How to implement common sorting algorithms in Java

Summary:

1. Bubble sort

Determine the best value in each round of loop;

public void bubbleSort(int[] nums){ int temp; boolean isSort = false; //优化，发现排序好就退出 for (int i = 0; i < nums.length-1; i++) { for (int j = 0; j < nums.length-1-i; j++) { //每次排序后能确定较大值 if(nums[j] > nums[j+1]){ isSort = true; temp = nums[j]; nums[j] = nums[j+1]; nums[j+1] = temp; } } if(!isSort){ return; } else { isSort = false; } } }

2. Selection sort

Select the best value each time and swap it to the edge;

public void selectSort(int[] nums){ for (int i = 0; i < nums.length-1; i++) { int index = i; int minNum = nums[i]; for (int j = i+1; j < nums.length; j++) { if(nums[j] < minNum){ minNum = nums[j]; index = j; } } if(index != i){ nums[index] = nums[i]; nums[i] = minNum; } } }

3. Insertion sort

Find its own position for each number in the loop and insert it;

public void insertionSort(int[] nums){ for (int i = 1; i < nums.length; i++) { int j = i; int insertNum = nums[i]; while(j-1 >= 0 && nums[j-1] > insertNum){ nums[j] = nums[j-1]; j--; } nums[j] = insertNum; } }

4. Quick sort

Select a basic value that is smaller than it Put it on one side, and put the larger one on the other side;

public void quickSortDfs(int[] nums, int left, int right){ if(left > right){ return; } int l = left; int r = right; int baseNum = nums[left]; while(l < r){ //必须右边先走 while(nums[r] >= baseNum && l < r){ r--; } while(nums[l] <= baseNum && l < r){ l++; } int temp = nums[l]; nums[l] = nums[r]; nums[r] = temp; } nums[left] = nums[l]; nums[l] = baseNum; quickSortDfs(nums, left, r-1); quickSortDfs(nums, l+1, right); }

5. Merge sort

Divide and conquer algorithm;

//归 public void mergeSortDfs(int[] nums, int l, int r){ if(l >= r){ return; } int m = (l+r)/2; mergeSortDfs(nums, l, m); mergeSortDfs(nums, m+1, r); merge(nums, l, m, r); } //并 private void merge(int[] nums, int left, int mid, int right){ int[] temp = new int[right-left+1]; int l = left; int m = mid+1; int i = 0; while(l <= mid && m <= right){ if(nums[l] < nums[m]){ temp[i++] = nums[l++]; } else { temp[i++] = nums[m++]; } } while(l <= mid){ temp[i++] = nums[l++]; } while(m <= right){ temp[i++] = nums[m++]; } System.arraycopy(temp, 0, nums, left, temp.length); }

6. Er sort

Introducing step size to reduce the number of number exchanges and improve efficiency;

6.1 Hill-bubble sort (slow)

public void shellBubbleSort(int[] nums){ for (int step = nums.length/2; step > 0 ; step /= 2) { for (int i = step; i < nums.length; i++) { for (int j = i-step; j >= 0; j -= step) { if(nums[j] > nums[j+step]){ int temp = nums[j]; nums[j] = nums[j+step]; nums[j+step] = temp; } } } } }

6.2 Hill -Insertion sort (fast)

public void shellInsertSort(int[] nums){ for (int step = nums.length/2; step > 0; step /= 2) { for (int i = step; i < nums.length; i++) { int j = i; int insertNum = nums[i]; while(j-step >= 0 && nums[j-step] > insertNum){ nums[j] = nums[j-step]; j-=step; } nums[j] = insertNum; } } }

7. Heap sort

Big top heap implements ascending order, moving the maximum value to the last position of the heap each time;

public void heapSort2(int[] nums) { for(int i = nums.length/2-1; i >= 0; i--){ sift(nums, i, nums.length); } for (int i = nums.length-1; i > 0; i--) { int temp = nums[0]; nums[0] = nums[i]; nums[i] = temp; sift(nums, 0, i); } } private void sift(int[] nums, int parent, int len) { int value = nums[parent]; for (int child = 2*parent +1; child < len; child = child*2 +1) { if(child+1 < len && nums[child+1] > nums[child]){ child++; } if(nums[child] > value){ nums[parent] = nums[child]; parent = child; } else { break; } } nums[parent] = value; }

8. Counting sorting

Count the occurrences of each number in order;

public void countSort(int[] nums){ int max = Integer.MIN_VALUE; int min = Integer.MAX_VALUE; for(int num : nums){ max = Math.max(max, num); min = Math.min(min, num); } int[] countMap = new int[max-min+1]; for(int num : nums){ countMap[num-min]++; } int i = 0; int j = 0; while(i < nums.length && j < countMap.length){ if(countMap[j] > 0){ nums[i] = j+min; i++; countMap[j]--; } else { j++; } } }

9. Bucket sorting

Similar to counting sorting, the difference is that the statistics are the numbers in a certain interval (bucket);

public void bucketSort(int[] nums){ int max = Integer.MIN_VALUE; int min = Integer.MAX_VALUE; for(int num : nums){ max = Math.max(max, num); min = Math.min(min, num); } int bucketCount = (max-min)/nums.length+1; List> bucketList = new ArrayList<>(); for (int i = 0; i < bucketCount; i++) { bucketList.add(new ArrayList<>()); } for(int num : nums){ int index = (num-min)/nums.length; bucketList.get(index).add(num); } for(List bucket : bucketList){ Collections.sort(bucket); } int j = 0; for(List bucket : bucketList){ for(int num : bucket){ nums[j] = num; j++; } } }

10. Cardinal sorting

By ones, tens, hundreds Bits are sorted in order;

public void radixSort(int[] nums){ int min = Integer.MAX_VALUE; int max = Integer.MIN_VALUE; for (int num : nums) { min = Math.min(min, num); max = Math.max(max, num); } for (int i = 0; i < nums.length; i++) { nums[i] -= min; } max -= min; int maxLen = (max+"").length(); int[][] bucket = new int[nums.length][10]; int[] bucketCount = new int[10]; for (int i = 0, n = 1; i < maxLen; i++, n*=10) { for (int num : nums) { int digitVal = num / n % 10; bucket[bucketCount[digitVal]][digitVal] = num; bucketCount[digitVal]++; } int index = 0; for (int j = 0; j < bucketCount.length; j++) { if(bucketCount[j] > 0){ for (int k = 0; k < bucketCount[j]; k++) { nums[index] = bucket[k][j]; index++; } } bucketCount[j] = 0; } } for (int i = 0; i < nums.length; i++) { nums[i] += min; } }

11. Using collections or API

11.1 Priority queue

public void priorityQueueSort(int[] nums){ PriorityQueue queue = new PriorityQueue<>(); for(int num : nums){ queue.offer(num); } for (int i = 0; i < nums.length; i++) { nums[i] = queue.poll(); } }

11.2 Java API

public void arraysApiSort(int[] nums){ Arrays.sort(nums); }

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