- package com.algorithm.hash;
- public class alg1 {
- public static void main(String argv[]) {
- int[] array1 = {10,2,7,4,5,6,3,8,9,1};
- int[] array2 = {1,2,3,4,5,6,7,8,9,10};
- int[] array3 = {1,2,3,4,5,6,7,8,9,10};
- alg1.execute1(array1, 8);
- alg1.execute2(array2, 8);
- alg1.execute3(array3, 8);
- }
- //思路:使用hash表存储数组各元素是否存在的标志,然后遍历数组,判断sum与当前数组元素的差值是否在hash表中,
- //若为真则打印,该算法不要求数组有序,但要求一个hash数组的额外空间,时间复杂度是O(n)
- private static void execute1(int[] array, int m) {
- int size = array.length;
- int hash[] = new int[size];
- for(int i = 0; i < size; i++) {
- hash[array[i]%size] = 1;
- }
- for(int i = 0; i < size; i++) {
- int tmp = m - array[i];
- if((tmp > array[i]) && (hash[tmp%size] == 1)){
- System.out.println(array[i] + " " + tmp);
- }
- }
- }
- //思路:该方法的前提是要求数组是有序的,然后再遍历数组,判断sum与数组元素的差值是否在数组中,由于数组有序所以可以采用二分查找的方法
- //二分查找的时间复杂度为O(logn),排序的时间复杂度是O(nlogn),查找n次,总的时间复杂度为O(nlogn),避免了空间的浪费
- private static void execute2(int[] array, int m) {
- for(int i = 0; i < array.length; i++) {
- int tmp = m - array[i];
- if (tmp > array[i]) {
- if (binarySearch(array, tmp) != -1) {
- System.out.println(array[i] + " " + tmp);
- }
- }
- }
- }
- private static int binarySearch(int[] array, int key) {
- if (array.length == 0) {
- return -1;
- }
- int first = 0;
- int last = array.length -1;
- int mid;
- while(first <= last) {
- mid = (first + last) / 2;
- if (array[mid] == key) {
- return mid;
- } else if (array[mid] < key) {
- first = mid + 1;
- } else {
- last = mid -1;
- }
- }
- return -1;
- }
- //思路:该方法的前提是要求数组是有序的,使用两个指针,分别指向最后一个元素和第一个元素,判断它们的和是否等于sum,若等于则打印,并且first向前移动,last也向前移动
- //若它们的和小于sum,则说明first太小了,需要first向前移动,若它们的和大于sum,则说明last太大了,需要last向前移动,直到last>=first
- private static void execute3(int[] array, int m) {
- int first = 0;
- int last = array.length -1;
- int sum = 0;
- while(first < last ) {
- sum = array[first] + array[last];
- if (sum == m) {
- System.out.println(array[first] + " " + array[last]);
- first++;
- last--;
- } else if (sum < m) {
- first++;
- } else {
- last--;
- }
- }
- }
-