In database design, relational decomposition is the process of breaking down a complex database into smaller, simpler components in order to improve the efficiency and organization of the database. The goal of relational decomposition is to create a set of tables that are in third normal form (3NF), which means that they are free of redundancy and have a logical structure that is easy to understand and maintain.
There are several different types of relational decomposition that can be used, including horizontal decomposition, vertical decomposition, and temporal decomposition.
Horizontal decomposition involves dividing a table into smaller tables that contain a subset of the original table’s attributes. This is useful for reducing redundancy and improving the efficiency of the database, as it allows you to store related data in the same table and avoid duplicating data in multiple tables.
Vertical decomposition involves dividing a table into smaller tables that contain a subset of the original table’s rows. This is useful for improving the organization of the database and making it easier to query and update the data.
Temporal decomposition involves dividing a table into smaller tables that contain different versions of the data at different points in time. This is useful for tracking the history of data changes and allowing you to restore the database to a previous state if necessary.
To decompose a database using relational decomposition, you first need to identify the functional dependencies that exist within the database. A functional dependency is a relationship between two attributes in a database where the value of one attribute (the determinant) determines the value of another attribute (the dependent).
For example, consider a database with the following attributes:
- Employee ID (primary key)
- Employee name (determinant)
- Employee salary (dependent)
- Employee department (dependent)
In this database, the following functional dependencies exist:
- Employee ID -> Employee name
- Employee name -> Employee salary
- Employee name -> Employee department
To decompose this database into smaller, simpler tables, you can start by identifying the attributes that are related to each other and creating tables that contain those attributes. For example, you could create the following two tables:
Employee:
- Employee ID (primary key)
- Employee name (determinant)
Department:
- Employee name (determinant)
- Employee department (dependent)
This decomposition would be in third normal form (3NF) because all the attributes in each table are fully dependent on the primary key and there is no redundancy in the data.
Once you have decomposed the database into smaller tables, you can use relationships (such as foreign keys) to link the tables together and recreate the original database. This allows you to retrieve data from multiple tables in a single query and ensure that the data is consistent and accurate.
Overall, relational decomposition is an important tool for improving the efficiency and organization of a database. By breaking down a complex database into smaller, simpler tables, you can reduce redundancy, improve performance, and make it easier to maintain and update the database over time.