Unit 4 Object Relational Modeling. Key Concepts Object-Relational Modeling outcomes and process...

Unit 4

Object Relational Modeling

Key ConceptsObject-Relational Modeling outcomes and

processRelational data modelNormalizationAnomaliesFunctional dependencyReferential integrityObject-oriented extensions to relational

modelingTranslating from a CDM to an ORM.

Object-relational data modeling converts a conceptual data model to a logical data model based on relational and object-oriented technology.

Purposes of Object-Relational ModelingProduce database structures

Create entity classesEnhance and finalize the attributes in the data model

What Is a Relational Data Model?Based on the concept of relations

(tables of data)Relationships established by matching

primary and foreign keysRelational DBMSs (RDBMS) are the most

commonly used in industry today.Many DBMS vendors have begun adding

object-oriented features, creating an object-relational model.

What Is a Relation?A named, two-dimensional table with the

following properties:All cells contain are atomic (single-value)

data.Entries in columns are from the same set of

values (domain range).Each row is unique (i.e. has a nonempty

primary key).Column order does not matter.Row order does not matter.

This is called First Normal Form (1NF)

Homework Review Question #2 page 234

Give one example of each of the three normal forms (other than those included in this chapter)

Give an example of 1NF now

Example relation: note uniqueness of rows guaranteed by Emp_ID. Primary keys are underlined

What Is Normalization?The process of converting complex data

structures into well-structured relationsWell-structured relation

Contains a minimum amount of redundancies Allows rows to be inserted, modified, and

deleted without introducing errors or inconsistencies

Consequences of Relations that Are Not Well StructuredInsertion anomaly – adding new rows

forces user to create duplicate dataUpdate anomaly – changes in one row

force changes in other rows because of duplication

Deletion anomaly – deleting rows may cause a loss of data that would be needed for other future rows

Data integrity requires well-structured relations.

What Is a Functional Dependency?The functional dependency of attribute

B on attribute A is represented by an arrow A B, and implies that every valid value of attribute A uniquely determines the value of attribute B.

Determinant – the attribute on the left side of the arrow

All primary keys are determinants

The Normal Forms1st NF

All relations are in 1NFRelations do not include multivalued attributes

2nd NF Relations with no partial-key functional

dependencies3rd NF

Relations with no transitive functional dependenciesHigher

Normal forms: 4th, Boyce Codd, 5th – mainly theoretical, not needed for most OOSAD problems

Main goal is to achieve 3NF for all relations.

Second Normal Form (2NF)1NF, plus no partial key functional

dependenciesIf the primary key is a composite key

(composed of more than one attribute) it is possible for an attribute to be functionally dependent on only part of the key

Avoid partial dependencies for 2NF

This table has a composite key (Emp_ID and Course)

Functional dependencies:Emp_ID Name, Dept, SalaryEmp_ID, Course Date_Completed

Name, Dept, and Salary all have partial key dependencies, causing duplication of data.

Solution:

Break the relation into two separate relations.

1:N relationship linked by Emp_ID

No partial key dependencies

Well structured

Third Normal Form (3NF)2NF, plus no transitive functional

dependenciesGiven three attributes in a relation A, B, C

If A B and B C, this forms a transitive functional dependency

Avoid transitive dependencies for 3NF

Here, Customer_ID Salesperson, and Salesperson Region, cause a transitive dependency

Break the relation into two separate relations.

1:N relationship linked by SalesPerson

No transitive dependencies

Well structured

Solution:

Primary and Foreign KeysPrimary key – one or more attributes that

together form a unique identifier for rows in the relation

Foreign key – an attribute that appears as a non-primary key attribute or as part of a primary key in one relation and as a primary key attribute in another relation

Relationship – rows in one relation are matched with related rows in another relation through foreign keys

Referential IntegrityA rule that states that any foreign key

value (on the relation of the many side) MUST match a primary key value in the relation of the one side

No foreign key can contain a value that is not present in a primary key in the other relation


If referential integrity is violated, what problems will result?

Object-Oriented Extensions to Relational Modeling

GeneralizationMultivalued attributes (OK to violate atomicity requirement of 1NF)

AggregationObject identifiersPointersBehaviorsRicher set of data types

Object-relational Data Model

Translating Conceptual Data Model to Object-Relational Model

Relational approach, forces atomic attributes

Object-relational approach, with multivalued attribute

Comparison of techniques for translating multivalued attributes

STUDENT (StudentID, Name, Address)STUDENT_PHONES(StudentID, PhoneNumber)

STUDENT (StudentID, Name, Address, {PhoneNumbers})

When constructing 1:N relationships, the foreign key is added as an attribute to the relation on the N side.

Associative class and M:N relationship


How are relationships between classes represented in relational notation?


How is a foreign key represented in relational notation?

Associative ClassesAssociative class is translated into a

relation whose primary key is a composite of the primary keys of the other two classes.

M:N relationship between Work and Skill is implemented as an extra relation UseSkills, whose primary key is composed of the primary keys of Work and Skill.

Unary 1:N relationship is represented by a foreign key managerID, which matches with the empId primary key of the same relation.

Unary M:N relationship is represented by a separate relation Prerequisite, whose primary key is composed of two primary key values from the Course relation.

Other RelationshipsAggregation and Composition – use

same rules that apply to association. Composition is 1:N, aggregation is M:N

Generalization – no uniform standard exists. Can make use of stereotypes to annotate generalizations

Merging Object Relationships

Similar or redundant object relations can be merged into one

Example:

merge

Problems with MergingSynonyms – two relations with different

attribute names referring to same meaningSolution – decide on a single standard name

Homonyms – two relations with same attribute names referring to different meaningsSolution – create new attribute for second meaning

Dependencies between non-key attributes after mergeSolution – normalize the merged relation

PVF WebStore Conceptual Data ModelUse Figure 7.31 on page 208 of Object-

Oriented Systems Analysis and Design

Unit 4 Object Relational Modeling. Key Concepts Object-Relational Modeling outcomes and process...

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