program of insertion and deletion in b tree

Clearly, the B-tree allows a desired record to be located faster, assuming all other system parameters are identical. The red node from the binary tree has a depth of three while the corresponding leaf node in the B tree has a depth of one. B-Tree The image shows a binary tree for locating a particular record in a set of eight leaves. A simplified example of this principle is shown below. When there are many children per node, a record can be found by passing through fewer nodes than if there are two children per node. B-trees save time by using nodes with many branches (called children), compared with binary trees, in which each node has only two children. For example, a b-tree with a height of 2 and a branching factor of 1001 can store over one billion keys but requires at most two disk accesses to search for any node. Since disk accesses are expensive (time consuming) operations, a b-tree tries to minimize the number of disk accesses. B-trees are balanced trees that are optimized for situations when part or all of the tree must be maintained in secondary storage such as a magnetic disk. In fact, the system often spends more time retrieving data than actually processing data. Unfortunately, a magnetic disk, the most common form of secondary storage, is significantly slower than random access memory (RAM).

Instead, a relatively small portion of the data structure is maintained in primary storage, and additional data is read from secondary storage as needed. Purpose: − understand the notion of B trees − to build, in C, a B tree 1 2-3 Trees 1.1 General Presentation Laboratory Module 8 B Trees When working with large sets of data, it is often not possible or desirable to maintain the entire structure in primary storage (RAM).

Program of insertion and deletion in b tree