix; 
        data[--buckets[subKey]] = temp[m]; 
      } 
      System.out.println("对" + rate + "位上子关键字排序：" 
          + java.util.Arrays.toString(data)); 
      rate *= radix; 
    } 
  } 
 
  public static void main(String[] args) { 
    int[] data = { 1100, 192, 221, 12, 13 }; 
    System.out.println("排序之前：\n" + java.util.Arrays.toString(data)); 
    radixSort(data, 10, 4); 
    System.out.println("排序之后：\n" + java.util.Arrays.toString(data)); 
  } 
}

Result

排序之前：
[1100, 192, 221, 12, 13]
开始排序：
对1位上子关键字排序：[1100, 221, 192, 12, 13]
对10位上子关键字排序：[1100, 12, 13, 221, 192]
对100位上子关键字排序：[12, 13, 1100, 192, 221]
对1000位上子关键字排序：[12, 13, 192, 221, 1100]
排序之后：
[12, 13, 192, 221, 1100]

Quick Sort

Code:

package interview; 
/** 
 * @author Administrator 
 * 快速排序 
 */ 
public class QuickSort { 
  private static void swap(DataWrap[] data, int i, int j) { 
    DataWrap temp = data[i]; 
    data[i] = data[j]; 
    data[j] = temp; 
  } 
  private static void subSort(DataWrap[] data, int start, int end) { 
    if (start < end) { 
      DataWrap base = data[start]; 
      int i = start; 
      int j = end + 1; 
      while (true) { 
        while (i < end && data[++i].compareTo(base) <= 0) 
          ; 
        while (j > start && data[--j].compareTo(base) >= 0) 
          ; 
        if (i < j) { 
          swap(data, i, j); 
        } else { 
          break; 
        } 
      } 
      swap(data, start, j); 
      subSort(data, start, j - 1); 
      subSort(data, j + 1, end); 
    } 
  } 
  public static void quickSort(DataWrap[] data){ 
    subSort(data,0,data.length-1); 
  } 
  public static void main(String[] args) { 
    DataWrap[] data = { new DataWrap(9, ""), new DataWrap(-16, ""), 
        new DataWrap(21, "*"), new DataWrap(23, ""), 
        new DataWrap(-30, ""), new DataWrap(-49, ""), 
        new DataWrap(21, ""), new DataWrap(30, "*"), 
        new DataWrap(30, "") }; 
    System.out.println("排序之前：\n" + java.util.Arrays.toString(data)); 
    quickSort(data); 
    System.out.println("排序之后：\n" + java.util.Arrays.toString(data)); 
  } 
}

Result

排序之前：
[9, -16, 21*, 23, -30, -49, 21, 30*, 30]
排序之后：
[-49, -30, -16, 9, 21, 21*, 23, 30*, 30]

Direct selection sort

Code:

package interview; 
/** 
 * @author Administrator 
 * 直接选择排序 
 */ 
public class SelectSort { 
  public static void selectSort(DataWrap[] data) { 
    System.out.println("开始排序"); 
    int arrayLength = data.length; 
    for (int i = 0; i < arrayLength - 1; i++) { 
      for (int j = i + 1; j < arrayLength; j++) { 
        if (data[i].compareTo(data[j]) > 0) { 
          DataWrap temp = data[i]; 
          data[i] = data[j]; 
          data[j] = temp; 
        } 
      } 
      System.out.println(java.util.Arrays.toString(data)); 
    } 
  } 
  public static void main(String[] args) { 
    DataWrap[] data = { new DataWrap(9, ""), new DataWrap(-16, ""), 
        new DataWrap(21, "*"), new DataWrap(23, ""), 
        new DataWrap(-30, ""), new DataWrap(-49, ""), 
        new DataWrap(21, ""), new DataWrap(30, "*"), 
        new DataWrap(30, "") }; 
    System.out.println("排序之前：\n" + java.util.Arrays.toString(data)); 
    selectSort(data); 
    System.out.println("排序之后：\n" + java.util.Arrays.toString(data)); 
  } 
}

排序之前：
[9, -16, 21*, 23, -30, -49, 21, 30*, 30]
开始排序
[-49, 9, 21*, 23, -16, -30, 21, 30*, 30]
[-49, -30, 21*, 23, 9, -16, 21, 30*, 30]
[-49, -30, -16, 23, 21*, 9, 21, 30*, 30]
[-49, -30, -16, 9, 23, 21*, 21, 30*, 30]
[-49, -30, -16, 9, 21*, 23, 21, 30*, 30]
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
排序之后：
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]

Hill sort

Code:

package interview; 
/** 
 * @author Administrator 
 * Shell排序 
 */ 
public class ShellSort { 
  public static void ShellSort(DataWrap[] data) { 
    System.out.println("开始排序"); 
    int arrayLength = data.length; 
    int h = 1; 
    /** 
     * 将数组分割成若干个子序列 
     */ 
    while (h <= arrayLength / 3) { 
      h = h * 3 + 1; 
      System.out.println("h的结果：" + h); 
    } 
    while (h > 0) { 
      System.out.println("===h的值：" + h + "==="); 
      /** 
       * 将分成的若干子序列进行直接插入排序 
       */ 
      for (int i = h; i < arrayLength; i++) { 
        DataWrap temp = data[i]; 
        if (data[i].compareTo(data[i - h]) < 0) { 
          int j = i - h; 
          for (; j >= 0 && data[j].compareTo(temp) > 0; j -= h) { 
            data[j + h] = data[j]; 
          } 
          data[j + h] = temp; 
        } 
        System.out.println(java.util.Arrays.toString(data)); 
      } 
      h = (h - 1) / 3; 
    } 
  } 
  public static void main(String[] args) { 
    DataWrap[] data = {  
        new DataWrap(9, ""), new DataWrap(-16, ""), 
        new DataWrap(21, "*"), new DataWrap(23, ""), 
        new DataWrap(-30, ""), new DataWrap(-49, ""), 
        new DataWrap(21, ""), new DataWrap(30, "*"), 
        new DataWrap(30, "")}; 
    System.out.println("排序之前：\n" + java.util.Arrays.toString(data)); 
    ShellSort(data); 
    System.out.println("排序之后：\n" + java.util.Arrays.toString(data)); 
  } 
}

Result:

排序之前：
[9, -16, 21*, 23, -30, -49, 21, 30*, 30]
开始排序
h的结果：4
===h的值：4===
[-30, -16, 21*, 23, 9, -49, 21, 30*, 30]
[-30, -49, 21*, 23, 9, -16, 21, 30*, 30]
[-30, -49, 21*, 23, 9, -16, 21, 30*, 30]
[-30, -49, 21*, 23, 9, -16, 21, 30*, 30]
[-30, -49, 21*, 23, 9, -16, 21, 30*, 30]
===h的值：1===
[-49, -30, 21*, 23, 9, -16, 21, 30*, 30]
[-49, -30, 21*, 23, 9, -16, 21, 30*, 30]
[-49, -30, 21*, 23, 9, -16, 21, 30*, 30]
[-49, -30, 9, 21*, 23, -16, 21, 30*, 30]
[-49, -30, -16, 9, 21*, 23, 21, 30*, 30]
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]
排序之后：
[-49, -30, -16, 9, 21*, 21, 23, 30*, 30]

Required tool class:

package interview;
public class DataWrap implements Comparable<DataWrap>{  
	 int data;  
	 String flag;  
	 public DataWrap(int data, String flag) {  
	   this.data = data;  
	   this.flag = flag;  
	 }  
	 public String toString(){  
	   return data + flag;  
	 }  
	 @Override  
	 public int compareTo(DataWrap dw) {  
	   return this.data > dw.data ?  
	       1 : (this.data == dw.data ? 0 : -1);  
	 }  
	}

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