itec 3220m using and designing database systems instructor: prof. z.yang course website: zyang/itec...

ITEC 3220MUsing and Designing Database Systems

Instructor: Prof. Z.YangCourse Website: http://people.math.yorku.ca/~zyang/itec3220m.htm Office: Tel 3049

Chapter 3

The Relational Database Model (Cont’d)

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Relational Database Operators

• Relational algebra

– Defines theoretical way of manipulating table contents using relational operators:

• SELECT

• PROJECT

• JOIN

• INTERSECT

– Use of relational algebra operators on existing tables (relations) produces new relations

• UNION• DIFFERENCE• PRODUCT• DIVIDE

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Relational Algebra Operators (continued)

• Union:

– Combines all rows from two tables, excluding duplicate rows

– Tables must have the same attribute characteristics

• Intersect:

– Yields only the rows that appear in both tables

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Union

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Intersect

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Relational Algebra Operators (continued)

• Difference

– Yields all rows in one table not found in the other table—that is, it subtracts one table from the other

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Venn Diagrams for Traditional Set Operators

Union Intersection

Venn Diagram:

Differences

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Product

Yields all possible pairs of rows from two tables

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Relational Algebra Operators (continued)

• Select– Yields values for all rows found in a

table– Can be used to list either all row

values or it can yield only those row values that match a specified criterion

– Yields a horizontal subset of a table

• Project– Yields all values for selected attributes– Yields a vertical subset of a table

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Select

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Project

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Relational Algebra Operators (continued)

• Join

– Allows us to combine information from two or more tables

– Real power behind the relational database, allowing the use of independent tables linked by common attributes

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• Links tables by selecting rows with common values in common attribute(s)

• Three-stage process– Product creates one table– Select yields appropriate rows– Project yields single copy of

each attribute to eliminate duplicate columns

Natural Join Process

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Natural Join (continued)

• Final outcome yields table that

– Does not include unmatched pairs

– Provides only copies of matches

• If no match is made between the table rows,

– the new table does not include the unmatched row

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Other Joins

• EquiJOIN– Links tables based on equality condition

that compares specified columns of tables

– Join criteria must be explicitly defined• Theta JOIN

– EquiJOIN that compares specified columns of each table using operator other than equality one

• Outer JOIN– Matched pairs are retained – Unmatched values in other tables left

null– Right and left

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Divide

Requires use of single-column table and two-column table

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Summary of Meanings of the Relational Algebra

Operators• Select: Extracts rows that satisfy a

specified condition• Project: Extracts specified columns• Product: Builds a table from two

tables consisting of all possible combinations of rows, one from each of the two tables

• Union: Builds a table from all rows appearing in either of two tables

• Intersect: Builds a table consisting of all rows appearing in both of two specified tables

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Summary of Meanings of the Relational Algebra Operators

(Cont’d)

• Join: Extracts rows from a product of two tables such that two input rows contributing to any output row satisfy some specified condition

• Outer Join: Extracts the matching rows of two tables and the unmatched rows from both tables

• Divide: Builds a table consisting of all values of one column of a binary table that match all values in a unary table

Chapter 4

Entity Relationship (E-R) Modeling

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In this chapter, you will learn:

• How relationships between entities are defined and refined, and how such relationships are incorporated into the database design process

• Key terms: cardinality, connectivity, optional, mandatory, strong relationship, weak relationship, supertype, subtype, etc.

• How to develop an E-R diagram

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The Entity Relationship (ER) Model

• ER model forms the basis of an ER diagram

• ERD represents the conceptual database as viewed by end user

• ERDs depict the ER model’s three main components: – Entities

– Attributes

– Relationships

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Entities

• Refers to the entity set and not to a single entity occurrence

• Corresponds to a table and not to a row in the relational environment

• In both the Chen and Crow’s Foot models, an entity is represented by a rectangle containing the entity’s name

• Entity name, a noun, is usually written in capital letters

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Attributes

• Characteristics of entities

• Domain is set of possible values• Primary keys underlined

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Examples

• EMPLOYEE (EMPLOYEE _ID, EMPLOYEE _NAME, ADDRESS, DATE-EMPLOYED)

ADDRESSEMPLOYEE _NAME

EMPLOYEEEMPLOYEE _ID

DATE-EMPLOYED

EMPLOYEE

EMPLOYEE _ID

EMPLOYEE _NAME

ADDRESS

DATE-EMPLOYED

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Attributes (Cont’d)

• Simple– Cannot be subdivided– Age, sex, marital status

• Composite– Can be subdivided into

additional attributes– Address into street, city,

zip

• Single-valued– Can have only a single

value– Person has one social

security number

• Multi-valued– Can have many values– Person may have several

college degrees– In the Chen E-R model, the

multivalued attributes are shown by a double line connecting the attributes to the entity

• Derived– Can be derived with

algorithm– Age can be derived from

date of birth– Versus stored attribute

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Attributes (Cont’d)

An attribute broken into component parts

Address

Street_Address Post_CodeStateCity

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Attributes (Cont’d)

Years_Employed

Employee_ID

Date_Employed

Skills

AddressEmployee_Name

EMPLOYEE

Entity with a multivalued attribute (Skill) and derived attribute (Years_Employed)

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How to Deal with Multivalued Attributes

• With the original entity, create several new attributes, one for each of the original multivalued attribute’s components.

• Create a new entity composed of the original multivalued attribute’s components.

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An Example

Car_Vin

Mod_code

Car_Color

Car_Year

CAR

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Relationships

• Association between entities• Connected entities are called participants• Operate in both directions• Connectivity describes relationship

classification– 1:1, 1:M, M:N

• Cardinality– Expresses number of entity occurrences

associated with one occurrence of related entity

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ERD SymbolsERD Symbols

• Rectangles represent entities• Diamonds represent the

relationship(s) between the entities

• “1” side of relationship– Number 1 in Chen Model– Bar crossing line in Crow’s Feet

Model• “Many” relationships

– Letter “M” and “N” in Chen Model– Three pronged “Crow’s foot” in

Crow’s Feet Model

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Connectivity and Cardinality in an ERD

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Relationship Strength

• Existence dependence– Entity’s existence depends on existence of

related entities– Existence-independent entities can exist apart

from related entities– EMPLOYEE claims DEPENDENT

• Weak (non-identifying) – One entity is existence-independent on another– PK of related entity doesn’t contain PK component

of parent entity

• Strong (identifying) – One entity is existence-dependent on another– PK of related entity contains PK component of

parent entity

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Weak Entity

• Existence-dependent on another entity

• Has primary key that is partially or totally derived from parent entity

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Relationship Participation

• Optional– Entity occurrence does not require a

corresponding occurrence in related entity

– Shown by drawing a small circle on side of optional entity on ERD

• Mandatory– Entity occurrence requires corresponding

occurrence in related entity– If no optionality symbol is shown on ERD,

it is mandatory

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Relationship Degree

• Indicates number of associated entities• Unary

– Single entity– Exists between occurrences of same entity set

• Binary– Two entities associated– Most common– To simplify the conceptual design, most higher-

order relationships are decomposed into appropriate equivalent relationships when possible

• Ternary– Three entities associated

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Three Types of Relationships

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Recursive Relationship

• Definition: A relationship can exist between occurrences of the same entity set.

PERSON

is married to

1 1EMPLOYEE

manages

1 M

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Composite Entities

• Also known as bridge entities

• Composed of the primary keys of each of the entities to be connected

• May also contain additional attributes that play no role in the connective process

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A Composite Entity in an ERD

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Example M:N Relationship

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Converting M:N Relationship to Two 1:M Relationships (Cont’d)

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An Example

claims DEPENDENT

ORDER PRODUCT

EMPLOYEE

employs

STORE1 ZX YW

1M M

(a,b) (g,h) (i,j)

(c,d)

(e,f) (k,l)

(o,p)(m,n)

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Comparison of E-R Modeling Symbols

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Developing an E-R Diagram

• Iterative Process– Step1: General narrative of

organizational operations developed– Step2: Basic E-R Model graphically

depicted and reviewed– Step3: Modifications made to

incorporate newly discovered E-R components

• Repeat process until designers and users agree E-R Diagram complete

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Example

• Create an ERD using the following business rules:– A company operates four

departments– Each department employs

employees– Each of the employees may or

may not have one or more dependents

– Each employee may or may not have an employment history

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Exercise

Design an E-R diagram for a real estate firm that lists property of sale. The firm has a number of sales offices in several states. Each sales office is assigned one or more employees. Attributes of employees include ID and name. An employee must be assigned to only one sales office.For each sales office, there is always one employee assigned to manage that office. An employee may manage only the sales office to which he is assigned.The firm lists property for sale. Attributes of property include ID and location. Components of location include address, city, state, and Zip_code.Each unit of property must be listed with one of the sales offices. A sales office may have any number of properties listed, or may have no properties listed.Each unit of property has one or more owners. An owner may own one or more units of property. An attribute of the relationship between property and owner is Percent_Owned.