chapter 4chapter 4 logical database design and the ...mdamian/past/databasefa11/notes/...chapter...

Chapter 4Chapter 4Logical Database Design and

the Relational Model

11

ObjectivesObjectives

• Define terms for the relational data modelDefine terms for the relational data model

• Brief introduction to SQL

• Transform E-R diagrams to relations• Transform E-R diagrams to relations

• Create tables with entity and relational integrity constraintsconstraints

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Steps in Database Problem Solving

Business ProblemStudy and Analyze

w/Team

Conceptual Model

Interviews & Integrated Model

(E-R)

L i l M d l

Transformation(Six Cases)

Logical Model(Relations)

Normalization(Three Steps)

Logical Model(3NF Relations)

(Three Steps)

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IMPLEMENTATION

Advantages of Relational Modelg

• Can represent all kinds of information

• Based on Math (relations)

• Natural to people

• Relatively simple

• We know how to implement it fastp

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Motivating ExampleMotivating Example

• Make a list of students in the class, keeping their ID,Make a list of students in the class, keeping their ID, name and phone number

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Motivating ExampleMotivating Example

• Make a list of students in the class, keeping their ID,Make a list of students in the class, keeping their ID, name and phone number

• You’d probably come up with something like this:p y p g

ID Name Phone

Mik 111xx Mike 111

yy Elisa 222

• This is the basic structure of the relational model, a table or relation

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table or relation

Extra AssumptionsExtra Assumptions

• You would not repeat the same row twiceYou would not repeat the same row twice

• No two rows have the same ID, but they may have the same name and phone numberp

ID Name Phone

Mik 111xx Mike 111

yy Elisa 222

• ID would be the PRIMARY KEY (PK).

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Now add emails … (many!)Now add emails … (many!)

• Now you need to add the emails of each student, butNow you need to add the emails of each student, but you do not know how many emails

• Can you come up with a solution? Try it …y p y

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Many Fieldsy

• Could come up with something like thisCould come up with something like this

ID Name Phone Email1 Email2

xx Mike 111 bad idea

yy Elisa 222 bad idea

• Above would not work very well. How many fields?– Wasted spaceWasted space– What if a student has more emails?– How to process it in my program?

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Un-normalizedUn normalized

• Could also try this:

ID Name Phone Email

xx Mike 111 mk@ad comxx Mike 111 [email protected]

xx Mike 111 [email protected]

yy Elisa 222 [email protected]

• Problem is duplication, we are repeating the name and phone


number in the second row– What if Mike changes his phone?

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• Later we will study normalization to solve this.

Now add emails … (many!)( y )• A much better way:

Email

ID Name Phone

StudentID Email

xx [email protected]

Student

xx Mike 111

yy Elisa 222

xx [email protected]

yy [email protected]

• Every StudentID on the second table needs a matching ID on the first table: StudentID is a FOREIGN KEYthe first table: StudentID is a FOREIGN KEY

• In a way, StudentID in the second table is a pointer or reference to the first table

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Formalizing: Relations• Definition: A relation is a named table of data

– Table is made up of rows (records or tuples), and columns (attributes or fields)

• Not all tables qualify as relations. Requirements:1 Every relation has a unique name1. Every relation has a unique name.2. Every attribute value is atomic (not multivalued, not

composite)3 E i i ( ’ h i h l h3. Every row is unique (can’t have two rows with exactly the

same values for all their fields)4. Attributes (columns) in tables have unique names( ) q5. The order of the columns is irrelevant6. The order of the rows is irrelevant

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By definition, all relations are in 1st Normal Form (1NF).

Correspondence with ER Modelp

• Relations (tables) correspond to entity types and to l i himany-to-many relationship types

• Rows correspond to entity instances and to many-to-l ti hi i tmany relationship instances

• Columns correspond to attributes

• NOTE: The word relation (in relational database) is

NOT the same as the word relationship (in ER model)

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Formalizing Key Fieldsg y

• Primary key (PK) – Minimal set of attributes that uniquely identifies a row,

chosen for referencing

Thi i h t th t ll i– This is how we can guarantee that all rows are unique

• Foreign key (FK)Set of attributes in a table that serves as a reference to the– Set of attributes in a table that serves as a reference to the primary key of another table

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Constraints Implied by the Keysp y y

• Entity Integrity Constraint– No attribute of the PK may be null

• Referential Integrity Constraint– For a FK, either all attributes are null, or the values appear

in the PK of a row of the referred tablein the PK of a row of the referred table

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Well-Structured Relations

• Bad designs have redundancy

• Well-structured relation: minimal redundancy

• Anomaly: error or inconsistency arising from bad y y gdesign when changing (Insert, Update, Delete) data

• We eliminate anomalies through Normalization

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Is Student a Well-Structured Relation?Is Student a Well Structured Relation?

Student

ID Name Phone Email

xx Mike 111 [email protected]

Mik 111 k@ dxx Mike 111 [email protected]


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Review

• Conceptual ModelR l i l M d l• Relational Model

• Relation• Well Structured Relation• Well-Structured Relation• Primary Key• Foreign Keyg y• Entity Integrity Constraint• Referential Integrity Constraint

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Transforming E-R Into Relationsg

• Use a rectangle for each entity (table), with attributes inside rectangles, too– Can be vertical or horizontal– Primary key is underlined– Primary key is underlined

• Use arrows from Foreign key to Primary key

ID Name Phone ID

Name

StudentID

Email

Student Student Email

StudentID Email

Name

Phone

EmailEmail

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E-R vs. Relational

• Entities are represented by tablesB t t bl l t l ti hi lti l d– But tables may also represent relationships, or multivaluedattributes

• Foreign Keys used to relate table rows– Similar to relationships in E-R, but lower level

• Relational model is more concrete, lower level– Usually many more tables than entities

d d d b h i l l– Harder to understand by non-technical people– Directly implementable

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Brief Intro to SQLBrief Intro to SQL

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SQLQ

• Structured Query Language

• Standard Language for Relational Databases

• Every RDBMS implements SQL, with slight y gvariations, including

– Special data types

– Stored procedures

– Kinds of indexes, file organization ...g

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Basics

• Data Definition Language (DDL)– Create the database schema– CREATE / DROP / ALTER, …

• Data Manipulation Language (DML)– Manipulate the populated data– INSERT UPDATE DELETE SELECTINSERT, UPDATE, DELETE, SELECT, …

• Data Control Language (DCL)– Manage users permissions and suchManage users, permissions and such

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Conventions

• -- comments until end of line

• /* can also use C-style comments */

• SQL is case insensitive (except for data)

• But we usually type reserved words in ALL CAPS

• Use single quotes for ‘character constants’g q

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CREATE TABLECREATE TABLE

CREATE TABLE table_name (field type constraints,field2 type2 ,CONSTRAINT name ...,...

);

CREATE TABLE Book (ISBN CHAR(9) PRIMARY KEY,Title VARCHAR(20) UNIQUE NOT NULL,Pages Integer

);

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Common Datatypesyp

• CHAR(n)fi d l th t i dd d ith t d– fixed length strings, padded with spaces at end

• VARCHAR(n)i bl l th t i b t l th– variable length strings, but no longer than n

• NUMERIC(prec, dec)– fixed precision numbers (not floats)fixed precision numbers (not floats)– prec(ision) is total number of digits– dec is how many after the decimal point

NUMERIC(3 2) l i 9 99– NUMERIC(3,2) max value is 9.99

• DATE, TIMESTAMPRepresent dates or specific points in time

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– Represent dates, or specific points in time

Common Constraints

• PRIMARY KEY

• NOT NULL

• UNIQUE

• REFERENCES (foreign key)

– After REFERENCES put name of table, then field in p ,

parenthesis– StudentId REFERENCES Student(Id)

• CHECK– Allows to specify a condition or predicate

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– CHECK(age>20)

CREATE TABLE ExampleCREATE TABLE Example

CREATE TABLE Student (Id CHAR(3) PRIMARY KEY,Name VARCHAR(20) NOT NULL,Age INT DEFAULT 20 CHECK(Age>0 AND AGE<100),G d C OGender CHAR NOT NULL,Deg_code CHAR(2) NOT NULL REFERENCES Degree(code),Major CHAR(3),Credits INTEGERCredits INTEGER

);

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INSERT

• INSERT INTO table (fields)

VALUES (values)

• Character constants have single quotes ‘a’

INSERT INTO Student (Id,Name,Major,Age)VALUES (1, ‘Amy Cremer','CS',21);

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SELECT (Retrieving Data)( g )

• SELECT fields

FROM table

WHERE conditions

• Can use fields or expressions (a+3), * for all fields

• Conditions use normal operators (=,>) and are p ( , )combined with AND, OR, NOT

SELECT *FROM Student

SELECT Id,NameFROM StudentWHERE Major='CS'

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More ExamplesMore Examples

SELECT Id,Name,Age+5, , gFROM StudentWHERE Major='CS' AND Gender=’F’

SELECT Id,Name,Age+5 AS AgeIn5FROM StudentWHERE Age>=20 OR Age <=10WHERE Age> 20 OR Age < 10

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DELETE

• DELETE FROM table DELETEFROM St d t

WHERE conditionsFROM StudentWHERE Id=1

• If no conditions, delete all data

• Does NOT delete the meta-data, ,

use DROP TABLE for that

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UPDATE (Change Data)( g )

• UPDATE table

SET field=value

WHERE conditions

UPDATE StudentSET Name='Alfredo', Age=25SET Name Alfredo , Age 25WHERE Id=1;

UPDATE StudentSET Age=Age+1WHERE Id=1;

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;

Complete Examplep p

• Write CREATE TABLE statement

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Now Insert StatementsINSERT INTO Major(Id, Name) VALUES

('CS' 'Computer Science');( CS , Computer Science );

INSERT INTO Student(Id, Name, MajorId) VALUES(1, 'Paul Gordon', 'CS');

• Notice that field names and values match

( , au Go do , CS );

• Notice that field names and values match

• Notice that value of Student.MajorId needs to match a value of Major Idvalue of Major.Id

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Now You Tryy• Insert major for SWE, IT

d j i i S• Insert students majoring in SWE, IT

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Basic SELECTS• Show all students

SELECT * FROM Student;

• Now you do all majorsy j

SELECT * FROM Major;

A d th Id d N f ll t d t j i i CS• And then Id and Name of all students majoring in CS

SELECT Id, Name FROM StudentWHERE Student.MajorId = 'CS‘;

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Updatesp• Change the student with Id 2 to be CS instead of SWE

UPDATE StudentSET MajorId = 'CS'WHERE Id=2 ;

• Change the name of the student with Id=3 to be Rich

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Deletes• Delete any student majoring in IT

DELETE FROM StudentWHERE MajorId = 'IT';

• Now you do – delete the IT major (from the table)

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From E-R to TablesFrom E R to Tables

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Six Cases of Transforming E-R Diagrams into Relations

1. Map Regular Entities

2. Map Binary Relationshipsp y p

3. Map Weak Entities

4 Map Associati e Entities4. Map Associative Entities

5. Map Unary Relationships

6. Map Ternary (and n-ary) Relationships

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1. Mapping Regular Entitiespp g gEMPLOYEE

SSN• Create a new table for each entity

R b d li h SSNName (First, Middle, Last){Emails}Date of Birth

• Remember to underline the identifier (Fig. 4-8)

• For composite attributes, map Date of Birth[Age]

For composite attributes, map only the basic pieces (Fig. 4-9)

• Derived attributes disappear

ID First Middle Last DoB

Employee• For multivalued attributes we need a new table (Fig. 4-10)

• We may need to create several

ID Email

Email

• We may need to create several tables for independent multivalued attributes

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Email

You Try …yBOOK

ISBNISBNTitle{Authors}Format (Binding, NumPages, Dimensions, [Weight])

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Corresponding SQL

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2. Map Binary Relationshipsp y p





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Mapping Binary Relationshipspp g y p

• One-to-Many P i k th id b f i k th– Primary key on the one side becomes a foreign key on the many side (Fig. 4-12).

• One-to-One – Primary key on the mandatory side becomes a foreign key

on the optional side (Fig. 4-14).

M t M• Many-to-Many– Create a new relation with the primary keys of the two

entities as its primary key (Fig. 4-13).p y y ( g )

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Fig. 4-12: Example of mapping a 1:M relationship(a) Relationship between customers and orders

[Primary key on the one side becomes a

Note the mandatory one

Fig. 4-12: (b) Mapping the relationship[Primary key on the one side becomes a

foreign key on the many side]

Again, no null value in the foreign key…this is because of the mandatory

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Foreign key

because of the mandatory minimum cardinality

One-to-Many Relationship

0STUDENT

IDN

PROGRAMIDN

>0Majors in

ID N

Name Name

Program

ID N M j

Student

ID Name

• For one-to-many (or one-

ID Name Major

CREATE TABLE Program (to-one) relationship, put a foreign key on the side that relates to one entity.

g (ID INT PRIMARY KEY,Name VARCHAR(20)

); y

• Put any relationship attributes on that table, too.

CREATE TABLE Student (ID INT PRIMARY KEY,Name VARCHAR(50),

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Major INT REFERENCES Program(ID));

Figure 4-14 Example of mapping a binary 1:1 relationship

) I h l ti hi (1 1)a) In_charge relationship (1:1)

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Often in 1:1 relationships, one direction is optional.

Fig. 4-14: (b) Resulting relations

mandatory

PK

optional

FK

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[Primary key on the mandatory side becomes a foreign key on the optional side]

Many-to-Many Relationship

0<STUDENT

IDPROGRAM

ID>0Majors in

Name Name

ProgramStudent

ID NameID Name

M j I

Student Program

MajorsIn

• For a many-to-many, we need a new table representing the relationship.

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• This table has Foreign Keys to both entities.

Figure 4-13 Example of mapping an M:N relationship

) C l t l ti hi (M N)a) Completes relationship (M:N)

The Completes relationship will need to become a separate relation

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p p p

Figure 4-13 Example of mapping an M:N relationship (cont.)

b) Th lti l tib) Three resulting relations

Composite primary key (CPK)Composite primary key (CPK)

Foreign key Foreign key

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You Try It …

0<PERSON

IDCOUNTRY

ID>Is Citizen

Name Name

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2. Map Binary Relationships p y p





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3. Mapping Weak Entitiespp g

• A weak entity becomes a separate relation withA weak entity becomes a separate relation with a foreign key taken from the strong entity

• Primary key composed of:y y p– Partial identifier of weak entity

– Primary key of identifying relation (strong entity) (Fig. 4-11)

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Weak Entities

0<EMPLOYEE

SSNN

DEPENDENTNameD f Bi h

Has

Name Date of Birth

DependentEmployee

Employee Name DoBSSN Name

• Transform the strong entity normally

• For the weak entity, the PK becomes the identifier, plus the PK of the identifying entity

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You Try It …

0<

BOOKISBNTi l

CHAPTERNumber

Has

0TitleEdition

NumberTitle

6060








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4. Mapping Associative Entitiespp g

• Identifier Not Assigned – Default primary key for the association relation is

composed of the primary keys of the two entities (as in M:N relationship) (Fig. 4-15)M:N relationship) (Fig. 4 15)

• Identifier Assigned – It is natural and familiar to end-users.

– Default identifier may not be unique. (Fig. 4-16).

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Figure 4-16: Mapping an associative entity(a) Associative entity (SHIPMENT)

[Default primary key for the association

relation is assigned](a) Associative entity (SHIPMENT) relation is assigned]

(b) Three resulting relations

Primary key differs from foreign keys

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You Try It …

0 0

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5. Mapping Unary Relationshipspp g U y p

• Same as other relationships, except that the FK maySame as other relationships, except that the FK may go to the same table.

• For one-to-many, the table has a reference to other y,rows of the same table (Fig. 4-17).

• For many-to-many, an extra table has two FKs, both y y, ,to the same table (Fig. 4-18).

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Figure 4-17 Mapping a unary 1:N relationship

(a) EMPLOYEE entity with unary relationship(a) EMPLOYEE entity with unary relationship

A recursive FK is a FK inFK is a FK in a relation that references the PK values of that same relation.

(b) EMPLOYEE relation with recursive foreign key

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Figure 4-18: Mapping a unary M:N relationship

(a) Bill-of-(a) Bill-of-materials relationships (M:N)

One table for the entity type.

O t bl f

(b) ITEM and COMPONENT

One table for an associative relation in which the primary key

relationsthe primary key has two attributes, both taken from the

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taken from the primary key of the entity.

You Try It …

0EMPLOYEE

SSNBoss

0

Supervises

SSNName >

0

W kWorker

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You Try It …IsCorequisite

Requirer

>0COURSE

IDPre

Requirer

Required

>0

>0

IsPrerequisiteName >

0

Post

Required

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6. Mapping Ternary Relationshipspp g y p

• One relation for each entity and one for the i i iassociative entity.

• Associative entity has foreign keys to each entity i th l ti hi (Fi 4 19)in the relationship (Fig. 4-19).

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Figure 4-19 Mapping a ternary relationship

a) PATIENT TREATMENT Ternary relationship witha) PATIENT TREATMENT Ternary relationship with associative entity

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Figure 4-19 Mapping a ternary relationship (cont.)

b) Mapping the ternary relationship PATIENT TREATMENT

A patient may receive a treatment

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once in the morning, then the same treatment in the afternoon.


Figure 4-19 Mapping a ternary relationship (cont.)


Remember that the primary

key MUST be

This is why treatment date and time are included in

But this makes a very cumbersome

key

It would be better to create a

surrogate key like

7575

key MUST be unique

time are included in the composite primary key

key… surrogate key like Treatment#

Mi d E iMixed Exercises

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Practice Exercise

0<TV SERIES

IDTi l

EPISODENumberTitle

Has

TitleTitleFirstAiring Date

7777

Practice Exercise

COURSESECTION

Belongs TEACHERTeaches

0<COURSE

IDName

SecNoTerm(Semester, Year)

Belongs TEACHERSSNName

>0Teaches

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Practice Exercise

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Next Topicp

• Next topic is the most important topic (theory) in this database management class.

• What is it?

• Normalization

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