Tree data structures, or trees, as they are simply known in the programming world, are non-linear data structures that organize data hierarchically. Arranging data hierarchically means that the data is arranged in lower or higher levels, relative to their relative importance, authority or superiority. This practical arrangement of data makes it more accessible and data can be assessed effectively even as a cursory glance. Trees are also advantageous in that they allow us to discern relations between data and its components.
Components of a Tree
The Data Tree is comprised of a collection of nodes. Each node contains a bit of data, and is connected to other nodes via branches.Each node may or may not have a child node leading off of it.
The first node of the tree is called a root. The root node leads off to another node, where the root becomes the parent node and the second node becomes the child. Thus interrelated data are presented via parent and child nodes.The variety of nodes in a tree are connected to each other by edges. These edges manage and depict the relationship between the nodes.
The bottom nodes, the last tier of the tree, are called leaves and they do not have any children.
The height of a tree is essentially measured as the longest path one can follow to the leaf. The length, whereas, is the path to its root.
Trees are preferred over other forms of data organization, such as Arrays and Linked List,because of the following advantages of the tree structure:
- Data that naturally forms a hierarchy can be better represented through a tree.
- Sorting keys in the form of a tree makes it easier to isolate and pinpoint any particular key.
- It also functions as a workflow for compositing digital images for visual effects.