Entity-Relationship Model PDF

ENTITY-RELATIONSHIP MODEL Entity Sets Relationship Sets Design Issues Parul Saxena, MITS Mapping Constraints Keys E-R Diagram Extended E-R Features Design of an E-R Database Schema Reduction of an E-R Schema to Tabl...

ENTITY-RELATIONSHIP MODEL Entity Sets Relationship Sets Design Issues Parul Saxena, MITS Mapping Constraints Keys E-R Diagram Extended E-R Features Design of an E-R Database Schema Reduction of an E-R Schema to Tables 1 ENTITY SETS A database can be modeled as: a collection of entities, Parul Saxena, MITS relationship among entities. An entity is an object that exists and is distinguishable from other objects. Example: specific person, company, event, plant Entities have attributes Example: people have names and addresses An entity set is a set of entities of the same type that share the same properties. Example: set of all persons, companies, trees, holidays 2 ENTITY SETS - CUSTOMER AND LOAN customer-id customer- customer- customer- loan- amount name street city number Parul Saxena, MITS 3 ATTRIBUTES An entity is represented by a set of attributes, that is descriptive properties possessed by all members of an entity set. Example: customer = (customer-id, customer-name, Parul Saxena, MITS customer-street, customer-city) loan = (loan-number, amount) Domain – the set of permitted values for each attribute Attribute types: Simple and composite attributes. Single-valued and multi-valued attributes E.g. multivalued attribute: phone-numbers Derived attributes Can be computed from other attributes E.g. age, given date of birth 4 COMPOSITE ATTRIBUTES Parul Saxena, MITS 5 RELATIONSHIP SETS A relationship is an association among several entities Example: Hayes depositor A-102 Parul Saxena, MITS customer entityrelationship setaccount entity A relationship set is a mathematical relation among n ≥ 2 entities, each taken from entity sets {(e1, e2, … en) | e1 ∈ E1, e2 ∈ E2, …, en ∈ En} where (e1, e2, …, en) is a relationship Example: (Hayes, A-102) ∈ depositor 6 RELATIONSHIP SET BORROWER Parul Saxena, MITS 7 RELATIONSHIP SETS (CONT.) An attribute can also be property of a relationship set. For instance, the depositor relationship set between entity sets customer and account may have the attribute access-date Parul Saxena, MITS 8 DEGREE OF A RELATIONSHIP SET Refers to number of entity sets that participate in a relationship set. Relationship sets that involve two entity sets are binary Parul Saxena, MITS (or degree two). Generally, most relationship sets in a database system are binary. Relationship sets may involve more than two entity sets. E.g. Suppose employees of a bank may have jobs (responsibilities) at multiple branches, with different jobs at different branches. Then there is a ternary relationship set between entity sets employee, job and branch Relationships between more than two entity sets are rare. Most relationships are binary. 9 MAPPING CARDINALITIES Express the number of entities to which another entity can be associated via a relationship set. Most useful in describing binary relationship sets. Parul Saxena, MITS For a binary relationship set the mapping cardinality must be one of the following types: One to one One to many Many to one Many to many 10 MAPPING CARDINALITIES Parul Saxena, MITS One to one One to many Note: Some elements in A and B may not be mapped to any 11 elements in the other set MAPPING CARDINALITIES Parul Saxena, MITS Many to one Many to many Note: Some elements in A and B may not be mapped to any 12 elements in the other set MAPPING CARDINALITIES AFFECT ER DESIGN Can make access-date an attribute of account, instead of a relationship attribute, if each account can have only one customer i.e., the relationship from account to customer is many to one, or equivalently, customer to account is one to many Parul Saxena, MITS 13 E-R DIAGRAMS Parul Saxena, MITS Rectangles represent entity sets. Diamonds represent relationship sets. Lines link attributes to entity sets and entity sets to relationship sets. Ellipses represent attributes Double ellipses represent multivalued attributes. 14 Dashed ellipses denote derived attributes. Underline indicates primary key attributes (will study later) E-R DIAGRAM WITH COMPOSITE, MULTIVALUED, AND DERIVED ATTRIBUTES Parul Saxena, MITS 15 RELATIONSHIP SETS WITH ATTRIBUTES Parul Saxena, MITS 16 ROLES Entity sets of a relationship need not be distinct The labels “manager” and “worker” are called roles; they specify how employee entities interact via the works-for relationship set. Roles are indicated in E-R diagrams by labeling the lines that connect diamonds to rectangles. Parul Saxena, MITS Role labels are optional, and are used to clarify semantics of the relationship 17 For some entities in a unary relationship, a separate column can be created that refers to the primary key of the same entity set. Parul Saxena, MITS 18 CARDINALITY CONSTRAINTS We express cardinality constraints by drawing either a directed line (→), signifying “one,” or an undirected line (—), signifying “many,” between the relationship set and the entity set. E.g.: One-to-one relationship: Parul Saxena, MITS A customer is associated with at most one loan via the relationship borrower A loan is associated with at most one customer via borrower 19 ONE-TO-MANY RELATIONSHIP In the one-to-many relationship a loan is associated with at most one customer via borrower, a customer is associated with several (including 0) loans via borrower Parul Saxena, MITS 20 MANY-TO-ONE RELATIONSHIPS In a many-to-one relationship a loan is associated with several (including 0) customers via borrower, a customer is associated with at most one loan via Parul Saxena, MITS borrower 21 MANY-TO-MANY RELATIONSHIP Parul Saxena, MITS A customer is associated with several (possibly 0) loans via borrower A loan is associated with several (possibly 0) customers via borrower 22 PARTICIPATION OF AN ENTITY SET IN A RELATIONSHIP SET Total participation (indicated by double line): every entity in the entity set participates in at least one relationship in the relationship set E.g. participation of loan in borrower is total every loan must have a customer associated to it via borrower Parul Saxena, MITS Partial participation: some entities may not participate in any relationship in the relationship set E.g. participation of customer in borrower is partial 23 ALTERNATIVE NOTATION FOR CARDINALITY LIMITS Cardinality limits can also express participation constraints Parul Saxena, MITS 24 KEYS A super key of an entity set is a set of one or more attributes whose values uniquely determine each entity. Parul Saxena, MITS A candidate key of an entity set is a minimal super key Customer-id is candidate key of customer account-number is candidate key of account Although several candidate keys may exist, one of the candidate keys is selected to be the primary key. 25 KEYS FOR RELATIONSHIP SETS The combination of primary keys of the participating entity sets forms a super key of a relationship set. Parul Saxena, MITS (customer-id, account-number) is the super key of depositor NOTE: this means a pair of entity sets can have at most one relationship in a particular relationship set. E.g. if we wish to track all access-dates to each account by each customer, we cannot assume a relationship for each access. We can use a multivalued attribute though Must consider the mapping cardinality of the relationship set when deciding the what are the candidate keys Need to consider semantics of relationship set in selecting the primary key in case of more than 26 one candidate key E-R DIAGRAM WITH A TERNARY RELATIONSHIP Parul Saxena, MITS 27 WEAK ENTITY SETS An entity set that does not have a primary key is referred to as a weak entity set. The existence of a weak entity set depends on the Parul Saxena, MITS existence of a identifying entity set it must relate to the identifying entity set via a total, one-to- many relationship set from the identifying to the weak entity set Identifying relationship depicted using a double diamond The discriminator (or partial key) of a weak entity set is the set of attributes that distinguishes among all the entities of a weak entity set. The primary key of a weak entity set is formed by the primary key of the strong entity set on which the weak entity set is existence dependent, plus the weak entity set’s discriminator. 28 WEAK ENTITY SETS (CONT.) We depict a weak entity set by double rectangles. We underline the discriminator of a weak entity set with a dashed line. payment-number – discriminator of the payment entity set Primary key for payment – (loan-number, payment-number) Parul Saxena, MITS 29 MORE WEAK ENTITY SET EXAMPLES In a university, a course is a strong entity and a course- offering can be modeled as a weak entity The discriminator of course-offering would be semester (including year) and section-number (if there is more than Parul Saxena, MITS one section) If we model course-offering as a strong entity we would model course-number as an attribute. Then the relationship with course would be implicit in the course-number attribute 30 SPECIALIZATION Top-down design process; we designate subgroupings within an entity set that are distinctive from other entities in the set. Parul Saxena, MITS These subgroupings become lower-level entity sets that have attributes or participate in relationships that do not apply to the higher-level entity set. Depicted by a triangle component labeled ISA (E.g. customer “is a” person). Attribute inheritance – a lower-level entity set inherits all the attributes and relationship participation of the higher-level entity set to which it is linked. 31 SPECIALIZATION EXAMPLE Parul Saxena, MITS 32 GENERALIZATION A bottom-up design process – combine a number of entity sets that share the same features into a higher- level entity set. Specialization and generalization are simple inversions Parul Saxena, MITS of each other; they are represented in an E-R diagram in the same way. The terms specialization and generalization are used interchangeably. 33 SPECIALIZATION AND GENERALIZATION (CONTD.) Can have multiple specializations of an entity set based on different features. E.g. permanent-employee vs. temporary-employee, in Parul Saxena, MITS addition to officer vs. secretary vs. teller Each particular employee would be a member of one of permanent-employee or temporary-employee, and also a member of one of officer, secretary, or teller The ISA relationship also referred to as superclass - subclass relationship 34 DESIGN CONSTRAINTS ON A SPECIALIZATION/GENERALIZATION Constraint on which entities can be members of a given lower-level entity set. condition-defined E.g. all customers over 65 years are members of senior- Parul Saxena, MITS citizen entity set; senior-citizen ISA person. user-defined Constraint on whether or not entities may belong to more than one lower-level entity set within a single generalization. Disjoint an entity can belong to only one lower-level entity set Noted in E-R diagram by writing disjoint next to the ISA triangle Overlapping an entity can belong to more than one lower-level entity set 35 DESIGN CONSTRAINTS ON A SPECIALIZATION/GENERALIZATION (CONTD.) Completeness constraint -- specifies whether or not an entity in the higher-level entity set must belong to at least one of the lower-level entity sets within a Parul Saxena, MITS generalization. total : an entity must belong to one of the lower-level entity sets partial: an entity need not belong to one of the lower-level entity sets 36 Parul Saxena, MITS 37 Parul Saxena, MITS 38 Parul Saxena, MITS 39 AGGREGATION Consider the ternary relationship works-on, which we saw earlier Suppose we want to record managers for tasks performed by an employee at a branch Parul Saxena, MITS 40 AGGREGATION (CONT.) Relationship sets works-on and manages represent overlapping information Every manages relationship corresponds to a works-on relationship Parul Saxena, MITS However, some works-on relationships may not correspond to any manages relationships So we can’t discard the works-on relationship Eliminate this redundancy via aggregation Treat relationship as an abstract entity Allows relationships between relationships Abstraction of relationship into new entity Without introducing redundancy, the following diagram represents: An employee works on a particular job at a particular branch An employee, branch, job combination may have an associated manager 41 E-R DIAGRAM WITH AGGREGATION Parul Saxena, MITS 42 E-R DESIGN DECISIONS The use of an attribute or entity set to represent an object. Parul Saxena, MITS Whether a real-world concept is best expressed by an entity set or a relationship set. The use of a ternary relationship versus a pair of binary relationships. The use of a strong or weak entity set. The use of specialization/generalization – contributes to modularity in the design. The use of aggregation – can treat the aggregate entity set as a single unit without concern for the 43 details of its internal structure. E-R DIAGRAM FOR A BANKING ENTERPRISE Parul Saxena, MITS 44 SUMMARY OF SYMBOLS USED IN E-R NOTATION Parul Saxena, MITS 45 SUMMARY OF SYMBOLS (CONT.) Parul Saxena, MITS 46 ALTERNATIVE E-R NOTATIONS Parul Saxena, MITS 47 UML UML: Unified Modeling Language UML has many components to graphically model Parul Saxena, MITS different aspects of an entire software system UML Class Diagrams correspond to E-R Diagram, but several differences. 48 SUMMARY OF UML CLASS DIAGRAM NOTATION Parul Saxena, MITS 49 UML CLASS DIAGRAMS (CONTD.) Entity sets are shown as boxes, and attributes are shown within the box, rather than as separate ellipses in E-R diagrams. Binary relationship sets are represented in UML by just Parul Saxena, MITS drawing a line connecting the entity sets. The relationship set name is written adjacent to the line. The role played by an entity set in a relationship set may also be specified by writing the role name on the line, adjacent to the entity set. The relationship set name may alternatively be written in a box, along with attributes of the relationship set, and the box is connected, using a dotted line, to the line depicting the relationship set. Non-binary relationships drawn using diamonds, just as in ER diagrams 50 UML CLASS DIAGRAM NOTATION (CONT.) Parul Saxena, MITS overlapping disjoint *Note reversal of position in cardinality constraint depiction *Generalization can use merged or separate arrows independent 51 of disjoint/overlapping REDUCTION OF AN E-R SCHEMA TO TABLES Primary keys allow entity sets and relationship sets to be expressed uniformly as tables which represent the contents of the database. A database which conforms to an E-R diagram can be represented by a collection of tables. Parul Saxena, MITS For each entity set and relationship set there is a unique table which is assigned the name of the corresponding entity set or relationship set. Each table has a number of columns (generally corresponding to attributes), which have unique names. Converting an E-R diagram to a table format is the basis for deriving a relational database design from an E-R diagram. 52 REPRESENTING ENTITY SETS AS TABLES A strong entity set reduces to a table with the same attributes. Parul Saxena, MITS 53 COMPOSITE AND MULTIVALUED ATTRIBUTES Composite attributes are flattened out by creating a separate attribute for each component attribute E.g. given entity set customer with composite attribute name with component attributes first-name and last-name the table corresponding to the entity set has two attributes Parul Saxena, MITS name.first-name and name.last-name A multivalued attribute M of an entity E is represented by a separate table EM Table EM has attributes corresponding to the primary key of E and an attribute corresponding to multivalued attribute M E.g. Multivalued attribute dependent-names of employee is represented by a table employee-dependent-names( employee-id, dname) Each value of the multivalued attribute maps to a separate row of the table EM E.g., an employee entity with primary key John and dependents Johnson and Johndotir maps to two rows: (John, Johnson) and (John, Johndotir) 54 REPRESENTING WEAK ENTITY SETS A weak entity set becomes a table that includes a column for the primary key of the identifying strong entity set Parul Saxena, MITS 55 REPRESENTING RELATIONSHIP SETS AS TABLES A many-to-many relationship set is represented as a table with columns for the primary keys of the two participating entity sets, and any descriptive attributes of the relationship set. E.g.: table for relationship set borrower Parul Saxena, MITS 56 REDUNDANCY OF TABLES Many-to-one and one-to-many relationship sets that are total on the many-side can be represented by adding an extra attribute to the many side, containing the primary key of the one side E.g.: Instead of creating a table for relationship account- Parul Saxena, MITS branch, add an attribute branch-name to the entity account. 57 REDUNDANCY OF TABLES (CONT.) For one-to-one relationship sets, either side can be chosen to act as the “many” side That is, extra attribute can be added to either of the tables Parul Saxena, MITS corresponding to the two entity sets The table corresponding to a relationship set linking a weak entity set to its identifying strong entity set is redundant. E.g. The payment table already contains the information that would appear in the loan-payment table (i.e., the columns loan-number and payment-number). 58  REPRESENTING SPECIALIZATION AS TABLES Method 1: Form a table for the higher level entity Form a table for each lower level entity set, include primary key of higher level entity set and local attributes Parul Saxena, MITS table table attributes person name, street, city customer name, credit-rating employee name, salary Drawback: getting information about, e.g., employee requires accessing two tables 59  REPRESENTING SPECIALIZATION AS TABLES (CONT.) Method 2: Form a table for each entity set with all local and inherited attributes table table attributes Parul Saxena, MITS person name, street, city customer name, street, city, credit-rating employee name, street, city, salary Drawback: street and city may be stored redundantly for persons who are both customers and employees 60 REPRESENTING SPECIALIZATION AS TABLES (CONT.) Method 3: Only subclasses are mapped to tables. The attributes Parul Saxena, MITS in the superclass are duplicated in all subclasses. table table attributes customer name, street, city, credit-rating employee name, street, city, salary This method is most preferred when inheritance is disjoint 61 REPRESENTING SPECIALIZATION AS TABLES (CONT.) Method 4: Only the superclass is mapped to a table. The attributes in Parul Saxena, MITS the subclasses are taken to the superclass. table table attributes person name, street, city, credit-rating, salary This method will introduce null values. When we insert salary record in the table, the credit- rating column value will be null. In the same way, when we insert a credit-rating record in the table, the salary value will be null. 62 RELATIONS CORRESPONDING TO AGGREGATION To represent aggregation, create a table containing primary key of the aggregated relationship, Parul Saxena, MITS the primary key of the associated entity set Any descriptive attributes 63  RELATIONS CORRESPONDING TO AGGREGATION (CONT.) E.g. to represent aggregation manages between relationship works-on and entity set manager, create a table manages(employee-id, branch-name, title, manager-name) Parul Saxena, MITS 64 E-R DIAGRAM FOR EXERCISE 2.10 Parul Saxena, MITS 65 E-R DIAGRAM FOR EXERCISE 2.15 Parul Saxena, MITS 66 EXISTENCE DEPENDENCIES If the existence of entity x depends on the existence of entity y, then x is said to be existence dependent on y. y is a dominant entity (in example below, loan) Parul Saxena, MITS x is a subordinate entity (in example below, payment) loan loan-payment payment If a loan entity is deleted, then all its associated payment entities must be deleted also. 67 DBMS SCHEMA Definition of schema: Design of a database is called the schema. Schema is of three types: Parul Saxena, MITS Physical schema, logical schema and view schema. For example: We have a schema that shows the relationship between three tables: Course, Student and Section. The diagram only shows the design of the database, it doesn’t show the data present in those tables. Schema is only a structural view(design) of a database as shown in the diagram below. 68 The design of a database at physical level is called physical schema, how the data stored in blocks of storage is described at this level. Parul Saxena, MITS Design of database at logical level is called logical schema, programmers and database administrators work at this level, at this level data can be described as certain types of data records gets stored in data structures, however the internal details such as implementation of data structure is hidden at this level (available at physical level). Design of database at view level is called view schema. This generally describes end user 69 interaction with database systems. DBMS INSTANCE Definition of instance: The data stored in database at a particular moment of time is called instance of database. Database schema defines the variable Parul Saxena, MITS declarations in tables that belong to a particular database; the value of these variables at a moment of time is called the instance of that database. For example, lets say we have a single table student in the database, today the table has 100 records, so today the instance of the database has 100 records. Lets say we are going to add another 100 records in this table by tomorrow so the instance of database tomorrow will have 200 records in table. In short, at a particular moment the data stored in database is called the instance, that changes over time when we 70 add or delete data from the database.