How to Map Composite Attributes?

Mapping composite attributes is a fundamental step in database design, particularly when transitioning from a conceptual model to a physical one. Composite attributes are those that can be divided into smaller sub-attributes with independent meanings.

Understanding Composite Attributes

A composite attribute is essentially a group of simple attributes. For example, an Address might be composed of Street, City, State, and Zip Code. While the Address itself is meaningful, its components also hold individual significance.

Mapping in Entity-Relationship Diagrams (ERDs)

Entity-Relationship Diagrams are a common method for mapping composite attributes in a DBMS. They use graphical symbols to represent the entities, attributes, and relationships between them.

In an ERD, composite attributes are typically represented in one of two ways:

1. Textual Grouping: As mentioned in the reference, composite attributes are often represented by grouping related attributes together and enclosing them in brackets.

   • Example: Employee (EmployeeID, Name (FirstName, LastName), Address (Street, City, State, Zip))
   • Here, Name and Address are composite attributes, broken down into their components within the parentheses.

2. Graphical Representation: Graphically in an ER diagram:

   • The entity is represented by a rectangle.
   • Attributes are represented by ovals.
   • A composite attribute is shown as an oval connected to the entity.
   • The component attributes are then shown as ovals connected to the composite attribute oval.

   This graphical method clearly illustrates the hierarchical nature of the composite attribute and its components.

Mapping to a Relational Database Schema

When you translate an ER diagram into a relational database schema (which becomes the structure of your tables), composite attributes are typically flattened. This means the composite attribute itself is not created as a single column. Instead, each of its simple components becomes a separate column in the relation (table).

Here's how the mapping works:

• Identify the composite attribute: Locate the composite attribute in your ERD (e.g., Address).
• Identify its simple components: Determine the individual attributes that make up the composite (e.g., Street, City, State, Zip).
• Create columns for each component: In the corresponding table for the entity, create a separate column for each of the simple components.

Example: Mapping the Employee entity with composite attributes to a table:

Let's revisit our Employee example with the composite attributes Name and Address.

• ERD Attributes: EmployeeID, Name (FirstName, LastName), Address (Street, City, State, Zip)

• Relational Table Columns:

  • EmployeeID (Primary Key)
  • FirstName
  • LastName
  • Street
  • City
  • State
  • Zip

In the final Employee table, you would have individual columns for FirstName, LastName, Street, City, State, and Zip instead of a single Name or Address column.

This approach simplifies querying and data manipulation in the database as each atomic piece of data is stored in its own column.

Key Takeaways:

• ERDs use grouping (often with brackets) or graphical connections to represent composite attributes conceptually.
• When moving to a relational database, composite attributes are decomposed, and each simple component becomes a separate column in the table.
• This decomposition is crucial for ensuring data is atomic and easily accessible through standard SQL queries.