K’th Largest Element in BST when modification to BST is not allowed
Given a Binary Search Tree (BST) and a positive integer k, find the k’th largest element in the Binary Search Tree.
For example, in the following BST, if k = 3, then output should be 14, and if k = 5, then output should be 10.
We have discussed two methods in this post. The method 1 requires O(n) time. The method 2 takes O(h) time where h is height of BST, but requires augmenting the BST (storing count of nodes in left subtree with every node).
Can we find k’th largest element in better than O(n) time and no augmentation?
Approach:
- The idea is to do reverse inorder traversal of BST. Keep a count of nodes visited.
- The reverse inorder traversal traverses all nodes in decreasing order, i.e, visit the right node then centre then left and continue traversing the nodes recursively.
- While doing the traversal, keep track of the count of nodes visited so far.
- When the count becomes equal to k, stop the traversal and print the key.
C++
// C++ program to find k'th largest element in BST#include<bits/stdc++.h>using namespace std; struct Node{ int key; Node *left, *right;}; // A utility function to create a new BST nodeNode *newNode(int item){ Node *temp = new Node; temp->key = item; temp->left = temp->right = NULL; return temp;} // A function to find k'th largest element in a given tree.void kthLargestUtil(Node *root, int k, int &c){ // Base cases, the second condition is important to // avoid unnecessary recursive calls if (root == NULL || c >= k) return; // Follow reverse inorder traversal so that the // largest element is visited first kthLargestUtil(root->right, k, c); // Increment count of visited nodes c++; // If c becomes k now, then this is the k'th largest if (c == k) { cout << "K'th largest element is " << root->key << endl; return; } // Recur for left subtree kthLargestUtil(root->left, k, c);} // Function to find k'th largest elementvoid kthLargest(Node *root, int k){ // Initialize count of nodes visited as 0 int c = 0; // Note that c is passed by reference kthLargestUtil(root, k, c);} /* A utility function to insert a new node with given key in BST */Node* insert(Node* node, int key){ /* If the tree is empty, return a new node */ if (node == NULL) return newNode(key); /* Otherwise, recur down the tree */ if (key < node->key) node->left = insert(node->left, key); else if (key > node->key) node->right = insert(node->right, key); /* return the (unchanged) node pointer */ return node;} // Driver Program to test above functionsint main(){ /* Let us create following BST 50 / \ 30 70 / \ / \ 20 40 60 80 */ Node *root = NULL; root = insert(root, 50); insert(root, 30); insert(root, 20); insert(root, 40); insert(root, 70); insert(root, 60); insert(root, 80); int c = 0; for (int k=1; k<=7; k++) kthLargest(root, k); return 0;} |
Java
// Java code to find k'th largest element in BST // A binary tree nodeclass Node { int data; Node left, right; Node(int d) { data = d; left = right = null; }} class BinarySearchTree { // Root of BST Node root; // Constructor BinarySearchTree() { root = null; } // function to insert nodes public void insert(int data) { this.root = this.insertRec(this.root, data); } /* A utility function to insert a new node with given key in BST */ Node insertRec(Node node, int data) { /* If the tree is empty, return a new node */ if (node == null) { this.root = new Node(data); return this.root; } if (data == node.data) { return node; } /* Otherwise, recur down the tree */ if (data < node.data) { node.left = this.insertRec(node.left, data); } else { node.right = this.insertRec(node.right, data); } return node; } // class that stores the value of count public class count { int c = 0; } // utility function to find kth largest no in // a given tree void kthLargestUtil(Node node, int k, count C) { // Base cases, the second condition is important to // avoid unnecessary recursive calls if (node == null || C.c >= k) return; // Follow reverse inorder traversal so that the // largest element is visited first this.kthLargestUtil(node.right, k, C); // Increment count of visited nodes C.c++; // If c becomes k now, then this is the k'th largest if (C.c == k) { System.out.println(k + "th largest element is " + node.data); return; } // Recur for left subtree this.kthLargestUtil(node.left, k, C); } // Method to find the kth largest no in given BST void kthLargest(int k) { count c = new count(); // object of class count this.kthLargestUtil(this.root, k, c); } // Driver function public static void main(String[] args) { BinarySearchTree tree = new BinarySearchTree(); /* Let us create following BST 50 / \ 30 70 / \ / \ 20 40 60 80 */ tree.insert(50); tree.insert(30); tree.insert(20); tree.insert(40); tree.insert(70); tree.insert(60); tree.insert(80); for (int i = 1; i <= 7; i++) { tree.kthLargest(i); } }} // This code is contributed by Kamal Rawal |
Python3
# Python3 program to find k'th largest # element in BST class Node: # Constructor to create a new node def __init__(self, data): self.key = data self.left = None self.right = None # A function to find k'th largest # element in a given tree. def kthLargestUtil(root, k, c): # Base cases, the second condition # is important to avoid unnecessary # recursive calls if root == None or c[0] >= k: return # Follow reverse inorder traversal # so that the largest element is # visited first kthLargestUtil(root.right, k, c) # Increment count of visited nodes c[0] += 1 # If c becomes k now, then this is # the k'th largest if c[0] == k: print("K'th largest element is", root.key) return # Recur for left subtree kthLargestUtil(root.left, k, c) # Function to find k'th largest element def kthLargest(root, k): # Initialize count of nodes # visited as 0 c = [0] # Note that c is passed by reference kthLargestUtil(root, k, c) # A utility function to insert a new # node with given key in BST */def insert(node, key): # If the tree is empty, # return a new node if node == None: return Node(key) # Otherwise, recur down the tree if key < node.key: node.left = insert(node.left, key) elif key > node.key: node.right = insert(node.right, key) # return the (unchanged) node pointer return node # Driver Codeif __name__ == '__main__': # Let us create following BST # 50 # / \ # 30 70 # / \ / \ # 20 40 60 80 */ root = None root = insert(root, 50) insert(root, 30) insert(root, 20) insert(root, 40) insert(root, 70) insert(root, 60) insert(root, 80) for k in range(1,8): kthLargest(root, k) # This code is contributed by PranchalK |
C#
using System; // C# code to find k'th largest element in BST // A binary tree node public class Node{ public int data; public Node left, right; public Node(int d) { data = d; left = right = null; }} public class BinarySearchTree{ // Root of BST public Node root; // Constructor public BinarySearchTree() { root = null; } // function to insert nodes public virtual void insert(int data) { this.root = this.insertRec(this.root, data); } /* A utility function to insert a new node with given key in BST */ public virtual Node insertRec(Node node, int data) { /* If the tree is empty, return a new node */ if (node == null) { this.root = new Node(data); return this.root; } if (data == node.data) { return node; } /* Otherwise, recur down the tree */ if (data < node.data) { node.left = this.insertRec(node.left, data); } else { node.right = this.insertRec(node.right, data); } return node; } // class that stores the value of count public class count { private readonly BinarySearchTree outerInstance; public count(BinarySearchTree outerInstance) { this.outerInstance = outerInstance; } internal int c = 0; } // utility function to find kth largest no in // a given tree public virtual void kthLargestUtil(Node node, int k, count C) { // Base cases, the second condition is important to // avoid unnecessary recursive calls if (node == null || C.c >= k) { return; } // Follow reverse inorder traversal so that the // largest element is visited first this.kthLargestUtil(node.right, k, C); // Increment count of visited nodes C.c++; // If c becomes k now, then this is the k'th largest if (C.c == k) { Console.WriteLine(k + "th largest element is " + node.data); return; } // Recur for left subtree this.kthLargestUtil(node.left, k, C); } // Method to find the kth largest no in given BST public virtual void kthLargest(int k) { count c = new count(this); // object of class count this.kthLargestUtil(this.root, k, c); } // Driver function public static void Main(string[] args) { BinarySearchTree tree = new BinarySearchTree(); /* Let us create following BST 50 / \ 30 70 / \ / \ 20 40 60 80 */ tree.insert(50); tree.insert(30); tree.insert(20); tree.insert(40); tree.insert(70); tree.insert(60); tree.insert(80); for (int i = 1; i <= 7; i++) { tree.kthLargest(i); } }} // This code is contributed by Shrikant13 |
Output:
K'th largest element is 80 K'th largest element is 70 K'th largest element is 60 K'th largest element is 50 K'th largest element is 40 K'th largest element is 30 K'th largest element is 20
Complexity Analysis:
- Time Complexity: O(h + k).
The code first traverses down to the rightmost node which takes O(h) time, then traverses k elements in O(k) time. Therefore overall time complexity is O(h + k). - Auxiliary Space: O(1).
As no extra space is needed.
This article is contributed by Chirag Sharma. Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above
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