Object-Oriented Database Development (Hoffer Chap 15)

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Object-Oriented Database Development (Hoffer Chap
15)

• University of California, Berkeley
• School of Information Management and Systems
• SIMS 257 Database Management

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Lecture Outline

• Review
• Object Oriented DBMS
• Inverted File and Flat File DBMS
• Object-Relational DBMS (revisited)
• Intelligent DBMS
• Object Oriented Database Development
• Design using UML
• Construction with ODL
• Querying with OQL

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Lecture Outline

• Review
• Object Oriented DBMS
• Inverted File and Flat File DBMS
• Object-Relational DBMS (revisited)
• Intelligent DBMS
• Object Oriented Database Development
• Design using UML
• Construction with ODL
• Querying with OQL

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Object-Oriented DBMS Basic Concepts

• Each real-world entity is modeled by an object.
  Each object is associated with a unique
  identifier (sometimes call the object ID or OID)

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Object-Oriented DBMS Basic Concepts

• Each object has a set of instance attributes (or
  instance variables) and methods.
• The value of an attribute can be an object or set
  of objects. Thus complex object can be
  constructed from aggregations of other objects.
• The set of attributes of the object and the set
  of methods represent the object structure and
  behavior, respectively

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Object-Oriented DBMS Basic Concepts

• The attribute values of an object represent the
  objects status.
• Status is accessed or modified by sending
  messages to the object to invoke the
  corresponding methods

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Object-Oriented DBMS Basic Concepts

• Objects sharing the same structure and behavior
  are grouped into classes.
• A class represents a template for a set of
  similar objects.
• Each object is an instance of some class.

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Object-Oriented DBMS Basic Concepts

• A class can be defined as a specialization of of
  one or more classes.
• A class defined as a specialization is called a
  subclass and inherits attributes and methods from
  its superclass(es).

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Object-Oriented DBMS Basic Concepts

• An OODBMS is a DBMS that directly supports a
  model based on the object-oriented paradigm.
• Like any DBMS it must provide persistent storage
  for objects and their descriptions (schema).
• The system must also provide a language for
  schema definition and and for manipulation of
  objects and their schema
• It will usually include a query language,
  indexing capabilities, etc.

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Generalization Hierarchy
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Inverted File DBMS

• Usually similar to Hierarchic DBMS in record
  structure
• Support for repeating groups of fields and
  multiple value fields
• All access is via inverted file indexes to DBS
  specified fields.
• Examples ADABAS DBMS from Software AG -- used in
  the MELVYL system

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Flat File DBMS

• Data is stored as a simple file of records.
• Records usually have a simple structure
• May support indexing of fields in the records.
• May also support scanning of the data
• No mechanisms for relating data between files.
• Usually easy to use and simple to set up

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Object Relational Data Model

• Class, instance, attribute, method, and integrity
  constraints
• OID per instance
• Encapsulation
• Multiple inheritance hierarchy of classes
• Class references via OID object references
• Set-Valued attributes
• Abstract Data Types

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PostgreSQL Classes

• The fundamental notion in Postgres is that of a
  class, which is a named collection of object
  instances. Each instance has the same collection
  of named attributes, and each attribute is of a
  specific type. Furthermore, each instance has a
  permanent object identifier (OID) that is unique
  throughout the installation. Because SQL syntax
  refers to tables, we will use the terms table and
  class interchangeably. Likewise, an SQL row is an
  instance and SQL columns are attributes.

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Creating a Class

• You can create a new class by specifying the
  class name, along with all attribute names and
  their types
• CREATE TABLE weather (
• city varchar(80),
• temp_lo int, -- low
  temperature
• temp_hi int, -- high
  temperature
• prcp real, --
  precipitation
• date date
• )

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Intelligent Database Systems

• Intelligent DBS are intended to handle more than
  just data, and may be used in tasks involving
  large amounts of information where analysis and
  discovery are needed.

The following is based on Intelligent Databases
by Kamran Parsaye, Mark Chignell, Setrag
Khoshafian and Harry Wong AI Expert, March 1990,
v. 5 no. 3. Pp 38-47
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Intelligent Database Systems

• They represent the evolution and merging of
  several technologies
• Automatic Information Discovery
• Hypermedia
• Object Orientation
• Expert Systems
• Conventional DBMS

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Intelligent Database Systems
Automatic discovery
Expert Systems
Intelligent Databases
Hypermedia
Object Orientation
Traditional Databases
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Intelligent Databases

• Intelligent Database Engine
• OO support
• Inference features
• Global optimization
• Rule manager
• Explanation manager
• Transaction manager
• Metadata manager
• Access module
• Multimedia manager

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Lecture Outline

• Review
• Object Oriented DBMS
• Inverted File and Flat File DBMS
• Object-Relational DBMS (revisited)
• Intelligent DBMS
• Object Oriented Database Development
• Construction with ODL
• Design using UML
• Querying with OQL

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Chapter 15Object-Oriented Database Development

• Modern Database Management
• 6th Edition
• Jeffrey A. Hoffer, Mary B. Prescott, Fred R.
  McFadden

This Lecture uses the slides following from
www.prenhall.com/hoffer
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Object Definition Language (ODL)

• Corresponds to SQLs DDL (Data Definition
  Language)
• Specify the logical schema for an object-oriented
  database
• Based on the specifications of Object Database
  Management Group (ODMG)

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Defining a Class

• class keyword for defining classes
• attribute keyword for attributes
• operations return type, name, parameters in
  parentheses
• relationship keyword for establishing
  relationship

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Defining an Attribute

• Value can be either
• Object identifier OR Literal
• Types of literals
• Atomic a constant that cannot be decomposed
  into components
• Collection multiple literals or object types
• Structure a fixed number of named elements,
  each of which could be a literal or object type
• Attribute ranges
• Allowable values for an attribute
• enum for enumerating the allowable values

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Kinds of Collections

• Set unordered collection without duplicates
• Bag unordered collection that may contain
  duplicates
• List ordered collection, all the same type
• Array dynamically sized ordered collection,
  locatable by position
• Dictionary unordered sequence of key-value
  pairs without duplicates

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Defining Structures

• Structure user-defined type with components
• struct keyword
• Example
• struct Address
• String street_address
• String city
• String state
• String zip

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Defining Operations

• Return type
• Name
• Parentheses following the name
• Arguments within the parentheses

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Defining Relationships

• Only unary and binary relationships allowed
• Relationships are bi-directional
• implemented through use of inverse keyword
• ODL relationships are specified
• relationship indicates that class is on many-side
• relationship set indicates that class is on
  one-side and other class (many) instances
  unordered
• relationship list indicates that class is on
  one-side and other class (many) instances ordered

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Figure 15-1 UML class diagram for a university
database
The following slides illustrate the ODL
implementation of this UML diagram
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Figure 15-2 ODL Schema for university database
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Figure 15-2 ODL Schema for university database
class keyword begins the class definition.Class
components enclosed between and
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Figure 15-2 ODL Schema for university database
specify allowable values using enum
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Figure 15-2 ODL Schema for university database
extent the set of all instances of the class
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Figure 15-2 ODL Schema for university database
Operation definition return type, name, and
argument list. Arguments include data types and
names
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Figure 15-2 ODL Schema for university database
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Figure 15-2 ODL Schema for university database
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Figure 15-2 ODL Schema for university database
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Figure 15-3 UML class diagram for an employee
project database
(a) Many-to-many relationship with an association
class
Note In order to capture special features of
assignment, this should be converted into two 1N
relationships
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Figure 15-3 UML class diagram for an employee
project database
(b) Many-to many relationship broken into two
one-to-many relationships
class Employee (extent employees key
emp_id) . attribute set (string)
skills_required
Note key indicates indentifier (candidate key)
Note attribute set indicates a multivalued
attribute
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Figure 15-4 UML class diagram showing employee
generalization
class Employee extends Employee (
. .
Note extends denotes subclassing
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Figure 15-5 UML class diagram showing student
generalization
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Creating Object Instances

• Specify a tag that will be the object identifier
• MBA699 course ()
• Initializing attributes
• Cheryl student (name Cheryl Davis,
  dateOfBirth4/5/77)
• Initializing multivalued attributes
• Dan employee (emp_id 3678, name Dan Bellon,
  skills Database design, OO
  Modeling)
• Establishing links for relationship
• Cheryl student (takes OOAD99F, Telecom99F,
  Java99F)

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Querying Objects in the OODB

• Object Query Language (OQL)
• ODMG standard language
• Similar to SQL-92
• Some differences
• Joins use classs relationship name
• Select x.enrollment from courseofferings x,
  x.belongs_to y where y.crse_course MBA 664
  and x.section 1
• Using a set in a query
• Select emp_id, name from employees where
  Database Design in skills

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Current ODBMS Products

• Rising popularity due to
• CAD/CAM applications
• Geographic information systems
• Multimedia
• Web-based applications
• Increasingly complex data types
• Applications of ODBMS
• Bill-of-material
• Telecommunications navigation
• Health care
• Engineering design
• Finance and trading

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Table15-1 ODBMS Products