The Entity Relationship Model - Learning MySQL [Book]
Learn how to handle many-to-many relationships in database design with an example of creating a database Handling a one-to-one relationship or one-or- many relationship can be done pretty simply. 6, Programming. 7, Law. 8, Commerce. 9, Physical Education . Issues/Permissions index definition. This definition explains the meaning of a relational database and how it stores chief privacy offer and legal engineer at Immuta Inc., on data governance called a relation, in a relational database contains one or more data. Relation Definition. • Database is collection of Database schema: set of all relation schemas. 4 Ensures only legal database instances exist. • Simplest form.
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.
What is Relation? - Definition from Techopedia
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.
- Learning MySQL by Hugh E. Williams, Saied M.M. Tahaghoghi
- Relational model
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. 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.
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.
The ER diagram representation of the customer and product entities, and the sale relationship between them. Partial and Total Participation Relationships between entities can be optional or compulsory. In our example, we could decide that a person is considered to be a customer only if they have bought a product.
On the other hand, we could say that a customer is a person whom we know about and whom we hope might buy something—that is, we can have people listed as customers in our database who never buy a product. These are referred to as the participation constraints of the relationship. In an ER diagram, we indicate total participation with a double line between the entity box and the relationship diamond. Alternatives[ edit ] Other models are the hierarchical model and network model. Some systems using these older architectures are still in use today in data centers with high data volume needs, or where existing systems are so complex and abstract that it would be cost-prohibitive to migrate to systems employing the relational model.
Also of note are newer object-oriented databases. Implementation[ edit ] There have been several attempts to produce a true implementation of the relational database model as originally defined by Codd and explained by DateDarwen and others, but none have been popular successes so far.
The relational model was the first database model to be described in formal mathematical terms. Hierarchical and network databases existed before relational databases, but their specifications were relatively informal.
After the relational model was defined, there were many attempts to compare and contrast the different models, and this led to the emergence of more rigorous descriptions of the earlier models; though the procedural nature of the data manipulation interfaces for hierarchical and network databases limited the scope for formalization.
Codd as a general model of data, and subsequently promoted by Chris Date and Hugh Darwen among others. In The Third Manifesto first published in Date and Darwen attempt to show how the relational model can allegedly accommodate certain "desired" object-oriented features.
SQL's NULL construct was intended to be part of a three-valued logic system, but fell short of that due to logical errors in the standard and in its implementations. In the mathematical model, reasoning about such data is done in two-valued predicate logicmeaning there are two possible evaluations for each proposition: Data are operated upon by means of a relational calculus or relational algebrathese being equivalent in expressive power.
The relational model of data permits the database designer to create a consistent, logical representation of information. Consistency is achieved by including declared constraints in the database design, which is usually referred to as the logical schema.
The theory includes a process of database normalization whereby a design with certain desirable properties can be selected from a set of logically equivalent alternatives. The access plans and other implementation and operation details are handled by the DBMS engine, and are not reflected in the logical model. The basic relational building block is the domain or data typeusually abbreviated nowadays to type.
A tuple is an ordered set of attribute values. An attribute is an ordered pair of attribute name and type name. An attribute value is a specific valid value for the type of the attribute. This can be either a scalar value or a more complex type. A relation consists of a heading and a body. A heading is a set of attributes.
How to Handle a Many-to-Many Relationship in Database Design
A body of an n-ary relation is a set of n-tuples. The heading of the relation is also the heading of each of its tuples. A relation is defined as a set of n-tuples. In both mathematics and the relational database model, a set is an unordered collection of unique, non-duplicated items, although some DBMSs impose an order to their data.
In mathematics, a tuple has an order, and allows for duplication. Codd originally defined tuples using this mathematical definition. Codd 's great insights that using attribute names instead of an ordering would be so much more convenient in general in a computer language based on relations[ citation needed ].
This insight is still being used today.
Though the concept has changed, the name "tuple" has not. An immediate and important consequence of this distinguishing feature is that in the relational model the Cartesian product becomes commutative. A table is an accepted visual representation of a relation; a tuple is similar to the concept of a row.
A relvar is a named variable of some specific relation type, to which at all times some relation of that type is assigned, though the relation may contain zero tuples.
The basic principle of the relational model is the Information Principle: In accordance with this Principle, a relational database is a set of relvars and the result of every query is presented as a relation. The consistency of a relational database is enforced, not by rules built into the applications that use it, but rather by constraintsdeclared as part of the logical schema and enforced by the DBMS for all applications.
In practice, several useful shorthands are expected to be available, of which the most important are candidate key really, superkey and foreign key constraints. Interpretation[ edit ] To fully appreciate the relational model of data it is essential to understand the intended interpretation of a relation. The body of a relation is sometimes called its extension. This is because it is to be interpreted as a representation of the extension of some predicatethis being the set of true propositions that can be formed by replacing each free variable in that predicate by a name a term that designates something.
There is a one-to-one correspondence between the free variables of the predicate and the attribute names of the relation heading. Each tuple of the relation body provides attribute values to instantiate the predicate by substituting each of its free variables. The result is a proposition that is deemed, on account of the appearance of the tuple in the relation body, to be true.
Contrariwise, every tuple whose heading conforms to that of the relation, but which does not appear in the body is deemed to be false. This assumption is known as the closed world assumption: For example, the absence of the tuple 'John', 'Spanish' from a table of language skills cannot necessarily be taken as evidence that John does not speak Spanish. For a formal exposition of these ideas, see the section Set-theoretic Formulationbelow.
Application to databases[ edit ] A data type as used in a typical relational database might be the set of integers, the set of character strings, the set of dates, or the two boolean values true and false, and so on. The corresponding type names for these types might be the strings "int", "char", "date", "boolean", etc.
It is important to understand, though, that relational theory does not dictate what types are to be supported; indeed, nowadays provisions are expected to be available for user-defined types in addition to the built-in ones provided by the system. Attribute is the term used in the theory for what is commonly referred to as a column.
Similarly, table is commonly used in place of the theoretical term relation though in SQL the term is by no means synonymous with relation. A table data structure is specified as a list of column definitions, each of which specifies a unique column name and the type of the values that are permitted for that column.