ITEC 3220M Using and Designing Database Systems Instructor: Prof. Z.Yang Course Website: zyang/itec...
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Transcript of 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)
3
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
4
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
5
Union
6
Intersect
7
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
8
Venn Diagrams for Traditional Set Operators
Union Intersection
Venn Diagram:
Differences
9
Product
Yields all possible pairs of rows from two tables
10
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
11
Select
12
Project
13
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
14
• 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
15
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
16
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
17
Divide
Requires use of single-column table and two-column table
18
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
19
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
21
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
22
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
23
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
24
Attributes
• Characteristics of entities
• Domain is set of possible values• Primary keys underlined
25
Examples
• EMPLOYEE (EMPLOYEE _ID, EMPLOYEE _NAME, ADDRESS, DATE-EMPLOYED)
ADDRESSEMPLOYEE _NAME
EMPLOYEEEMPLOYEE _ID
DATE-EMPLOYED
EMPLOYEE
EMPLOYEE _ID
EMPLOYEE _NAME
ADDRESS
DATE-EMPLOYED
26
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
27
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)
29
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.
30
An Example
Car_Vin
Mod_code
Car_Color
Car_Year
CAR
31
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
32
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
33
Connectivity and Cardinality in an ERD
34
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
35
Weak Entity
• Existence-dependent on another entity
• Has primary key that is partially or totally derived from parent entity
36
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
37
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
38
Three Types of Relationships
39
Recursive Relationship
• Definition: A relationship can exist between occurrences of the same entity set.
PERSON
is married to
1 1EMPLOYEE
manages
1 M
40
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
41
A Composite Entity in an ERD
42
Example M:N Relationship
43
Converting M:N Relationship to Two 1:M Relationships (Cont’d)
44
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)
45
Comparison of E-R Modeling Symbols
46
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
47
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
48
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.