基本思想:
图示: (88,85,83,73,72,60,57,48,42,6)
平均时间复杂度:
O(NlogN)由于每次重新恢复堆的时间复杂度为O(logN),共N - 1次重新恢复堆操作,再加上前面建立堆时N / 2次向下调整,每次调整时间复杂度也为O(logN)。二次操作时间相加还是O(N * logN)。
Java代码实现:
public class HeapSortTest { public static void main(String[] args) { // TODO Auto-generated method stub int[] arr = new int[] { 10, 3, 2, 5, 6, 1, -2, 3, 14, 12, 3, 8, 55, 44, -10 }; print(arr); heapSort(arr); System.out.println("排序后的数组:"); print(arr); } private static void print(int[] a) { for (int i = 0; i < a.length; i++) { System.out.print(a[i] + " "); } System.out.println(); } private static void swap(int[] a, int i, int j) { a[i] = a[i] + a[j]; a[j] = a[i] - a[j]; a[i] = a[i] - a[j]; } private static void heapSort(int[] a) { for (int i = a.length - 1; i >= 0; i--) { createMaxHeap(a, i); swap(a, 0, i); print(a); } } private static void createMaxHeap(int[] a, int lastIndex) { for (int i = (lastIndex - 1) / 2; i >= 0; i--) { int k = i; while ((2 * k + 1) <= lastIndex) { int biggerIndex = 2 * k + 1; if (biggerIndex < lastIndex) { if (a[biggerIndex] < a[biggerIndex + 1]) { biggerIndex++; } } if (a[k] < a[biggerIndex]) { swap(a, k, biggerIndex); k = biggerIndex; } else { break; } } } } }