Problems with Optimizing Merge Sort for Large Datasets in C# - Memory Usage Spikes
After trying multiple solutions online, I still can't figure this out. I've searched everywhere and can't find a clear answer. I've looked through the documentation and I'm still confused about I'm currently implementing a merge sort algorithm in C# for sorting large datasets, and I've run into important memory usage issues... My implementation works correctly for smaller arrays, but when I try to sort an array with over a million elements, I notice the memory spikes sharply, causing the application to slow down considerably and sometimes even throw an `OutOfMemoryException`. Here’s the code I’m using: ```csharp public void MergeSort(int[] array, int left, int right) { if (left < right) { int mid = left + (right - left) / 2; MergeSort(array, left, mid); MergeSort(array, mid + 1, right); Merge(array, left, mid, right); } } private void Merge(int[] array, int left, int mid, int right) { int n1 = mid - left + 1; int n2 = right - mid; int[] LeftArray = new int[n1]; int[] RightArray = new int[n2]; Array.Copy(array, left, LeftArray, 0, n1); Array.Copy(array, mid + 1, RightArray, 0, n2); int i = 0, j = 0, k = left; while (i < n1 && j < n2) { if (LeftArray[i] <= RightArray[j]) { array[k++] = LeftArray[i++]; } else { array[k++] = RightArray[j++]; } } while (i < n1) { array[k++] = LeftArray[i++]; } while (j < n2) { array[k++] = RightArray[j++]; } } ``` I’ve tried optimizing the array copies by using linked lists instead of arrays, but that hasn’t made much difference. I also considered using in-place sorting methods to cut down on memory allocation, but I really want to stick with merge sort for its stability. Are there any specific optimizations I can apply to reduce memory usage for large datasets? Is there a more efficient way of merging that doesn't involve creating new arrays for the left and right halves? I’m using .NET 6.0 and targeting a 64-bit environment. Any advice would be greatly appreciated! I'd really appreciate any guidance on this. This is part of a larger application I'm building. Is there a simpler solution I'm overlooking?