In a binary search tree, AVL Tree, Red-Black tree etc., every node can have only one value (key) and maximum of two children but there is another type of search tree called B-Tree in which a node can store more than one value (key) and it can have more than two children. B-Tree was developed in the year of 1972 by Bayer and McCreight with the name Height Balanced m-way Search Tree. Later it was named as B-Tree.

B-Tree can be defined as follows...

Here, number of keys in a node and number of children for a node is depend on the order of the B-Tree. Every B-Tree has order.

B-Tree of Order m has the following properties...

B-Tree can be defined as follows...

**B-Tree is a self-balanced search tree with multiple keys in every node and more than two children for every node.**Here, number of keys in a node and number of children for a node is depend on the order of the B-Tree. Every B-Tree has order.

B-Tree of Order m has the following properties...

- Property #1 - All the leaf nodes must be at same level.
- Property #2 - All nodes except root must have at least [m/2]-1 keys and maximum of m-1 keys.
- Property #3 - All non leaf nodes except root (i.e. all internal nodes) must have at least m/2 children.
- Property #4 - If the root node is a non leaf node, then it must have at least 2 children.
- Property #5 - A non leaf node with n-1 keys must have n number of children.
- Property #6 - All the key values within a node must be in Ascending Order.

For example, B-Tree of Order 4 contains maximum 3 key values in a node and maximum 4 children for a node.

**Example**

_{}

^{}

**Operations on a B-Tree**

The following operations are performed on a B-Tree...

- Search
- Insertion
- Deletion

**Search Operation in B-Tree**

In a B-Ttree, the search operation is similar to that of Binary Search Tree. In a Binary search tree, the search process starts from the root node and every time we make a 2-way decision (we go to either left subtree or right subtree). In B-Tree also search process starts from the root node but every time we make n-way decision where n is the total number of children that node has. In a B-Ttree, the search operation is performed with O(log n) time complexity. The search operation is performed as follows...

- Step 1: Read the search element from the user
- Step 2: Compare, the search element with first key value of root node in the tree.
- Step 3: If both are matching, then display "Given node found!!!" and terminate the function
- Step 4: If both are not matching, then check whether search element is smaller or larger than that key value.
- Step 5: If search element is smaller, then continue the search process in left subtree.
- Step 6: If search element is larger, then compare with next key value in the same node and repeat step 3, 4, 5 and 6 until we found exact match or comparison completed with last key value in a leaf node.
- Step 7: If we completed with last key value in a leaf node, then display "Element is not found" and terminate the function.

**Insertion Operation in B-Tree**

In a B-Tree, the new element must be added only at leaf node. That means, always the new keyValue is attached to leaf node only. The insertion operation is performed as follows...

- Step 1: Check whether tree is Empty.
- Step 2: If tree is Empty, then create a new node with new key value and insert into the tree as a root node.
- Step 3: If tree is Not Empty, then find a leaf node to which the new key value cab be added using Binary Search Tree logic.
- Step 4: If that leaf node has an empty position, then add the new key value to that leaf node by maintaining ascending order of key value within the node.
- Step 5: If that leaf node is already full, then split that leaf node by sending middle value to its parent node. Repeat the same until sending value is fixed into a node.
- Step 6: If the splitting is occurring to the root node, then the middle value becomes new root node for the tree and the height of the tree is increased by one.

**Example**

_{}

^{}

## No comments:

## Post a Comment