Introduction to Non-Linear Data Structures

 

Non-linear data structure

• A non-linear data structure is another important type in which data elements are not arranged sequentially; mainly, data elements are arranged in random order without forming a linear structure.
• Data elements are present at the multilevel, for example, tree.
• In trees, the data elements are arranged in the hierarchical form, whereas in graphs, the data elements are arranged in random order, using the edges and vertex.
• Multiple runs are required to traverse through all the elements completely. Traversing in a single run is impossible to traverse the whole data structure.
• Each element can have multiple paths to reach another element.
• The data structure where data items are not organized sequentially is called a non-linear data structure. In other words, data elements of the non-linear data structure could be connected to more than one element to reflect a special relationship among them.

Let us discuss some of its types:

Trees and Graphs are the types of non-linear data structures.

Tree:

• The tree is a non-linear data structure that is comprised of various nodes. The nodes in the tree data structure are arranged in hierarchical order.

• It consists of a root node corresponding to its various child nodes, present at the next level. The tree grows on a level basis, and root nodes have limited child nodes depending on the order of the tree.
• For example, in the binary tree, the order of the root node is 2, which means it can have at most 2 children per node, not more than it.
• The non-linear data structure cannot be implemented directly, and it is implemented using the linear data structure like an array and linked list.
• The tree itself is a very broad data structure and is divided into various categories like Binary tree, Binary search tree, AVL trees, Heap, max Heap, min-heap, etc.
• All the types of trees mentioned above differ based on their properties.

Graph

• A graph is a non-linear data structure with a finite number of vertices and edges, and these edges are used to connect the vertices.
• The graph itself is categorized based on some properties; if we talk about a complete graph, it consists of the vertex set, and each vertex is connected to the other vertexes having an edge between them.
• The vertices store the data elements, while the edges represent the relationship between the vertices.
• A graph is very important in various fields; the network system is represented using the graph theory and its principles in computer networks.
• Even in Maps, we consider every location a vertex, and the path derived between two locations is considered edges.
• The graph representation's main motive is to find the minimum distance between two vertexes via a minimum edge weight.