Abstract
The article is devoted to the problem of representing graphs in the form that is most suitable for their recording in relational databases and for subsequent efficient extracting and processing. The article analyzes various ways to describe graphs, such as adjacency and, incidence matrices, and adjacency lists. Each of them is reviewed from the point of view of their compliance with normal forms to assess the possibility of using a particular method when developing databases for storing graphs. It is shown that for such a task, each of these methods has a large number of disadvantages that lead to low efficiency of both data storing and processing. The article suggests the way to represent graphs in the form of a relational list of edges corresponding to the third normal form and allowing to eliminate the disadvantages of other methods.
Highlights
Graphs are a set of vertices and connections between them, called edges, and are abstract mathematical objects that provide a universal way to describe various structures and systems
Methods of processing graphs using standard algorithms are the basis of many modern information systems [1, 2]
Algorithms are always designed to work with a specific data structure, and the choice of the way to represent the data significantly affects the methods of the data processing and the effectiveness of these methods
Summary
Graphs are a set of vertices and connections between them, called edges, and are abstract mathematical objects that provide a universal way to describe various structures and systems. The software part of any information system has two aspects: data structures and algorithms for processing them [3] This principle is reflected in many modern information technologies, in particular, in object-oriented programming and databases. For some special cases of graphs, for example, trees, there are effective ways to represent them for writing to relational database tables that take into account the structure of such graphs and their other features [4, 5] These methods are not applicable for other types of graphs. The problem with this is that such representation methods do not comply with the principles of the data storage in relational databases [6, 7], which results in the need to perform additional transformations of the data when it is transferred from the database to the application for further processing. This raises the challenge of developing a table structure for storing graphs and corresponding methods for processing them in order to reduce the overhead of converting data from one format to another
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