2-3 tree is a tree data structure in which every internal node (non-leaf node) has either one data element and two children or two data elements and three children. If a node contains one data element leftVal, it has two subtrees (children) namely left and middle. Whereas if a node contains two data elements leftVal and rightVal, it has three subtrees namely left, middle and right.
The main advantage with 2-3 trees is that it is balanced in nature as opposed to a binary search tree whose height in the worst case can be O(n). Due to this, the worst case time-complexity of operations such as search, insertion and deletion is as the height of a 2-3 tree is .
Search: To search a key K in given 2-3 tree T, we follow the following procedure:
- If T is empty, return False (key cannot be found in the tree).
- If current node contains data value which is equal to K, return True.
- If we reach the leaf-node and it doesn’t contain the required key value K, return False.
- If K < currentNode.leftVal, we explore the left subtree of the current node.
- Else if currentNode.leftVal < K currentNode.rightVal, we explore the right subtree of the current node.
- Else if K > currentNode.rightVal, we explore the right subtree of the current node.
Consider the following example:
Insertion: There are 3 possible cases in insertion which have been discussed below:
Case 1: Insert in a node with only one data element
Case 2: Insert in a node with two data elements whose parent contains only one data element.
Case 3: Insert in a node with two data elements whose parent also contains two data elements.
- Trie | (Insert and Search)
- K Dimensional Tree | Set 1 (Search and Insert)
- Treap | Set 2 (Implementation of Search, Insert and Delete)
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- B-Tree | Set 2 (Insert)
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