How would you sort the array with very huge length?
How would you sort the array with very huge length?
How to sort a big array with many repetitions?
- Create an empty AVL Tree with count as an additional field.
- Traverse input array and do following for every element ‘arr[i]’ …..a) If arr[i] is not present in tree, then insert it and initialize count as 1.
- Do Inorder Traversal of tree.
Which sorting algorithm is faster for large array?
For large number of data sets, Insertion sort is the fastest. In the practical sorting, this case occurs rarely. Note that randomized Quicksort makes worst cases less possible, which will be the case for in-order data if the pivot point in Quicksort is chosen as the first element.
Which sorting technique can be used to sort huge GB of data in an organization with limited main memory available?
External sorting
External sorting is a term for a class of sorting algorithms that can handle massive amounts of data. External sorting is required when the data being sorted do not fit into the main memory of a computing device (usually RAM) and instead, they must reside in the slower external memory (usually a hard drive).
Which sorting algorithm is best suited for insanely huge data?
Heapsort is a good algorithm in practice, but isn’t as fast as the other algorithms in some cases because it doesn’t have good locality of reference. That said, the fact that it never degenerates and needs only O(1) auxiliary space is a huge selling point.
Why quick sort is fastest sorting algorithm?
Even though quick-sort has a worst case run time of Θ(n2), quicksort is considered the best sorting because it is VERY efficient on the average: its expected running time is Θ(nlogn) where the constants are VERY SMALL compared to other sorting algorithms.
Which is the best sorting technique?
Time Complexities of Sorting Algorithms:
| Algorithm | Best | Worst |
|---|---|---|
| Bubble Sort | Ω(n) | O(n^2) |
| Merge Sort | Ω(n log(n)) | O(n log(n)) |
| Insertion Sort | Ω(n) | O(n^2) |
| Selection Sort | Ω(n^2) | O(n^2) |