We have covered the concepts of relational databases in "Introduction to . ER diagram notation for an attribute domain (StudentGrade) of an entity type (student ) . For example, we can have two binary relationship types associating the. The entity relationship (ER) data model has existed for over 35 years. It is well suited ER models, also called an ER schema, are represented by ER diagrams . ER modelling .. Example of mapping an M:N binary relationship type. For each . A relationship type is illustrated in an ERD using a diamond symbol. Consider the two entity types and is referred to as a binary relationship. Below is a ternary.
It helps us understand what kind of information we want to store and what kind of relationships there are. It is imperative that this diagram is easy to read and understand. The number of entities in a relationship is the arity of this relationship.
The aim of this article is to give some examples and show how big an impact the arity of relationships has on not only the readability of the diagram, but also the database itself. The most common types of relationships are: Unary one entity is invloved in the relationship. Binary two entities are involved in the relationship. Unary relationship type A Unary relationship between entities in a single entity type is presented on the picture below. As we see, a person can be in the relationship with another person, such as: To simplify the analysis, we assume that the database only stores results related to this experiment over a period of several years.
Entity An entity is a real-world item or concept that exists on its own. In our example, a particular student such as, "Emanuel Vagas"team, lab section, or experiment is an entity.
The set of all possible values for an entity, such as all possible students, is the entity type. In an ER model, we diagram an entity type as a rectangle containing the type name, such as student see Figure 2.
Definition An entity is a real-world item or concept that exists on its own. The set of all possible values for an entity is the entity type.
Entity Relationship Diagram
ER diagram notation for entity student Attribute Each entity has attributes, or particular properties that describe the entity. For example, student Emanuel Vagas has properties of his own Student Identification number, name, and grade.
A particular value of an attribute, such as 93 for the grade, is a value of the attribute. Most of the data in a database consists of values of attributes. The set of all possible values of an attribute, such as integers from 0 to for a grade, is the attribute domain.
In an ER model, an attribute name appears in an oval that has a line to the corresponding entity box, such as in Figure 3. Definition An attribute of an entity is a particular property that describes the entity.
The set of all possible values of an attribute is the attribute domain.
N-ary relationship types
Sometimes the value of an attribute is unknown or missing, and sometimes a value is not applicable. In such cases, the attribute can have the special value of null. For example, until the professor grades a laboratory assignment, the team grade is missing or null. Definition Null is the special attribute value that indicates an unknown or missing value. An attribute can be simple or composite.
ER Diagram Representation
A simple attribute, such as grade, is one component that is atomic. If we consider the name in two parts, last name and first name, then the name attribute is a composite. A composite attribute, such as "Emanuel Vagas", has multiple components, such as "Emanuel" and "Vagas"; and each component is atomic or composite. We illustrate this composite nature in the ER model by branching off the component attributes, such as in Figure 4.
We use all the leaf attributes; composite attributes are represented by their ungrouped components. Keys are also declared. Attributes that were earlier pushed into relationships are not yet included. We pick one of the two -- say S -- and add to S a column that represents the primary key of T, and all the attributes of R. It is better to choose as S the entity that has total or at least closer to total participation in R.
For example, the manages relationship between departments and employees is 1: We also add a foreign key constraint to S, on the new attribute, referring to the primary key of T. One alternative is to merge S and T into a single relationship; this makes sense only if both have total participation in R.
This means that S and T each have the same number of records, and each record s in S corresponds to exactly one t in T. We now add T's key to S as an attribute with foreign-key constraint. We must add T's key to S; we cannot do it the other way around. This might be more efficient if only a few s in S participate in the relationship; otherwise we would have many NULLs in the T-column of S. N relationships Here we must create a table R of tuples including the key of S skthe key of T tkand any attributes of R; we can not push the data into either S or T.
The sk column of R should have a foreign key constraint referring to the key column of S, and the tk column of R should similarly have a foreign key constraint to the key column of T. Again, we would have an appropriate foreign key constraint back to the original table.
Make this a foreign key in E1.