Table of Contents
Can there be duplicate values in binary tree?
Of course yes. One node in BST has two children which are left child and right child. Left child has smaller value than parent node, meanwhile the right child has larger or equal value of parent node. Here is an example of BST with duplicate value.
How does B Tree handle duplicates?
To handle duplicate keys in a B+ tree, as in multiple rows that have the same value, implementations typically force it to be unique by appending an additional hidden column to the table, and assigning it an auto-incrementing value when a record is created.
How do you count the number of nodes in a binary tree?
Find the left and the right height of the given Tree for the current root value and if it is equal then return the value of (2height – 1) as the resultant count of nodes. Otherwise, recursively call for the function for the left and right sub-trees and return the sum of them + 1 as the resultant count of nodes.
How to allow duplicates in a binary search tree?
So a Binary Search Tree by definition has distinct keys. How to allow duplicates where every insertion inserts one more key with a value and every deletion deletes one occurrence? A Simple Solution is to allow same keys on right side (we could also choose left side).
What is the best way to count numbers in binary search tree?
A Better Solution is to augment every tree node to store count together with regular fields like key, left and right pointers. Insertion of keys 12, 10, 20, 9, 11, 10, 12, 12 in an empty Binary Search Tree would create following. This approach has following advantages over above simple approach.
Is it possible to rotate a binary search tree?
These trees involve rotations, and a rotation may violate BST property of simple solution as a same key can be in either left side or right side after rotation. Below is implementation of normal Binary Search Tree with count with every key. This code basically is taken from code for insert and delete in BST.
What are the advantages of using bST over multiple duplicates?
1) Height of tree is small irrespective of number of duplicates. Note that most of the BST operations (search, insert and delete) have time complexity as O (h) where h is height of BST. So if we are able to keep the height small, we get advantage of less number of key comparisons. 2) Search, Insert and Delete become easier to do.