Implement quick sorting in java (code example)
Quick sort is also called partition-exchange sort (partition-exchange sort), referred to as quick sort, a sorting algorithm.
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Under average circumstances, sorting n items requires O(nlog n) (big O notation) comparisons. In the worst case, O(n^2) comparisons are required, but this situation is uncommon. In fact, quicksort O(nlog n) is usually significantly faster than other algorithms because its inner loop can be achieved efficiently on most architectures.
Quick sort uses the divide and conquer strategy to divide a sequence (list) into two subsequences, a smaller one and a larger one, and then recursively sort the two subsequences.
The steps are:
Select the pivot value: Pick an element from the sequence, which is called the "pivot".
Split: Reorder the sequence, all elements smaller than the baseline value are placed in front of the baseline, and all elements larger than the baseline value are placed behind the baseline (numbers equal to the baseline value can be to either side). After this division is completed, the sorting of the reference values is completed.
Recursively sort subsequences: recursively sort the subsequences with elements smaller than the baseline value and the subsequences with elements greater than the baseline value.
The judgment condition for recursing to the bottom is that the size of the array is zero or one. At this time, the array is obviously in order.
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There are several specific methods for selecting the benchmark value. This selection method has a decisive impact on the time performance of sorting.
Code implementation:
public class QuickSort { public static void main(String[] args) { int[] arr = SortUtil.randomArr(6); SortUtil.printArr(arr); // sort(arr,0,arr.length-1); sort1(arr,0,arr.length-1); // int[] arr1= netherlands(arr,0,arr.length-1); // SortUtil.printArr(arr1); SortUtil.printArr(arr); } /** * 快排1.0,时间复杂度O(n²),找出以arr[right]为界的中间位置,小于等于的放左边,大于等于的放右边 * 分为左右2个区域,每个区域重复上面的步骤,直到最后left=right * @param arr * @param left * @param right */ public static void sort(int[] arr,int left,int right){ if(left>=right){return;} int mid = partition(arr,left,right); sort(arr,left,mid-1); sort(arr,mid+1,right); } /** * 快排2.0 以arr[right]作为中间值,最差情况时间复杂度O(n²),平均时间复杂度为 O(n logn) * @param arr * @param left * @param right */ public static void sort1(int[] arr,int left,int right){ if(left>=right){return;} int[] mid = netherlands(arr,left,right); sort1(arr,left,mid[0]-1); sort1(arr,mid[1]+1,right); } private static int partition(int[] arr, int left, int right) { if (left > right) { return -1; } if (left == right) { return left; } int lessEqual = left - 1; int index = left; while (index < right) { // 情况1,当前位置小于等于标记值,当前位置不动,标记右移 if (arr[index] <= arr[right]) { lessEqual++; // 扩大小于等于区域 SortUtil.swap(arr, index, lessEqual); } index++; } // 右边界位置和大于区域的起始位置交换 SortUtil.swap(arr, ++lessEqual, right); return lessEqual; } /** * 荷兰国旗问题 * @param arr * @param left * @param right * @return */ private static int[] netherlands(int[] arr,int left,int right){ if(left>right){ return new int[]{-1,-1}; } if(left==right){ return new int[]{left,right}; } int lessEqual = left-1; int i = left; int more = right; while (i<more){ // 1.i位置==arr[right],i++ if (arr[i]==arr[right]){ i ++; } // 2.i位置<arr[right],i位置与小于区域右一个位置交换 else if (arr[i]<arr[right]){ SortUtil.swap(arr,++lessEqual,i++); } // 3.i位置>arr[right],i位置与大于区域左一个位置交换,i不动 else if(arr[i]>arr[right]){ SortUtil.swap(arr,i,--more); } } SortUtil.swap(arr,right,more); return new int[]{lessEqual+1,more}; } }
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