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 the partitioned element is more than k, then we recur for the left part. If index is the same as k, we have found the k-th smallest element and we return. If index is less than k, then we recur for the 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
C++14
// CPP program for implementation of QuickSelect #include <bits/stdc++.h> 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; } |
Java
// Java program of Quick Select import java.util.Arrays; class GFG { // partition function similar to quick sort // Considers last element as pivot and adds // elements with less value to the left and // high value to the right and also changes // the pivot position to its respective position // in the final array. public static int partition(int[] arr, int low, int high) { int pivot = arr[high], pivotloc = low; for (int i = low; i <= high; i++) { // inserting elements of less value // to the left of the pivot location if (arr[i] < pivot) { int temp = arr[i]; arr[i] = arr[pivotloc]; arr[pivotloc] = temp; pivotloc++; } } // swapping pivot to the final pivot location int temp = arr[high]; arr[high] = arr[pivotloc]; arr[pivotloc] = temp; return pivotloc; } // finds the kth position (of the sorted array) // in a given unsorted array i.e this function // can be used to find both kth largest and // kth smallest element in the array. // ASSUMPTION: all elements in arr[] are distinct public static int kthSmallest(int[] arr, int low, int high, int k) { // find the partition int partition = partition(arr, low, high); // if partition value is equal to the kth position, // return value at k. if (partition == k - 1) return arr[partition]; // if partition value is less than kth position, // search right side of the array. else if (partition < k - 1) return kthSmallest(arr, partition + 1, high, k); // if partition value is more than kth position, // search left side of the array. else return kthSmallest(arr, low, partition - 1, k); } // Driver Code public static void main(String[] args) { int[] array = new int[] { 10, 4, 5, 8, 6, 11, 26 }; int[] arraycopy = new int[] { 10, 4, 5, 8, 6, 11, 26 }; int kPosition = 3; int length = array.length; if (kPosition > length) { System.out.println("Index out of bound"); } else { // find kth smallest value System.out.println( "K-th smallest element in array : " + kthSmallest(arraycopy, 0, length - 1, kPosition)); } } } // This code is contributed by Saiteja Pamulapati |
Python3
# Python3 program of Quick Select # 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 def partition(arr, l, r): x = arr[r] i = l for j in range(l, r): if arr[j] <= x: arr[i], arr[j] = arr[j], arr[i] i += 1 arr[i], arr[r] = arr[r], arr[i] return i # finds the kth position (of the sorted array) # in a given unsorted array i.e this function # can be used to find both kth largest and # kth smallest element in the array. # ASSUMPTION: all elements in arr[] are distinct def kthSmallest(arr, l, r, k): # if k is smaller than number of # elements in array if (k > 0 and k <= r - l + 1): # Partition the array around last # element and get position of pivot # element in sorted array 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) print("Index out of bound") # Driver Code arr = [ 10, 4, 5, 8, 6, 11, 26 ] n = len(arr) k = 3print("K-th smallest element is ", end = "") print(kthSmallest(arr, 0, n - 1, k)) # This code is contributed by Muskan Kalra. |
C#
// C# program of Quick Select using System; class GFG { // partition function similar to quick sort // Considers last element as pivot and adds // elements with less value to the left and // high value to the right and also changes // the pivot position to its respective position // in the readonly array. static int partitions(int []arr,int low, int high) { int pivot = arr[high], pivotloc = low, temp; for (int i = low; i <= high; i++) { // inserting elements of less value // to the left of the pivot location if(arr[i] < pivot) { temp = arr[i]; arr[i] = arr[pivotloc]; arr[pivotloc] = temp; pivotloc++; } } // swapping pivot to the readonly pivot location temp = arr[high]; arr[high] = arr[pivotloc]; arr[pivotloc] = temp; return pivotloc; } // finds the kth position (of the sorted array) // in a given unsorted array i.e this function // can be used to find both kth largest and // kth smallest element in the array. // ASSUMPTION: all elements in []arr are distinct static int kthSmallest(int[] arr, int low, int high, int k) { // find the partition int partition = partitions(arr,low,high); // if partition value is equal to the kth position, // return value at k. if(partition == k) return arr[partition]; // if partition value is less than kth position, // search right side of the array. else if(partition < k ) return kthSmallest(arr, partition + 1, high, k ); // if partition value is more than kth position, // search left side of the array. else return kthSmallest(arr, low, partition - 1, k ); } // Driver Code public static void Main(String[] args) { int[] array = {10, 4, 5, 8, 6, 11, 26}; int[] arraycopy = {10, 4, 5, 8, 6, 11, 26}; int kPosition = 3; int length = array.Length; if(kPosition > length) { Console.WriteLine("Index out of bound"); } else { // find kth smallest value Console.WriteLine("K-th smallest element in array : " + kthSmallest(arraycopy, 0, length - 1, kPosition - 1)); } } } // This code is contributed by 29AjayKumar |
Javascript
<script> // Javascript program of Quick Select // partition function similar to quick sort // Considers last element as pivot and adds // elements with less value to the left and // high value to the right and also changes // the pivot position to its respective position // in the final array. function _partition(arr, low, high) { let pivot = arr[high], pivotloc = low; for (let i = low; i <= high; i++) { // inserting elements of less value // to the left of the pivot location if (arr[i] < pivot) { let temp = arr[i]; arr[i] = arr[pivotloc]; arr[pivotloc] = temp; pivotloc++; } } // swapping pivot to the final pivot location let temp = arr[high]; arr[high] = arr[pivotloc]; arr[pivotloc] = temp; return pivotloc; } // finds the kth position (of the sorted array) // in a given unsorted array i.e this function // can be used to find both kth largest and // kth smallest element in the array. // ASSUMPTION: all elements in arr[] are distinct function kthSmallest(arr, low, high, k) { // find the partition let partition = _partition(arr, low, high); // if partition value is equal to the kth position, // return value at k. if (partition == k - 1) return arr[partition]; // if partition value is less than kth position, // search right side of the array. else if (partition < k - 1) return kthSmallest(arr, partition + 1, high, k); // if partition value is more than kth position, // search left side of the array. else return kthSmallest(arr, low, partition - 1, k); } // Driver Code let array = [ 10, 4, 5, 8, 6, 11, 26]; let arraycopy = [10, 4, 5, 8, 6, 11, 26 ]; let kPosition = 3; let length = array.length; if (kPosition > length) { document.write("Index out of bound<br>"); } else { // find kth smallest value document.write( "K-th smallest element in array : "+ kthSmallest(arraycopy, 0, length - 1, kPosition)+"<br>"); } // This code is contributed by rag2127 </script> |
Output:
K-th smallest element is 6
Important Points:
- Like quicksort, it is fast in practice, but has poor worst-case performance. It is used in
- The partition process is same as QuickSort, only recursive code differs.
- 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++
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