Design issues with constraints of E-R model
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The document explains the entity-relationship (E-R) model used in database design, introducing key concepts such as entity sets, relationship sets, and attributes. It details the basic design considerations, including the differences between entity sets and attributes, the significance of relationship cardinalities, and constraints like mapping and participation constraints. The document also addresses design issues related to the representation of object relationships in a database schema.
Design issues with constraints of E-R model
- 1. Database Management System Design Issues With Constraints Of E-R Model
- 2. What is an E-R Model? o An entity–relationship model (ER model) describes inter-related things of interest in a specific domain of knowledge. An ER model is composed of entity types (which classify the things of interest) and specifies relationships that can exist between instances of those entity types. o The entity–relationship model (ER model) was developed to facilitate database design by allowing specification of an enterprise schema that represents the overall logical structure of a database. o Entity–relationship modeling was developed for database design by Peter Chen and published in a 1976 paper. However, variants of the idea existed previously. o The E-R model is very useful in mapping the meanings and interactions of real-world enterprises onto a conceptual schema. Because of this usefulness, many database-design tools draw on concepts from the E-R model. The E-R data model employs three basic concepts: entity sets, relationship sets, and attributes. o In software engineering an ER model is commonly formed to represent things that a business needs to remember in order to perform business processes. Consequently, the ER model becomes an abstract data model that defines a data or information structure that can be implemented in a database, typically a relational database.
- 3. Entity Sets o An entity is a “thing” or “object” in the real world that is distinguishable from all other objects. For example, each person in a university is an entity. o An entity has a set of properties, and the values for some set of properties may uniquely identify an entity. o For instance, a person may have a student_id property whose value uniquely identifies that person. Thus, the value 1604-1010-7121 for student_id would uniquely identify one particular student in the university. o An entity set is a set of entities of the same type that share the same properties, or attributes. o The set of all people who are instructors at a given university, for example, can be defined as the entity set instructor. Similarly, the entity set employee might represent the set of all employees in the company.
- 4. o Below are the entity sets instructor & student.
- 5. Relationship Sets o A relationship is an association among several entities. For example, we can define a relationship advisor that associates instructor Katz with student Shankar. This relationship specifies that Katz is an advisor to student Shankar. o A relationship set is a set of relationships of the same type. Formally, it is a mathematical relation on n ≥ 2 (possibly non distinct) entity sets. If E1, E2, . . . , En are entity sets, then a relationship set R is a subset of {(e1, e2, . . . , en) | e1 ∈ E1, e2 ∈ E2, . . . , en ∈ En}, where (e1, e2, . . . , en) is a relationship. o Considering the two entity sets instructor and student, we define the relationship set advisor to denote the association between instructors and students.
- 6. Attributes o For each attribute, there is a set of permitted values, called the domain, or value set, of that attribute. The domain of attribute course_id might be the set of all text strings of a certain length. Similarly, the domain of attribute semester might be strings from the set {Fall, Winter, Spring, Summer}. o An attribute, as used in the E-R model, can be characterized by the following attribute types:- 1. Simple and composite attributes. In our examples thus far, the attributes have been simple; which cannot be divided into subparts. Composite attributes, on the other hand, can be divided into subparts (that is, other attributes). For example, an attribute name could be structured as a composite attribute consisting of first name, middle initial, and last name.
- 7. 2. Single-valued and multivalued attributes. The attributes in our examples all have a single value for a particular entity. For instance, the student ID attribute for a specific student entity refers to only one student ID. Such attributes are said to be single valued. There may be instances where an attribute has a set of values for a specific entity. Suppose we add to the instructor entity set a phone number attribute. An instructor may have zero, one, or several phone numbers, and different instructors may have different numbers of phones. This type of attribute is said to be multivalued. 3. Derived attribute. The value for this type of attribute can be derived from the values of other related attributes or entities. For instance, let us say that the instructor entity set has an attribute students advised, which represents how many students an instructor advices. We can derive the value for this attribute by counting the number of student entities associated with that instructor. 4. Null attribute. An attribute takes a null value when an entity does not have a value for it. The null value may indicate “not applicable”—that is, that the value does not exist for the entity. For example, one may have no middle name.
- 8. Constraints o An E-R enterprise schema may define certain constraints to which the contents of a database must conform. o Types of constraints are:- 1. Mapping Constraints (Cardinalities) o Mapping cardinalities, or cardinality ratios, express the number of entities to which another entity can be associated via a relationship set. o Mapping cardinalities are most useful in describing binary relationship sets, although they can contribute to the description of relationship sets that involve more than two entity sets. o In this section, we shall concentrate on only binary relationship sets. o For a binary relationship set R between entity sets A and B, the mapping cardinality must be one of the following:
- 9. • One-to-one. An entity in A is associated with at most one entity in B, and an entity in B is associated with at most one entity in A. • One-to-many. An entity in A is associated with any number (zero or more) of entities in B. An entity in B, however, can be associated with at most one entity in A.
- 10. • Many-to-one. An entity in A is associated with at most one entity in B. An entity in B, however, can be associated with any number (zero or more) of entities in A. • Many-to-many. An entity in A is associated with any number (zero or more) of entities in B, and an entity in B is associated with any number (zero or more) of entities in A.
- 11. 2. Participation Constraints o The participation of an entity set E in a relationship set R is said to be total if every entity in E participates in at least one relationship in R. o If only some entities in E participate in relationships in R, the participation of entity set E in relationship R is said to be partial. o The participation of B in the relationship set is total while the participation of A in the relationship set is partial. The participation of both A and B in the relationship set are total. o For example, we expect every student entity to be related to at least one instructor through the advisor relationship. Therefore the participation of student in the relationship set advisor is total. o In contrast, an instructor need not advise any students. Hence, it is possible that only some of the instructor entities are related to the student entity set through the advisor relationship, and the participation of instructor in the advisor relationship set is therefore partial.
- 12. 3. Key Constraints o The values of the attribute values of an entity must be such that they can uniquely identify the entity. In other words, no two entities in an entity set are allowed to have exactly the same value for all attributes. o The notion of a key for a relation schema applies directly to entity sets. That is, a key for an entity is a set of attributes that suffice to distinguish entities from each other. o The concepts of super key, candidate key, and primary key are applicable to entity sets just as they are applicable to relation schemas. o Keys also help to identify relationships uniquely, and thus distinguish relationships from each other. Below, we define the corresponding notions of keys for relationships. o The primary key of an entity set allows us to distinguish among the various entities of the set. Let R be a relationship set involving entity sets E1, E2, . . . , En. o Let primary key (Ei) denote the set of attributes that forms the primary key for entity set Ei . Assume for now that the attribute names of all primary keys are unique. The composition of the primary key for a relationship set depends on the set of attributes associated with the relationship set R.
- 13. o If the relationship set R has no attributes associated with it, then the set of attributes primary-key(E1) ∪ primary-key(E2) ∪ ·· · ∪ primary-key(En) describes an individual relationship in set R. o If the relationship set R has attributes a1, a2, . . . , am associated with it, then the set of attributes primary-key(E1) ∪ primary-key(E2) ∪ · · · ∪ primary-key(En) ∪ {a1, a2, . . . , am} describes an individual relationship in set R. o In both of the above cases, the set of attributes primary-key(E1) ∪ primary-key(E2) ∪ ·· · ∪ primary-key(En) forms a super key for the relationship set. o If the attribute names of primary keys are not unique across entity sets, the attributes are renamed to distinguish them; the name of the entity set combined with the name of the attribute would form a unique name.
- 14. Entity-Relationship Design Issues o The notions of an entity set and a relationship set are not precise, and it is possible to define a set of entities and the relationships among them in a number of different ways. o Basic issues in the design of an E-R database schema are:- 1. Use of Entity Sets V/s Attributes o Consider the entity set instructor with the additional attribute phone number. It can easily be argued that a phone is an entity in its own right with attributes phone number and location; the location may be the office or home where the phone is located, with mobile (cell) phones perhaps represented by the value “mobile.” If we take this point of view, we do not add the attribute phone number to the instructor. Rather, we create: A phone entity set with attributes phone_number and location. o A relationship set inst_phone, denoting the association between instructors and the phones that they have.
- 15. o Treating a phone as an attribute phone_number implies that instructors have precisely one phone number each. Treating a phone as an entity phone permits instructors to have several phone numbers (including zero) associated with them. However, we could instead easily define phone_number as a multivalued attribute to allow multiple phones per instructor. o The main difference then is that treating a phone as an entity better models a situation where one may want to keep extra information about a phone, such as its location, or its type (mobile, IP phone, or plain old phone), or all who share the phone. o Thus, treating phone as an entity is more general than treating it as an attribute and is appropriate when the generality may be useful. o In contrast, it would not be appropriate to treat the attribute name (of an instructor) as an entity; it is difficult to argue that name is an entity in its own right (in contrast to the phone). Thus, it is appropriate to have name as an attribute of the instructor entity set.
- 16. 2. Use of Entity Sets V/s Relationship Sets o It is not always clear whether an object is best expressed by an entity set or a relationship set. An alternative is to imagine that there is a course-registration record for each course that each student takes. o Then, we have an entity set to represent the course-registration record. Let us call that entity set registration. Each registration entity is related to exactly one student and to exactly one section, so we have two relationship sets, one to relate course registration records to students and one to relate course-registration records to sections.
- 17. a. registration, the entity set representing course-registration records. b. section reg, the relationship set relating registration and course. c. student reg, the relationship set relating registration and student. o One possible guideline in determining whether to use an entity set or a relationship set is to designate a relationship set to describe an action that occurs between entities. This approach can also be useful in deciding whether certain attributes may be more appropriately expressed as relationships.
- 18. 3. Binary V/s n-ary Relationship Sets o Relationships in databases are often binary. Some relationships that appear to be non binary could actually be better represented by several binary relationships. o For instance, one could create a ternary relationship parent, relating a child to his/her mother and father. However, such a relationship could also be represented by two binary relationships, mother and father, relating a child to his/her mother and father separately. o Using the two relationships mother and father provides us a record of a child’s mother, even if we are not aware of the father’s identity; a null value would be required if the ternary relationship parent is used. Using binary relationship sets is preferable in this case. o In fact, it is always possible to replace a non binary (n-ary, for n > 2) relationship set by a number of distinct binary relationship sets. For simplicity, consider the abstract ternary (n = 3) relationship set R, relating entity sets A, B, and C. a. RA, relating E and A. b. RB, relating E and B. c. RC, relating E and C.
- 19. o If the relationship set R had any attributes, these are assigned to entity set E; further, a special identifying attribute is created for E (since it must be possible to distinguish different entities in an entity set on the basis of their attribute values). o For each relationship (ai , bi , ci ) in the relationship set R, we create a new entity ei in the entity set E. Then, in each of the three new relationship sets, we insert a relationship as follows: A. (ei , ai) in RA. B. (ei , bi) in RB. C. (ei , ci) in RC. o We can generalize this process in a straightforward manner to n-ary relationship sets. Thus, conceptually, we can restrict the E-R model to include only binary relationship sets. However, this restriction is not always desirable.
- 20. o An identifying attribute may have to be created for the entity set created to represent the relationship set. This attribute, along with the extra relationship sets required, increases the complexity of the design and overall storage requirements. o An n-ary relationship set shows more clearly that several entities participate in a single relationship. o There may not be a way to translate constraints on the ternary relationship into constraints on the binary relationships. For example, consider a constraint that says that R is many-to- one from A, B to C; that is, each pair of entities from A and B is associated with at most one C entity. This constraint cannot be expressed by using cardinality constraints on the relationship sets RA, RB, and RC.
- 21. 4. Placement of Relationship Attributes o The cardinality ratio of a relationship can affect the placement of relationship attributes. Thus, attributes of one-to-one or one-to-many relationship sets can be associated with one of the participating entity sets, rather than with the relationship set. o For instance, let us specify that advisor is a one-to-many relationship set such that one instructor may advise several students, but each student can be advised by only a single instructor. o In this case, the attribute date, which specifies when the instructor became the advisor of a student, could be associated with the student entity set. o Since each student entity participates in a relationship with at most one instance of instructor, making this attribute designation has the same meaning aswould placing date with the advisor relationship set. o Attributes of a one-to-many relationship set can be repositioned to only the entity set on the “many” side of the relationship. For one-to-one relationship sets, on the other hand, the relationship attribute can be associated with either one of the participating entities.
- 22. o The design decision of where to place descriptive attributes in such cases—as a relationship or entity attribute—should reflect the characteristics of the enterprise being modeled. o The designer may choose to retain date as an attribute of advisor to express explicitly that the date refers to the advising relationship and not some other aspect of the student’s university status (for example, date of acceptance to the university). o The choice of attribute placement is more clear-cut for many-to-many relationship sets. Returning to our example, let us specify the perhaps more realistic case that advisor is a many-to-many relationship set expressing that an instructor may advise one or more students, and that a student may be advised by one or more instructors. o If we are to express the date on which a specific instructor became the advisor of a specific student, date must be an attribute of the advisor relationship set, rather than either one of the participating entities. o If date were an attribute of student, for instance, we could not determine which instructor became the advisor on that particular date. o When an attribute is determined by the combination of participating entity sets, rather than by either entity separately, that attribute must be associated with the many-to-many relationship set.