# Quickselect Algorithm

Quickselect is a selection algorithm to find the k-th smallest element in an unordered list. It is related to the quick sort sorting algorithm.

Examples:

```Input: arr[] = {7, 10, 4, 3, 20, 15}
k = 3
Output: 7

Input: arr[] = {7, 10, 4, 3, 20, 15}
k = 4
Output: 10
```

The algorithm is similar to QuickSort. The difference is, instead of recurring for both sides (after finding pivot), it recurs only for the part that contains the k-th smallest element. The logic is simple, if index of partitioned element is more than k, then we recur for left part. If index is same as k, we have found the k-th smallest element and we return. If index is less than k, then we recur for right part. This reduces the expected complexity from O(n log n) to O(n), with a worst case of O(n^2).

```function quickSelect(list, left, right, k)

if left = right
return list[left]

Select a pivotIndex between left and right

pivotIndex := partition(list, left, right,
pivotIndex)
if k = pivotIndex
return list[k]
else if k < pivotIndex
right := pivotIndex - 1
else
left := pivotIndex + 1
```

 `// CPP program for implementation of QuickSelect ` `#include ` `using` `namespace` `std; ` ` `  `// Standard partition process of QuickSort(). ` `// It considers the last element as pivot ` `// and moves all smaller element to left of ` `// it and greater elements to right ` `int` `partition(``int` `arr[], ``int` `l, ``int` `r) ` `{ ` `    ``int` `x = arr[r], i = l; ` `    ``for` `(``int` `j = l; j <= r - 1; j++) { ` `        ``if` `(arr[j] <= x) { ` `            ``swap(arr[i], arr[j]); ` `            ``i++; ` `        ``} ` `    ``} ` `    ``swap(arr[i], arr[r]); ` `    ``return` `i; ` `} ` ` `  `// This function returns k'th smallest  ` `// element in arr[l..r] using QuickSort  ` `// based method.  ASSUMPTION: ALL ELEMENTS ` `// IN ARR[] ARE DISTINCT ` `int` `kthSmallest(``int` `arr[], ``int` `l, ``int` `r, ``int` `k) ` `{ ` `    ``// If k is smaller than number of  ` `    ``// elements in array ` `    ``if` `(k > 0 && k <= r - l + 1) { ` ` `  `        ``// Partition the array around last  ` `        ``// element and get position of pivot  ` `        ``// element in sorted array ` `        ``int` `index = partition(arr, l, r); ` ` `  `        ``// If position is same as k ` `        ``if` `(index - l == k - 1) ` `            ``return` `arr[index]; ` ` `  `        ``// If position is more, recur  ` `        ``// for left subarray ` `        ``if` `(index - l > k - 1)  ` `            ``return` `kthSmallest(arr, l, index - 1, k); ` ` `  `        ``// Else recur for right subarray ` `        ``return` `kthSmallest(arr, index + 1, r,  ` `                            ``k - index + l - 1); ` `    ``} ` ` `  `    ``// If k is more than number of  ` `    ``// elements in array ` `    ``return` `INT_MAX; ` `} ` ` `  `// Driver program to test above methods ` `int` `main() ` `{ ` `    ``int` `arr[] = { 10, 4, 5, 8, 6, 11, 26 }; ` `    ``int` `n = ``sizeof``(arr) / ``sizeof``(arr[0]); ` `    ``int` `k = 3; ` `    ``cout << ``"K-th smallest element is "`  `        ``<< kthSmallest(arr, 0, n - 1, k); ` `    ``return` `0; ` `} `

Output:

```K-th smallest element is 6
```

Important Points:

1. Like quicksort, it is fast in practice, but has poor worst-case performance. It is used in
2. The partition process is same as QuickSort, only recursive code differs.
3. There exists an algorithm that finds k-th smallest element in O(n) in worst case, but QuickSelect performs better on average.

Related C++ function : std::nth_element in C++

This article is contributed by Sahil Chhabra . If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.

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