Chapter 8: Object-Oriented Databases

©Silberschatz, Korth and Sudarshan8.1Database System Concepts

Chapter 8: Object-Oriented DatabasesChapter 8: Object-Oriented Databases

Need for Complex Data Types

The Object-Oriented Data Model

Object-Oriented Languages

Persistent Programming Languages

Persistent C++ Systems


Need for Complex Data TypesNeed for Complex Data Types

Traditional database applications in data processing had conceptually simple data types Relatively few data types, first normal form holds

Complex data types have grown more important in recent years E.g. Addresses can be viewed as a

Single string, or Separate attributes for each part, or Composite attributes (which are not in first normal form)

E.g. it is often convenient to store multivalued attributes as-is, without creating a separate relation to store the values in first normal form

Applications computer-aided design, computer-aided software engineering multimedia and image databases, and document/hypertext

databases.


Object-Oriented Data ModelObject-Oriented Data Model

Loosely speaking, an object corresponds to an entity in the E-R model.

The object-oriented paradigm is based on encapsulating code and data related to an object into single unit.

The object-oriented data model is a logical data model (like the E-R model).

Adaptation of the object-oriented programming paradigm (e.g., Smalltalk, C++) to database systems.


Object StructureObject Structure

An object has associated with it: A set of variables that contain the data for the object. The value of

each variable is itself an object.

A set of messages to which the object responds; each message may have zero, one, or more parameters.

A set of methods, each of which is a body of code to implement a message; a method returns a value as the response to the message

The physical representation of data is visible only to the implementor of the object

Messages and responses provide the only external interface to an object.

The term message does not necessarily imply physical message passing. Messages can be implemented as procedure invocations.


Object ClassesObject Classes

Similar objects are grouped into a class; each such object is called an instance of its class

All objects in a class have the same Variables, with the same types

message interface

methods

The may differ in the values assigned to variables

Example: Group objects for people into a person class

Classes are analogous to entity sets in the E-R model


Class Definition ExampleClass Definition Example

class employee {/*Variables */

string name;string address;date start-date;int salary;

/* Messages */int annual-salary();string get-name();string get-address();int set-address(string new-address);int employment-length();

};

Methods to read and set the other variables are also needed with strict encapsulation

Methods are defined separately E.g. int employment-length() { return today() – start-date;}

int set-address(string new-address) { address = new-address;}


Inheritance (Cont.)Inheritance (Cont.)

Place classes into a specialization/IS-A hierarchy variables/messages belonging to class person are

inherited by class employee as well as customer

Result is a class hierarchy

Note analogy with ISA Hierarchy in the E-R model


Class Hierarchy DefinitionClass Hierarchy Definition

class person{stringname;stringaddress:};

class customer isa person {int credit-rating;};

class employee isa person {date start-date;int salary;};

class officer isa employee {int office-number,int expense-account-number,};

...


Example of Multiple InheritanceExample of Multiple Inheritance

Class DAG for banking example.


Object-Oriented LanguagesObject-Oriented Languages

Object-oriented concepts can be used in different ways Object-orientation can be used as a design tool, and be

encoded into, for example, a relational database

analogous to modeling data with E-R diagram and then converting to a set of relations)

The concepts of object orientation can be incorporated into a programming language that is used to manipulate the database.

Object-relational systems – add complex types and object-orientation to relational language.

Persistent programming languages – extend object-oriented programming language to deal with databases by adding concepts such as persistence and collections.

End of Chapter End of Chapter


Chapter 9: Object-Relational DatabasesChapter 9: Object-Relational Databases

Nested Relations

Complex Types and Object Orientation

Querying with Complex Types

Creation of Complex Values and Objects

Comparison of Object-Oriented and Object-Relational Databases


Object-Relational Data ModelsObject-Relational Data Models

Extend the relational data model by including object orientation and constructs to deal with added data types.

Allow attributes of tuples to have complex types, including non-atomic values such as nested relations.

Preserve relational foundations, in particular the declarative access to data, while extending modeling power.

Upward compatibility with existing relational languages.


Example of a Nested RelationExample of a Nested Relation

Example: library information system

Each book has title,

a set of authors,

Publisher, and

a set of keywords

Non-1NF relation books


1NF Version of Nested Relation1NF Version of Nested Relation

1NF version of books

flat-books


4NF Decomposition of Nested Relation4NF Decomposition of Nested Relation

Remove awkwardness of flat-books by assuming that the following multivalued dependencies hold: title author

title keyword

title pub-name, pub-branch

Decompose flat-doc into 4NF using the schemas: (title, author)

(title, keyword)

(title, pub-name, pub-branch)


4NF Decomposition of 4NF Decomposition of flatflat––booksbooks


Problems with 4NF SchemaProblems with 4NF Schema

4NF design requires users to include joins in their queries.

1NF relational view flat-books defined by join of 4NF relations: eliminates the need for users to perform joins,

but loses the one-to-one correspondence between tuples and documents.

And has a large amount of redundancy

Nested relations representation is much more natural here.


Structured and Collection TypesStructured and Collection Types

Structured types can be declared and used in SQL

create type Publisher as (name varchar(20), branch varchar(20))

create type Book as (title varchar(20), author-array varchar(20) array [10], pub-date date, publisher Publisher, keyword-set setof(varchar(20)))

Note: setof declaration of keyword-set is not supported by SQL:1999

Using an array to store authors lets us record the order of the authors

Structured types can be used to create tables

create table books of Book Similar to the nested relation books, but with array of authors

instead of set


Structured Types (Cont.)Structured Types (Cont.) We can create tables without creating an intermediate type

For example, the table books could also be defined as follows: create table books (title varchar(20), author-array varchar(20) array[10], pub-date date, publisher Publisher keyword-list setof(varchar(20)))

Methods can be part of the type definition of a structured type:

create type Employee as ( name varchar(20), salary integer) method giveraise (percent integer)

We create the method body separately

create method giveraise (percent integer) for Employee begin set self.salary = self.salary + (self.salary * percent) / 100; end


InheritanceInheritance Suppose that we have the following type definition for people:

create type Person (name varchar(20),

address varchar(20)) Using inheritance to define the student and teacher types

create type Student under Person (degree varchar(20), department varchar(20)) create type Teacher under Person (salary integer, department varchar(20))

Subtypes can redefine methods by using overriding method in place of method in the method declaration


Multiple InheritanceMultiple Inheritance

SQL:1999 does not support multiple inheritance If our type system supports multiple inheritance, we can

define a type for teaching assistant as follows:create type Teaching Assistant

under Student, Teacher To avoid a conflict between the two occurrences of

department we can rename them

create type Teaching Assistant under Student with (department as student-dept), Teacher with (department as teacher-dept)


Collection Valued Attributes (Cont.)Collection Valued Attributes (Cont.)

We can access individual elements of an array by using indices E.g. If we know that a particular book has three authors, we could

write:

select author-array[1], author-array[2], author-array[3]from bookswhere title = `Database System Concepts’


SQL FunctionsSQL Functions

Define a function that, given a book title, returns the count of the number of authors (on the 4NF schema with relations books4 and authors).

create function author-count(name varchar(20)) returns integer begin declare a-count integer; select count(author) into a-count from authors where authors.title=name return a=count; end

Find the titles of all books that have more than one author.

select namefrom books4where author-count(title)> 1


Procedural ConstructsProcedural Constructs

SQL:1999 supports a rich variety of procedural constructs

Compound statement is of the form begin … end,

may contain multiple SQL statements between begin and end.

Local variables can be declared within a compound statements

While and repeat statementsdeclare n integer default 0;while n < 10 do

set n = n+1end while

repeat set n = n – 1

until n = 0end repeat


Procedural Constructs (Cont.)Procedural Constructs (Cont.)

For loop Permits iteration over all results of a query E.g. find total of all balances at the Perryridge branch

declare n integer default 0; for r as select balance from account where branch-name = ‘Perryridge’ do

set n = n + r.balance end for


Comparison of O-O and O-R DatabasesComparison of O-O and O-R Databases

Summary of strengths of various database systems:

Relational systems simple data types, powerful query languages, high protection.

Persistent-programming-language-based OODBs complex data types, integration with programming language, high

performance.

Object-relational systems complex data types, powerful query languages, high protection.

Note: Many real systems blur these boundaries E.g. persistent programming language built as a wrapper on a

relational database offers first two benefits, but may have poor performance.

End of ChapterEnd of Chapter

Chapter 10: XMLChapter 10: XML


IntroductionIntroduction

XML: Extensible Markup Language

Defined by the WWW Consortium (W3C)

Originally intended as a document markup language not a database language Documents have tags giving extra information about sections of the

document

E.g. <title> XML </title> <slide> Introduction …</slide>

Derived from SGML (Standard Generalized Markup Language), but simpler to use than SGML

Extensible, unlike HTML

Users can add new tags, and separately specify how the tag should be handled for display

Goal was (is?) to replace HTML as the language for publishing documents on the Web


XML Introduction (Cont.)XML Introduction (Cont.)

The ability to specify new tags, and to create nested tag structures made XML a great way to exchange data, not just documents. Much of the use of XML has been in data exchange applications, not as a

replacement for HTML

Tags make data (relatively) self-documenting E.g.

<bank> <account>

<account-number> A-101 </account-number> <branch-name> Downtown </branch-name> <balance> 500 </balance>

</account> <depositor>

<account-number> A-101 </account-number> <customer-name> Johnson </customer-name>

</depositor>

</bank>


XML: MotivationXML: Motivation

Data interchange is critical in today’s networked world Examples:

Banking: funds transfer

Order processing (especially inter-company orders)

Scientific data

– Chemistry: ChemML, …

– Genetics: BSML (Bio-Sequence Markup Language), …

Paper flow of information between organizations is being replaced by electronic flow of information

Each application area has its own set of standards for representing information

XML has become the basis for all new generation data interchange formats


XML Motivation (Cont.)XML Motivation (Cont.)

Earlier generation formats were based on plain text with line headers indicating the meaning of fields Similar in concept to email headers

Does not allow for nested structures, no standard “type” language

Tied too closely to low level document structure (lines, spaces, etc)

Each XML based standard defines what are valid elements, using XML type specification languages to specify the syntax

DTD (Document Type Descriptors)

XML Schema

Plus textual descriptions of the semantics

XML allows new tags to be defined as required However, this may be constrained by DTDs

A wide variety of tools is available for parsing, browsing and querying XML documents/data


Structure of XML DataStructure of XML Data

Tag: label for a section of data

Element: section of data beginning with <tagname> and ending with matching </tagname>

Elements must be properly nested Proper nesting

<account> … <balance> …. </balance> </account>

Improper nesting

<account> … <balance> …. </account> </balance>

Formally: every start tag must have a unique matching end tag, that is in the context of the same parent element.

Every document must have a single top-level element


Example of Nested ElementsExample of Nested Elements <bank-1> <customer>

<customer-name> Hayes </customer-name> <customer-street> Main </customer-street> <customer-city> Harrison </customer-city> <account>

<account-number> A-102 </account-number> <branch-name> Perryridge </branch-name> <balance> 400 </balance>

</account> <account> … </account>

</customer> . .

</bank-1>


Motivation for NestingMotivation for Nesting

Nesting of data is useful in data transfer Example: elements representing customer-id, customer name, and

address nested within an order element

Nesting is not supported, or discouraged, in relational databases With multiple orders, customer name and address are stored

redundantly

normalization replaces nested structures in each order by foreign key into table storing customer name and address information

Nesting is supported in object-relational databases

But nesting is appropriate when transferring data External application does not have direct access to data referenced

by a foreign key


Structure of XML Data (Cont.)Structure of XML Data (Cont.)

Mixture of text with sub-elements is legal in XML. Example:

<account> This account is seldom used any more. <account-number> A-102</account-number> <branch-name> Perryridge</branch-name> <balance>400 </balance></account>

Useful for document markup, but discouraged for data representation


AttributesAttributes

Elements can have attributes <account acct-type = “checking” >

<account-number> A-102 </account-number> <branch-name> Perryridge </branch-name> <balance> 400 </balance>

</account>

Attributes are specified by name=value pairs inside the starting tag of an element

An element may have several attributes, but each attribute name can only occur once

<account acct-type = “checking” monthly-fee=“5”>


Attributes Vs. SubelementsAttributes Vs. Subelements

Distinction between subelement and attribute In the context of documents, attributes are part of markup, while

subelement contents are part of the basic document contents

In the context of data representation, the difference is unclear and may be confusing

Same information can be represented in two ways

– <account account-number = “A-101”> …. </account>

– <account> <account-number>A-101</account-number> … </account>

Suggestion: use attributes for identifiers of elements, and use subelements for contents


More on XML SyntaxMore on XML Syntax

Elements without subelements or text content can be abbreviated by ending the start tag with a /> and deleting the end tag <account number=“A-101” branch=“Perryridge” balance=“200 />

To store string data that may contain tags, without the tags being interpreted as subelements, use CDATA as below

<![CDATA[<account> … </account>]]>

Here, <account> and </account> are treated as just strings


XML Document SchemaXML Document Schema

Database schemas constrain what information can be stored, and the data types of stored values

XML documents are not required to have an associated schema

However, schemas are very important for XML data exchange Otherwise, a site cannot automatically interpret data received from

another site

Two mechanisms for specifying XML schema Document Type Definition (DTD)

Widely used

XML Schema

Newer, not yet widely used


Document Type Definition (DTD)Document Type Definition (DTD)

The type of an XML document can be specified using a DTD

DTD constraints structure of XML data What elements can occur

What attributes can/must an element have

What subelements can/must occur inside each element, and how many times.

DTD does not constrain data types All values represented as strings in XML

DTD syntax <!ELEMENT element (subelements-specification) >

<!ATTLIST element (attributes) >


Element Specification in DTDElement Specification in DTD

Subelements can be specified as names of elements, or #PCDATA (parsed character data), i.e., character strings EMPTY (no subelements) or ANY (anything can be a subelement)

Example<! ELEMENT depositor (customer-name account-number)>

<! ELEMENT customer-name(#PCDATA)><! ELEMENT account-number (#PCDATA)>

Subelement specification may have regular expressions <!ELEMENT bank ( ( account | customer | depositor)+)>

Notation:

– “|” - alternatives

– “+” - 1 or more occurrences

– “*” - 0 or more occurrences


Bank DTDBank DTD

<!DOCTYPE bank [<!ELEMENT bank ( ( account | customer | depositor)+)><!ELEMENT account (account-number branch-name balance)><! ELEMENT customer(customer-name customer-street customer-city)><! ELEMENT depositor (customer-name account-number)><! ELEMENT account-number (#PCDATA)><! ELEMENT branch-name (#PCDATA)><! ELEMENT balance(#PCDATA)><! ELEMENT customer-name(#PCDATA)><! ELEMENT customer-street(#PCDATA)><! ELEMENT customer-city(#PCDATA)>

]>


XML SchemaXML Schema

XML Schema is a more sophisticated schema language which addresses the drawbacks of DTDs. Supports Typing of values

E.g. integer, string, etc

Also, constraints on min/max values

User defined types

Is itself specified in XML syntax, unlike DTDs

More standard representation, but verbose

Is integrated with namespaces

Many more features

List types, uniqueness and foreign key constraints, inheritance ..

BUT: significantly more complicated than DTDs, not yet widely used.


XML Schema Version of Bank DTDXML Schema Version of Bank DTD

<xsd:schema xmlns:xsd=http://www.w3.org/2001/XMLSchema>

<xsd:element name=“bank” type=“BankType”/>

<xsd:element name=“account”><xsd:complexType> <xsd:sequence> <xsd:element name=“account-number” type=“xsd:string”/> <xsd:element name=“branch-name” type=“xsd:string”/> <xsd:element name=“balance” type=“xsd:decimal”/> </xsd:squence></xsd:complexType>

</xsd:element>….. definitions of customer and depositor ….

<xsd:complexType name=“BankType”><xsd:squence>

<xsd:element ref=“account” minOccurs=“0” maxOccurs=“unbounded”/><xsd:element ref=“customer” minOccurs=“0” maxOccurs=“unbounded”/><xsd:element ref=“depositor” minOccurs=“0” maxOccurs=“unbounded”/>

</xsd:sequence></xsd:complexType></xsd:schema>


Querying and Transforming XML DataQuerying and Transforming XML Data

Translation of information from one XML schema to another Querying on XML data Above two are closely related, and handled by the same tools Standard XML querying/translation languages

XPath Simple language consisting of path expressions

XSLT Simple language designed for translation from XML to XML and

XML to HTML XQuery

An XML query language with a rich set of features

Wide variety of other languages have been proposed, and some served as basis for the Xquery standard XML-QL, Quilt, XQL, …


Tree Model of XML DataTree Model of XML Data

Query and transformation languages are based on a tree model of XML data

An XML document is modeled as a tree, with nodes corresponding to elements and attributes Element nodes have children nodes, which can be attributes or

subelements Text in an element is modeled as a text node child of the element Children of a node are ordered according to their order in the XML

document Element and attribute nodes (except for the root node) have a single

parent, which is an element node The root node has a single child, which is the root element of the

document

We use the terminology of nodes, children, parent, siblings, ancestor, descendant, etc., which should be interpreted in the above tree model of XML data.


XPathXPath

XPath is used to address (select) parts of documents using path expressions

A path expression is a sequence of steps separated by “/” Think of file names in a directory hierarchy

Result of path expression: set of values that along with their containing elements/attributes match the specified path

E.g. /bank-2/customer/name evaluated on the bank-2 data we saw earlier returns

<name>Joe</name>

<name>Mary</name>

E.g. /bank-2/customer/name/text( )

returns the same names, but without the enclosing tags


XSLTXSLT

A stylesheet stores formatting options for a document, usually separately from document E.g. HTML style sheet may specify font colors and sizes for

headings, etc.

The XML Stylesheet Language (XSL) was originally designed for generating HTML from XML

XSLT is a general-purpose transformation language Can translate XML to XML, and XML to HTML

XSLT transformations are expressed using rules called templates Templates combine selection using XPath with construction of

results


XQueryXQuery

XQuery is a general purpose query language for XML data

Currently being standardized by the World Wide Web Consortium (W3C) The textbook description is based on a March 2001 draft of the standard.

The final version may differ, but major features likely to stay unchanged.

Alpha version of XQuery engine available free from Microsoft

XQuery is derived from the Quilt query language, which itself borrows from SQL, XQL and XML-QL

XQuery uses a for … let … where .. result … syntax for SQL from where SQL where result SQL select let allows temporary variables, and has no equivalent in SQL


FLWR Syntax in XQuery FLWR Syntax in XQuery

For clause uses XPath expressions, and variable in for clause ranges over values in the set returned by XPath

Simple FLWR expression in XQuery

find all accounts with balance > 400, with each result enclosed in an <account-number> .. </account-number> tag

for $x in /bank-2/account

let $acctno := $x/@account-number where $x/balance > 400 return <account-number> $acctno </account-number>

Let clause not really needed in this query, and selection can be done In XPath. Query can be written as:

for $x in /bank-2/account[balance>400]return <account-number> $X/@account-number

</account-number>


Storage of XML DataStorage of XML Data

XML data can be stored in

Non-relational data stores Flat files

– Natural for storing XML

– But has all problems discussed in Chapter 1 (no concurrency, no recovery, …)

XML database

– Database built specifically for storing XML data, supporting DOM model and declarative querying

– Currently no commercial-grade systems

Relational databases Data must be translated into relational form

Advantage: mature database systems

Disadvantages: overhead of translating data and queries


Storing XML in Relational DatabasesStoring XML in Relational Databases

Store as string E.g. store each top level element as a string field of a tuple in a database

Use a single relation to store all elements, or Use a separate relation for each top-level element type

– E.g. account, customer, depositor

– Indexing:

» Store values of subelements/attributes to be indexed, such as customer-name and account-number as extra fields of the relation, and build indices

» Oracle 9 supports function indices which use the result of a function as the key value. Here, the function should return the value of the required subelement/attribute

Benefits: Can store any XML data even without DTD As long as there are many top-level elements in a document, strings are

small compared to full document, allowing faster access to individual elements.

Drawback: Need to parse strings to access values inside the elements; parsing is slow.


Storing XML as Relations (Cont.)Storing XML as Relations (Cont.)

Tree representation: model XML data as tree and store using relations nodes(id, type, label, value) child (child-id, parent-id) Each element/attribute is given a unique identifier

Type indicates element/attribute

Label specifies the tag name of the element/name of attribute

Value is the text value of the element/attribute

The relation child notes the parent-child relationships in the tree

Can add an extra attribute to child to record ordering of children

Benefit: Can store any XML data, even without DTD

Drawbacks:

Data is broken up into too many pieces, increasing space overheads

Even simple queries require a large number of joins, which can be slow


Storing XML in Relations (Cont.)Storing XML in Relations (Cont.)

Map to relations If DTD of document is known, can map data to relations Bottom-level elements and attributes are mapped to attributes of relations A relation is created for each element type

An id attribute to store a unique id for each element all element attributes become relation attributes All subelements that occur only once become attributes

– For text-valued subelements, store the text as attribute value

– For complex subelements, store the id of the subelement Subelements that can occur multiple times represented in a separate

table

– Similar to handling of multivalued attributes when converting ER diagrams to tables

Benefits: Efficient storage Can translate XML queries into SQL, execute efficiently, and then

translate SQL results back to XML Drawbacks: need to know DTD, translation overheads still present

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