CS 157A Chap 2

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Transcript CS 157A Chap 2

Chapter 2

THE RELATIONAL MODEL OF DATA

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 1

Chapter 2 The Relational Model of Data

2.1 An Overview of Data Models 2.2 Basics of Relational Model 2.3 Defining a Relation Schema in SQL 2.4 An Algebraic Query Language 2.5 Constraints on Relations 2.6 Summary of Chapter 2 2.7 References for Chapter 2 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 2

Section 2.1

AN OVERVIEW OF DATA MODELS

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 3

2.1 An Overview of Data Models

2.1.1 What is Data Model?

2.1.2 Important Data Models 2.1.3 The Relational Data Model in Brief 2.1.4 The Semi-structured Model in Brief 2.1.5 Other Data Models 2.1.6 Comparison of Modeling Approaches Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 4

2.1.1 What is Data Model?

A data model is a “small set of notations/mathematics” (mathematical model – see Definition in Discrete Mathematics) for describing data.

The description generally consists of 3 parts: 1.

2.

Structure : it can be imagined as 'object' in Java or 'struct' in C but in database world, the structure of data is higher level than physical data model . That's why we refer to it as conceptual model .

Operations : a limited set of queries (retrieving data) and modifications (changing data) 3.

Constraints : applying some limitations on what the data can be.

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 5

Structure

 

External view E.g. CS

 

conceptual view E.g Knowledge

 

Internal view Congress libaray Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6

2.1.2 Important Data Models

Currently, there are two important data models as follows: 1.

2.

The Relational Data Model commercial DBMS's (including Object Relational Extension) which is present in all The Semi-Structured Data Model (including XML) which is an added feature of most DBMS's Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 7

2.1.3 The Relational Data Model in Brief

 

The relational model is based on tables.

For instance, the following table shows 3 movies but you can imagine that there are many more rows.

Title

Gone with the wind Star Wars Wayne World

Year

1939 1977 1992

Length Genre

231 Drama 124 95 Sci-fi Comedy

8 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.1.3 The Relational Data Model in Brief (cont'd)

  

We are not going to talk about how to implement the database.

structure of the tables here and it will be postponed to higher courses in There are some operations that we can do on the tables. For example we can query the rows where the genre is 'comedy'.

As an example for the constraints , we may decide there could never be two movies with the same title and year in this table.

9 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.1.4 The Semi-structured Model in Brief

 

Semi-structured data resembles trees graphs , rather than tables or arrays.

or The principal manifestation of this viewpoint today is XML , a way to represent data by hierarchically nested tagged elements.

TYLIN: IBM ARC abandom it

The tags, similar to those used in HTML.

 

You can imagine tags as the column headers do in the relational model.

You can see an example of XML in the next slide which is the same as movies data.

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 10

2.1.4 The Semi-structured Model in Brief (cont'd)

1939 281 drama 1977 124 Scifi 1992 95 Comedy Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 11

2.1.5 Other Data Models

  

A modern trend is to add object-oriented features to the relational model.

There are two effects of object-orientation on relations: 1.

2.

Values can have structure , rather than being elementary types such as integer or strings.

Relations can have associated methods .

These extensions are called object-relational model.

12 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.1.5 Other Data Models (cont'd)

  

In earlier DBMS's, there were several other models like hierarchical model or network model.

Hierarchical model was a tree-oriented that unlike the modern DBMS's, it really operated at the physical level.

model Network model was a graph-oriented physical level model as well.

and also 13 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.1.6 Comparison of Modeling Approaches (IBM ARC; no more

    

Semi-structured models have more flexibility but relational model is still preferred.

In large databases, efficiency of access to data and modifying data are of great importance.

Ease of use is another factor of using DBMS's.

Both of these features can found in relational DBMS's.

Moreover, SQL , the structured query language, in spite of its simplicity, is a powerful language for database operations.

14 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

Section 2.2

BASICS OF RELATIONAL MODEL

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2.2 Basics of Relational Model

2.2.1 Attributes 2.2.2 Schemas 2.2.3 Tuples 2.2.4 Domains 2.2.5 Equivalent Representations of a Relation 2.2.6 Relation Instances 2.2.7 Keys of Relations 2.2.8 An Example Database Schema 2.2.9 Exercises for Section 2.2

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2.2 Basics of Relational Model

The relational model gives us a single way to represent data: as a two-dimensional table called a relation .

Movies relation

Title

Gone with the wind Star Wars Wayne World

Year

1939 1977 1992

Length Genre

231 Drama 124 95 Sci-fi Comedy

Each row ( tuple ) represents a movie and each column ( attribute ) represents a property of the movie.

17 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.2.1 Attributes

   

The columns of a relation are called attributes .

In the Movies relation (in previous slide), title, year, length, and genre are attributes.

Attributes appear at the top of the columns.

Like choosing descriptive names for variables in regular programming languages, attributes names should be chosen in such a way that describe the contents.

18 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.2.2 Schemas

  

The names of a relation and the set of attributes for the relation is called the schema of the relation.

We show the schema for the relation with the relation name followed by the parenthesized list of its attributes For instance, the following is the schema of relation Movies: Movies(title, year, length, genre) 19 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.2.2 Schemas (cont'd)

 

Note that the attributes are an order for the attributes.

a set, not a list but when we talk about relations, we often specify A database consists of one ore more relations. The set of schemas in the database is called a relational database schema , or just a database schema .

20 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.2.3 Tuples

  

The rows of a relation, other than the header row containing the attributes names, are called tuples .

A tuple has one component for each attribute of the relation.

For example, in the Movies relation, the first tuple has four components: 'Gone with the wind', 1939, 231, and drama for attributes title, year, length, and genre respectively.

21 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.2.3 Tuples (cont'd)

 

When we wish to write a tuple in isolation, not as a part of a relation, we normally use commas to separate components like this: ('Gone with the wind', 1939, 231, 'drama') Note that we always use the same order of the attributes to show the tuple in isolation.

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2.2.4 Domains

Tylin 8/29: Past, present, future data

The relational model requires that each component of each tuple be atomic .

  

That is, it must be of some elementary type such as integer or string .

It is not allowed for a value to be a set , list , array or any other type that reasonably can be broken into smaller components.

It's further assumed that associated with each attribute of a relation is a domain .

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2.2.4 Domains (cont'd)

We can include the domain for each attributes in a schema as follows: Movies(title:string, year:integer, length:integer, genre:string) 24 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.2.5 Equivalent Representations of a Relation

  

Relations are sets of tuples, not lists of tuples. In other words, the order of tuples in a relation has no significance .

Moreover, we can reorder the attributes relation as well.

of a Note that, when we change the order of the attributes, we should change the order of the contents as well.

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2.2.6 Relation Instances

    

Relations change over time. In other words, relations are not static .

For example, we insert tuples in the Movies relation over time, and also, we may delete or update some tuples as well.

Even the schema can be changed. In other words, we may add/delete an attribute to/from the schema.

We call a set of tuples for a given relation an instance of that relation.

Current instance , is the set of tuples that exists now.

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2.2.7 Keys of Relations

  

Relational model allows us to place some constraints on a schema.

One important constraint is called key constraint or simply a key .

A set of attributes (one or more) forms a key two tuples in the relation cannot have the same values in all the attributes of the key.

if 27 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.2.7 Keys of Relations (cont'd)

Example 2.1

For the Movies relation, we can assign the attributes title and year be the key of the relation.

In this way, the relation cannot have two tuples with the same title and year.

Note that the title by itself does not form a key because there are many movies over the years that have the same name. In other words, the title by itself is not unique and cannot identify a movie uniquely.

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 28

2.2.7 Keys of Relations (cont'd)

  

We indicate the attribute(s) contributing in the key by underlying them as follows: Movies(title, year, length, genre) Note that the key is a constraint for all possible instances of the relation, and not for a specific instance.

Most of the time, we use an artificial keys for a relation. For example, for the Movies relation, we could add a new attributes movie_id and assign it as the key. In this way, we could make sure it was unique for all possible tuples.

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2.2.8 An Example Database Schema

The database schema that are used during this book is as follows: Movies(title:string, year:integer, length:integer, genre:string, studioName:string, producerC#:integer) Moviestar(name:string, address:string, gender:char, birthdate:date) 30 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.2.8 An Example Database Schema (cont'd)

StarsIn(movieTitle:string, movieYear:integer, starName:string) MovieExec (name:string, addres:string, cert#:integer, netWorth:integer) Studio (name:string, address:string, presC#:integer) Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 31

2.2.9 Exercises for Section 2.2

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Section 2.3

DEFINING A RELATION SCHEMA IN SQL

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2.3 Defining a Relation Schema in SQL

2.3.1 Relations in SQL 2.3.2 Data Types 2.3.3 Simple Table Declaration 2.3.4 Modifying Relations Schemas 2.3.5 Default Values 2.3.6 Declaring Keys 2.3.7 Exercises for Section 2.3

34 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.3 Defining a Relation Schema in SQL

  

SQL, Structured Query Language, pronounced "sequel", is the principal language to describe , and manipulate relational database.

There is a standard called SQL-99 that most commercial databases implemented something similar, but not identical to, the standard.

There are two sub-languages for SQL:

 

DDL: Data Definition Language DML: Data Manipulation Language 35 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.3.1 Relations in SQL

 

SQL makes a distinction between three kinds of relations:

  

Stored relations : are called tables. These relations exists in database and usually we deal with them.

Views : are relations that do not exist but are constructed when needed.

Temporary tables tasks.

: are constructed temporarily by SQL processor when it executes queries or other We are going to discuss about tables in this chapter. Views will be covered in chapter 8 and temporary tables are never declared.

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2.3.2 Data Types

 

All attributes must have a data type.

The primitive data types supported by SQL are:

 

Character string

 

CHAR(n) : fixed length string of length n; short strings will be padded with trailing blank to make n characters.

VARCHAR(n) : variable length string up to n character; an end-marker or string-length is used to show the end of the string; the purpose is to save space.

Note that longer values will be truncated to fit.

Bit string

 

BIT(n) : fixed bit string of length n; BIT VARYING(n) : bit string of length up to n; 37 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.3.2 Data Types (cont'd)

The primitive data types (cont'd):

      

BOOLEAN: a logical value of TRUE, FALSE, or UNKNOWN (NULL) INT or INTEGER : integer value SHORTINT INTEGER's.

: short integer; usually the lower bound and the upper bound of SHORTINT is half of FLOAT or REAL : floating point number DOUBLE : double precision real number DECIMAL(n, d) : customized real number; NUMERIC(n, d) : a synonym for DECIMAL Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 38

2.3.2 Data Types (cont'd)

  

The primitive data types (cont'd):

DATE : represents a date value of the form 'yyyy-mm-dd'

TIME : represents a time value of the form 'HH:mm:ss' or 'HH:mm:ss.d' (d is a fraction of seconds) You can create a date constant like this: DATE '2011-08-24' You can create a time constant like this: TIME '16:09:25' or TIME '16:09:25.378'

Most databases have TIMESTAMP the form 'yyyy-mm-dd HH:mm:ss' data type of Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 39

2.3.3 Simple Table Declaration

The simplest form of relation declaration: CREATE TABLE tabName( attrib 1 type, attrib 2 type, ...

attrib n type); Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 40

2.3.3 Simple Table Declaration (cont'd)

Example 2.2

The relation Movies can be declared as follows: CREATE TABLE Movies( title CHAR(100), year INT, length INT, genre CHAR(10), studioName CHAR(30), producerC# INT); Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 41

2.3.3 Simple Table Declaration (cont'd)

Example 2.3

The relation MovieStar can be declared as follows: CREATE TABLE MovieStar( name CHAR(30), address VARCHAR(255), gender CHAR(1), birthdate DATE); The gender attribute can be 'M' or 'F'.

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2.3.4 Modifying Relations Schemas

 

To drop a relation R, execute the following SQL statement: DROP TABLE R; To alter the schema, we have several options.

 

To add attributes: ALTER TABLE R ADD attrib 1 type, ..., attrib n To drop attributes: ALTER TABLE R DROP attrib 1 , ..., attrib n ; type; 43 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.3.4 Modifying Relations Schemas (cont'd)

Example 2.4

Add an attribute to MoviesStar for phone data.

ALTER TABLE MovieStar ADD phone CHAR(16); Note that phone attribute will be NULL for all existing tuples .

Drop birthdate attribute ALTER TABLE MovieStar DROP bithdate; Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 44

2.3.5 Default Values

 

When we insert or modify a tuple, we sometimes do not have values for some attributes and we wish to assign a default values for them. To assign a default value for attribute1, we use the following syntax: CREATE TABLE tabName( attrib 1 type DEFAULT defaultValue , ...

attrib n type); Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 45

2.3.4 Modifying Relations Schemas (cont'd)

Example 2.5

Assign default value '?' for gender and default value '0000-00-00' for birthdate.

CREATE TABLE MovieStar( name CHAR(30), address VARCHAR(255), gender CHAR(1) DEFAULT '?', birthdate DATE DEFAULT DATE '0000-00-00'); Note that we can assign a default value when altering a schema as well: ALTER TABLE MovieStar ADD phone CHAR(16) DEFAULT 'unlisted' ; Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 46

2.3.6 Declaring Keys

There are two ways to declare an attribute or a set of attributes to be a key:

 

Method 1: CREATE TABLE tabName( attrib 1 ...

attrib n type PRIMARY KEY type); , Method 2: CREATE TABLE tabName( attrib 1 type, ...

attrib n type, PRIMARY KEY(attrib 1 ,...,attrib k ) ); Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 47

2.3.6 Declaring Keys (cont'd)

  

Note that if the key is a set of attributes, then we have to use method 2 but if the key is just one attribute, then either methods can be used.

There are two declarations that may be used to indicate key:

PRIMARY KEY

UNIQUE Both have the same effect but in PRIMARY KEY case, none of the attributes of the key can be NULL but in UNIQUE case, it's possible.

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2.3.6 Declaring Keys (cont'd)

Example 2.6

Declare name attribute as primary key in MovieStar relation.

CREATE TABLE MovieStar( name CHAR(30) PRIMARY KEY , address VARCHAR(255), gender CHAR(1) DEFAULT '?', birthdate DATE DEFAULT DATE '0000-00-00'); Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 49

2.3.6 Declaring Keys (cont'd)

Example 2.6 (cont'd) Alternatively, we can use the following syntax: CREATE TABLE MovieStar( name CHAR(30), address VARCHAR(255), gender CHAR(1) DEFAULT '?', birthdate DATE DEFAULT DATE '0000-00-00'), PRIMARY KEY (name) ; Note that UNIQUE can replace PRIMARY KEY.

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2.3.6 Declaring Keys (cont'd)

Example 2.7

Declare title and year attributes as primary key in Movies relation. CREATE TABLE Movies( title CHAR(100), year INT, length INT, genre CHAR(10), studioName CHAR(30), producerC# INT, PRIMARY KEY (title, year) ; Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 51

2.3.7 Exercises for Section 2.3

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Section 2.4

AN ALGEBRAIC QUERY LANGUAGE

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2.4 An Algebraic Query Language

2.4.1 Why Do We Need a Special Query Language?

2.4.2 What is an Algebra?

2.4.3 Overview of an Relational Algebra 2.4.4 Set Operations on Relations 2.4.5 Projection 2.4.6 Selection 2.4.7 Cartesian Product 2.4.8 Natural Joins 2.4.9 Theta-Joins 54 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.4 An Algebraic Query Language (cont'd)

2.4.10 Combining Operations to Form Queries 2.4.11 Naming and Renaming 2.4.12 Relationships Among Operations 2.4.13 A linear Notation for Algebraic Expressions 2.4.14 Exercises for Section 2.4

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2.4 An Algebraic Query Language

   

A DBMS needs a way to query the data and to modify the data.

We begin our study of operations on relations with a special algebra called relational algebra .

Relational algebra was used by some early DBMS's prototypes but is not used in current commercial DBMS's .

The real query language, SQL, uses relational algebra internally to optimize the process of retrieving the data.

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2.4.1 Why Do We Need a Special Query Language?

   

Why we don't use Java or C to retrieve the needed data?

For example, we could represent a tuple with an object in Java and we could represent a relation with an array of the objects! What would be the problem? Surprisingly, relational algebra is useful because it is less powerful than Java or C!

Ease of programming and producing highly optimized code by compiler are two important advantages of being less powerful.

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2.4.2 What is an Algebra?

   

In general, algebra consists of operators atomic operands .

and In arithmetic, the atomic operand are variables like x and y and constants like 10 and the operators are the simple arithmetic operators like: +, -, /, *.

Any algebra allows us to build expressions combining operators and atomic operands.

by Relational algebra next sub-sections.

is another example of algebra. Variables are relations and constants are finite relations. Operators will be covered in Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 58

2.4.3 Overview of an Relational Algebra

 

The operations fall into four classes:

   

Set operations : union, intersection, difference Operations that remove some parts of a relation:

 

Selection Projection – eliminates some tuples – eliminates some attributes Operations that combine the tuples of two relations:

 

Cartesian product : pairs the tuples of two relations in all possible ways Various kinds of joins : will be covered later Renaming : changes the schema without changing the tuples.

We refer to expressions of relational algebra as queries .

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2.4.4 Set Operations on Relations

  

The three most common operations on sets are:

  

Union : R

or both. S, is the set of elements that are in R or S Intersection : R

both R and S.

S, is the set of elements that are in Difference : R – S, is the set of elements that are in R but not in S.

Note that an element appears in a set once and duplicated values are not allowed.

When we apply these operations to relations, we need to put some conditions on R and S.

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2.4.4 Set Operations on Relations (cont'd)

 

The conditions of R and S

 

R and S must have the same schema. The order of attributes is important here and must be the same.

If the name of the attributes are different but the types are the same, we can rename the attributes temporarily by renaming operator.

61 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.4.4 Set Operations on Relations (cont'd)

Example 2.8

Given relations R and S as follows, compute: R

S, R

S, and R – S Name

Carrie Fisher Mark Hamill

Name

Carrie Fisher Harrison Ford

Gender

F M

Relation R Gender

F M

Relation S Birthdate

9/9/99 8/8/88

Birthdate

9/9/99 7/7/77

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2.4.4 Set Operations on Relations (cont'd)

Example 2.8 (cont'd) R

S Name

Carrie Fisher Mark Hamill Harrison Ford

Gender

F M M

Birthdate

9/9/99 8/8/88 7/7/77

R

S Name

Carrie Fisher

R - S Name

Mark Hamill

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 Gender

F

Gender

M

Birthdate

9/9/99

Birthdate

8/8/88

63

2.4.5 Projection

  

The projection operator produces a new relation that has only some of the attributes.

Projection operator in relational algebra is: π A1, A2, ..., An (R) This operator applies on the relation R and produces a new relation with only attributes A 1 , A 2 , …, A n from relation R. In other words, the schema of the new relation would have the following set of attributes: {A 1 , A 2 , …, A n } 64 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.4.5 Projection (cont'd)

Example 2.9

Given the relation Movies. Project the first three attributes.

Title

Star Wars

Year Length Genre

1977 124 sciFi Galaxy Quest 1999 104 Wayne’s World 1992 95

studioName ProducerC#

Fox Comedy Dreamworks Comedy Paramount 12345 67890 99999

The result relation Title

Star Wars

Year Length

1977 124 Galaxy Quest 1999 104 Wayne’s World 1992 95

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 65

2.4.5 Projection (cont'd)

Example 2.9 (cont'd) Project the Genre attribute.

The result relation Genre

sciFi Comedy

Note that in the relational algebra of sets , duplicate tuples are always eliminated. That's why 'Comedy' tuple is one instead of two.

66 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.4.6 Selection

   

The selection operator, applies to a relation R, and produces a new relation with a subset of R's tuples .

The tuples in the resulting relation are those that satisfy some condition C that involves the attributes of R.

Selection operator is denoted by: σ C (R) The schema for the resulting relation is the same as R's schema. 67 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.4.6 Selection (cont'd)

 

The operands in condition C are either constants or attributes of R.

We apply C to each tuple t of R by substituting.

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 68

2.4.6 Selection (cont'd)

Example 2.10

Given the Movies relation as follows: Find σ length >= 100 (Movies).

Title

Star Wars

Year Length Genre

1977 124 sciFi Galaxy Quest 1999 104 Wayne's World 1992 95

studioName ProducerC#

Fox Comedy DreamWorks Comedy Paramount 12345 67890 99999

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 69

2.4.6 Selection (cont'd)

Example 2.10 (cont'd) The first two tuples satisfy the condition. So, the result relation would be: Title

Star Wars Galaxy Quest

Year Length Genre

1977 124 sciFi 1999 104

studioName ProducerC#

Fox Comedy DreamWorks 12345 67890

70 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.4.6 Selection (cont'd)

Example 2.11

The Movies relation is given. Find the set of tuples that represent Fox movies at least 100 minutes long. So, we are looking for: σ length >= 100 AND studioName = 'FOX' (Movies).

Title

Star Wars

Year Length Genre

1977 124 sciFi Galaxy Quest 1999 104 Wayne's World 1992 95

studioName ProducerC#

Fox Comedy DreamWorks Comedy Paramount 12345 67890 99999

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 71

2.4.6 Selection (cont'd)

Example 2.11 (cont'd) The result would be: Title

Star Wars

Year Length Genre

1977 124 sciFi

studioName ProducerC#

Fox 12345

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 72

2.4.7 Cartesian Product

  

The Cartesian Product (or of S.

cross product is the set of pairs that can be formed by or just product for simplicity) of two sets R and S choosing the first element of the pair to be any element of R and the second any element This product is denote by R X S.

In relational algebra, the sets are the relations and the members are the tuples.

73 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.4.7 Cartesian Product (cont'd)

Example 2.12

A

1 3

B

2 4 4 9

B

2

C

5 7 10

D

6 8 11 3 3 3 1 1

A

1 4 4 4 2 2

R.B S.B C

2 2 5 4 9 7 10 2 4 9 5 7 10

Relation R Relation S Result R X S Note that attribute B is in both schemas, it has been R.B and S.B in the result to disambiguate them.

D

6 8 11 6 8 11

74 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.4.8 Natural Joins

    

More often the cross product is not what we want. Usually we want to pair only those tuples that match in some certain conditions.

The simplest way is the natural join of two relation R and S.

In this join we pair those tuples that agree with the common attributes in R and S.

Natural join is denoted by: R ∞ S A tuple that fails to pair with any tuple of the other relation is said to be a dangling tuple .

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 75

2.4.8 Natural Joins (cont'd)

Example 2.13

A

1 3

B

2 4 4 9

B

2

C

5 7 10

D

6 8 11

A

1 3

B

2 4

C

5 7

Relation R Relation S Result R ∞ S D

6 8

Note that attribute B is in both schemas, and since they should be equal in the result, therefore, one copy of it is enough in the result.

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 76

2.4.8 Natural Joins (cont'd)

Example 2.14

A

1 6 9

B

2 7 7

C

3 8 8

B

2 2 7

C

3 3 8

D

4 5 10

A

1 1 6 9

B

2 2 7 7

C

3 3 8 8

Relation U Relation V Result U ∞ V D

4 5 10 10

Note that attribute B and C are in both schemas, and since they should be equal in the result, therefore, one copy of them is enough in the result.

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 77

2.4.9 Theta-Joins

   

Equating the shared attributes is just one way that is used in natural join. It is sometimes desirable to pair tuples from two relations on some other basis.

Historically, the theta refers to an arbitrary condition. We use C as the condition rather than θ.

Theta-join is denoted by: R ∞ C S 78 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.4.9 Theta-Joins (cont'd)

Example 2.15

A

1 6 9

B

2 7 7

C

3 8 8

Relation U B

2 2

C

3 3 7 8

Relation V D

4 5 10

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 A

1 6 9 1 1

U.B U.C V.B V.C

2 3 2 3 7 7 2 2 3 3 8 8 2 7 7 7 3 8 8 8

Result: U ∞ A

4 5 10 10 10

79

2.4.9 Theta-Joins (cont'd)

Example 2.16

A

1 6 9

B

2 7 7

C

3 8 8

Relation U B

2 2

C

3 3 7 8

Relation V D

4 5 10

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 A U.B U.C V.B V.C

D

1 2 3 7 8

Result: U ∞ A V.B

10

V 80

2.4.10 Combining Operations to Form Queries

  

Relational algebra like all other algebras, allows us to form operations.

complex expressions by applying operations to the result of other One can construct expressions of relational algebra by applying operators to sub expressions, using parenthesis when necessary to indicate grouping of operands.

It is also possible to represent expressions as expression trees .

81 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.4.10 Combining Operations to Form Queries (cont'd)

Example 2.17

What are the titles and years of Movies made by fox that are at least 100 minutes long?

One solution would be: 1.

Select those tuples that have length >= 100.

2.

3.

4.

Select those tuples that have studioName = 'Fox'.

Compute the intersection of (1) and (2).

Project the relation from (3) onto attributes title and year.

82 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.4.10 Combining Operations to Form Queries (cont'd)

Example 2.17 (cont'd) Here is the suggested expression tree!

π title, year

σ length >= 100 σ studioName = 'Fox' Movies Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 Movies 83

2.4.10 Combining Operations to Form Queries (cont'd)

Example 2.17 (cont'd) Alternatively, we could represent the same expression in a linear notation as follows: π title,year (σ length>=100 ( Movies )

σ studioName=‘Fox’ ( Movies )) There are always more than one solution for a problem. For instance, the following expression does the same job but more efficiently. Can you say why?

π title,year (σ length>=100 AND studioName=‘Fox’ ( Movies )) Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 84

2.4.11 Naming and Renaming

   

Sometimes we need to change the relation's name or change its attributes names.

The following operator renames the relation R to S and renames the attributes as well: ρ S(A1, A2, …, An ) (R) Note that the resulting relation has the same tuples. In other words, the renaming operator does not change the relation's contents.

If we just want to rename the relation's name, then we can eliminate the attributes as: ρ S (R) Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 85

2.4.11 Naming and Renaming (cont'd)

Example 2.18

This is the same as example 2.12 but it uses the renaming operator to avoid ambiguity between the attributes.

A

1 3

B

2 4

B

2 4 9

C

5 7 10

Relation R Relation S D

6 8 11

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

3 3 3

A

1 1 1 4 4 4

B

2 2 2 2 4 9

X

2 4 9

R X ρ S(X, C, D) (S) C

5 7 10 5 7 10

D

6 8 11 6 8 11

86

2.4.11 Naming and Renaming (cont'd)

Example 2.18 (cont'd) Alternatively, we could make the product first and then rename the attributes as follows: ρ RS(A, B, X, C, D) (R X S) Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 87

2.4.12 Relationships Among Operations

   

Some operations can be expressed in terms of other operations.

For instance, the following identity is valid: R

S = R – (R – S) Also, theta-join can be expressed by cross product and selection as follows: R ∞ C S = σ C (R X S) The other equality is between natural-join and cross product as follows: R ∞ S = π L (σ C (R X S)) 88 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.4.13 A linear Notation for Algebraic Expressions

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 89

2.4.14 Exercises for Section 2.4

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 90

Section 2.5

CONSTRAINTS ON RELATIONS

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 91

2.5 Constraints on Relations

2.5.1 Relational Algebra as a Constraint Language 2.5.2 Referential Integrity Constraints 2.5.3 Key Constraints 2.5.4 Additional Constraint Examples 2.5.5 Exercises for Section 2.5

92 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.5 Constraints on Relations

  

A constraint is the ability to restrict the data that may be stored in a database.

So far we have seen one kind of constraints, the key.

Constraints can be expressed in relational algebra.

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 93

2.5.1 Relational Algebra as a Constraint Language

There are two ways in which we can use expressions of relational algebra to express constraints: 1.

2.

If R is an expression of a relational algebra, then R= R”.

is a constraint that says “the value of R must be empty”, or equivalently, “There are no tuples in If R and S are expressions of relational algebra, then R

S is a constraint that says “Every tuple in R must also be in S.” 94 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.5.2 Referential Integrity Constraints

 

Referential Integrity constraint asserts that a value appearing in one relation must also appear in another related relation.

For instance, in the Movies database, should we see a StarsIn tuple that has a person p in the starName attribute, we would expect that p appears as the name of some star in the MovieStar relation.

95 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.5.2 Referential Integrity Constraints (cont'd)

 

In general, if we have any value v as the component in attribute A of some tuple in one relation R, then v must appear in a particular component, say for attribute B, of some tuple of another relation S.

We can express this integrity constraint in relational algebra as: π A (R)

π B (S) or equivalently as: π A (R) π B (S) =

96 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.5.2 Referential Integrity Constraints (cont'd)

Example 2.21

Consider the following schemas: Movies(title, year, length, genre, studioName, producerC#) MovieExec(name, address, cert#, netWorth) The producer of a movie should be an executive and should have a record in MovieExec.

Therefore, we must expect that producerC# in Movies relation should appear as cert# in one tuple of MovieExec relation.

π producerC# (Movies)

π cert# (MovieExec) Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 97

2.5.2 Referential Integrity Constraints (cont'd)

Example 2.22 (multi-value referential integrity) Consider the following schemas: StarsIn(movieTitle, movieYear, starName) Movies(title, year, length, genre, studioName, producerC#) The combined movieTitle and movieYear in StarsIn relation must appear in one tuple of Movies relation.

π movieTitle, movieYear (StarsIn)

π title, year (Movies) 98 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.5.3 Key Constraints

Example 2.23

Consider the following schema: MovieStar(name, address, gender, birthdate) The attribute 'name' is the key of this relation.

That is, if two tuples have the same name, then they must have the same address, gender, and birthdate. To express this constraint in relational algebra, we make Cartesian product of the relation with itself as follows: 99 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.5.3 Key Constraints (cont'd)

Example 2.23 (cont'd) σ MS1.name = MS2.name AND MS1.address <> MS2.address

(MS1 X MS2) =

Note that we renamed the MovieStar relation to MS1 and MS2 to disambiguate the references to them.

Here are the renaming operators: ρ MS1 ρ MS2 (MovieStar) (MovieStar) 100 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.5.4 Additional Constraint Examples

Example 2.24

Consider the following schema: MovieStar(name, address, gender, birthdate) Suppose we wish to specify that the only legal values for the gender attribute are 'F' and 'M'.

We can express this constraint in relational algebra as: σ gender <> 'F' AND gender <> 'M' (MovieStar) =

101 Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011

2.5.4 Additional Constraint Examples (cont'd)

Example 2.25

Consider the following schema: MovieExec(name, address, cert#, netWorth) Studio(name, address, presC#) Suppose we wish to require that one must have a net worth of at least $10,000,000 to be the president of a movie studio.

The constraint can be expressed as: σ netWorth < 10000000 (Studio ∞ presC# = cert# or equivalently as: MovieExec) =

π precC# (Studio)

π cert# (σ netWorth < 10000000 (MovieExec)) Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 102

2.5.5 Exercises for Section 2.5

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 103

2.6 Summary of Chapter 2

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2.7 References for Chapter 2

Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 105