However, given the dominant market presence of the relational model, most of the rules to data model components, you identify entities, attributes, relationships The use of a proper naming convention will improve the data model's ability to to represent complex data relationships more effectively than the hierarchical. An entity type E (or a relationship type R) has attributes representing the . Generalization is the result of taking the union of two or more. (lower level) entity . entity set. ◇ Attributes are simple values, e.g. integers or character strings, not structs, sets, ◇A relationship connects two or more . Note convention: arrow.
A student and a course are entities, while an enrollment is a relationship between a student and a course. Similarly, an inventory and sales database might store information about products, customers, and sales. A product and a customer are entities, while a sale is a relationship between a customer and a product. A popular approach to conceptual design uses the Entity Relationship ER model, which helps transform the requirements into a formal description of the entities and relationships that appear in the database.
In the ER diagram, an entity set is represented by a rectangle containing the entity name. An entity set is represented by a named rectangle We typically use the database to store certain characteristics, or attributes, of the entities. In a sales database, we could store the name, email address, postal address, and telephone number for each customer. Attributes describe the entity they belong to.
An attribute may be formed from smaller parts; for example, a postal address is composed of a street number, city, ZIP code, and country. Some attributes can have multiple values for a given entity. For example, a customer could provide several telephone numbers, so the telephone number attribute is multivalued.
Entity–relationship model - Wikipedia
Attributes help distinguish one entity from other entities of the same type. We could use the name attribute to distinguish between customers, but this could be an inadequate solution because several customers could have identical names.
To be able to tell them apart, we need an attribute or a minimal combination of attributes guaranteed to be unique to each individual customer.
The identifying attribute or attributes form a key. In our example, we can assume that no two customers have the same email address, so the email address can be the key. However, we need to think carefully about the implications of our choices. For example, if we decide to identify customers by their email address, it would be hard to allow a customer to have multiple email addresses.
Any applications we build to use this database might treat each email address as a separate person, and it might be hard to adapt everything to allow people to have multiple email addresses. Clearly, there may be several possible keys that could be used to identify an entity; we choose one of the alternative, or candidate, keys to be our main, or primary, key.
You usually make this choice based on how confident you are that the attribute will be non-empty and unique for each individual entity, and on how small the key is shorter keys are faster to maintain and use. Attributes comprising the primary key are shown underlined.
The parts of any composite attributes are drawn connected to the oval of the composite attribute, and multivalued attributes are shown as double-lined ovals.
Similarly, a product price could be a positive rational number.
Attributes can be empty; for example, some customers may not provide their telephone numbers. You should think carefully when classifying an attribute as multivalued: The sales database requirements may specify that a product has a name and a price.
The Entity Relationship Model - Learning MySQL [Book]
To distinguish between products, we can assign a unique product ID number to each item we stock; this would be the primary key. Each product entity would have name, price, and product ID attributes. The ER diagram representation of the product entity Representing Relationships Entities can participate in relationships with other entities.
For example, a customer can buy a product, a student can take a course, an artist can record an album, and so on. Like entities, relationships can have attributes: Our database could then record each sale and tell us, for example, that at 3: For example, each customer can buy any number of products, and each product can be bought by any number of customers. This is known as a many-to-many relationship.
We can also have one-to-many relationships. For example, one person can have several credit cards, but each credit card belongs to just one person. Looking at it the other way, a one-to-many relationship becomes a many-to-one relationship; for example, many credit cards belong to a single person.
Finally, the serial number on a car engine is an example of a one-to-one relationship; each engine has just one serial number, and each serial number belongs to just one engine. We often use the shorthand terms 1: N for one-to-one, one-to-many, and many-to-many relationships, respectively. The number of entities on either side of a relationship the cardinality of the relationship define the key constraints of the relationship.
There are many relationships that may at first seem to be one-to-one, but turn out to be more complex.
Learning MySQL by Hugh E. Williams, Saied M.M. Tahaghoghi
For example, people sometimes change their names; in some applications, such as police databases, this is of particular interest, and so it may be necessary to model a many-to-many relationship between a person entity and a name entity. Redesigning a database can be time-consuming if you assume a relationship is simpler than it really is.
In an ER diagram, we represent a relationship set with a named diamond. The cardinality of the relationship is often indicated alongside the relationship diamond; this is the style we use in this book. With this notation, relationships cannot have attributes. Where necessary, relationships are promoted to entities in their own right: Model usability issues[ edit ] You can help by adding to it.
February In using a modeled database, users can encounter two well known issues where the returned results mean something other than the results assumed by the query author. The first is the 'fan trap'. It occurs with a master table that links to multiple tables in a one-to-many relationship. The issue derives its name from the way the model looks when it's drawn in an entity—relationship diagram: This type of model looks similar to a star schemaa type of model used in data warehouses.
When trying to calculate sums over aggregates using standard SQL over the master table, unexpected and incorrect results. The solution is to either adjust the model or the SQL.
This issue occurs mostly in databases for decision support systems, and software that queries such systems sometimes includes specific methods for handling this issue.
The second issue is a 'chasm trap'.
A chasm trap occurs when a model suggests the existence of a relationship between entity types, but the pathway does not exist between certain entity occurrences. For example, a Building has one-or-more Rooms, that hold zero-or-more Computers.
One would expect to be able to query the model to see all the Computers in the Building. However, Computers not currently assigned to a Room because they are under repair or somewhere else are not shown on the list. Another relation between Building and Computers is needed to capture all the computers in the building.
This last modelling issue is the result of a failure to capture all the relationships that exist in the real world in the model.
See Entity-Relationship Modelling 2 for details. Entity—relationships and semantic modeling[ edit ] Semantic model[ edit ] A semantic model is a model of concepts, it is sometimes called a "platform independent model".entity framework code first primary key convention
It is an intensional model. At the latest since Carnapit is well known that: The first part comprises the embedding of a concept in the world of concepts as a whole, i.