Data Modeling Using XML

7/30/2019 Data Modeling Using XML

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Oct 13, 2003 Murali Mani, Antonio Badia

Data Modeling usingXML

Murali Mani, WPI

Antonio Badia, University of

Louisville

Oct 13, 2003


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Outline

z Part I: How to come up with good XML

designs for real world database applications?

z Part II: Translation between Relational and

XML models.


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Part I:

How to come up with good XML designs

for real world database applications?


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What is XML?

J. E. Hopcroft

J. D. Ullman

book

author author publisher

J. E. Hopcroft J. D. Ullman

name=

"Addison-

Wesley"


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XML for information exchange


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XML Publishing

Text

applications

X gave two

thumbs up rating

to the movieFugitive, The

Database

applications

14000062B

2000025A

SalaryAgeName

XML

A

25

20000

B62

140000

X

gave two thumbs

up to Fugitive, The


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Publishing Relational Databases

14000062B2000025A

SalaryAgeName

A

25

Users/Applications see a uniform XML view Exchange data with other applications

Querying XML is easier?

Problem:

What is a good XML schema for a relational schema?


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XML for Data Modeling

Location location

(@val, @time, GPS)

GPS gps (@satellite)

Location location(@val, @time, Bstation*)

Bstation bstation

(@id, @sigStrength)

Location location (@val, @time, (GPS | Bstation*))


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XML as a logical data model

z Use data modeling features provided by XML

z Union types

z Recursive types

z Ordered relationships

z

Easier to Query?Problems:

z What is a good XML schema for an application?

z How do we store the data in relational databases?

Location location (@val, @time, (GPS | Bstation*))


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XML for data integration

Browse

Query,Update

XML Wrapper

Source1

Source2

SourceN


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Database Design Stages

ApplicationRequirements

Conceptual

Design

Logical Design

Physical Design

Conceptual Schema

Logical Schema

Physical Schema


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Logical Data Model and

Redundancy

90034CAA2AN

90034CALos AnA1AV

zipstatecityaddressname

Good Design

Los An

Person

40MXM

agepname

MXMEEYC

MXMCSSD

advisorBSsname

Professor Student

40MXMEEYC

40MXMCSSD

ageadvisorBSsname

Bad Design

Student_Professor


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What is a Data Model?

z Structural Specification

z Constraint Specification

z Operations


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Entity Relationship (ER) Modelz Structures: Entity Types, Relationship Types

z Constraints: Cardinality constraints

AdvisorProfessor Student(0,*) (1,1)

pnam

e

age

year

snam

e


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Relational Modelz Structures: Relations

z Constraints: Key, Foreign Key

agepname

Professor

advisorsname

Student

Key Constraints:

Key (Professor) = Key (Student) =

Foreign Key Constraints:

Student (advisor) referencesProfessor (pname)

S if i St t f XML


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Specifying Structures for XML

G = (N, T, P, S)N = {Book, Author, Publisher, #PCDATA}

T = {book, author, publisher, pcdata}

S = {Book}

Book book (Author +, Publisher)

Author author (#PCDATA)

Publisher publisher (@name::String)

#PCDATA pcdata ()

book



name=

"Addison-

Wesley"

Regular Tree Grammar

Every production rule is of the

form A a X

A N, a T, X is a regular

expression over N


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XML Schema Language

Proposals

z W3C DTD: local tree grammar

z W3C XML Schema: single type tree grammar

z ISO/OASIS RELAX NG: full-fledged regulartree grammar

Properties of different Regular


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Properties of different Regular

Tree Grammar classesz Expressiveness

z Regular tree grammarstrictly more expressive than single typetree grammar

z Single type tree grammarstrictly more expressive than localtree grammar

z Closure propertiesz Regular tree grammar closed under union, intersection and

difference

z Single type tree grammar/local tree grammar closed only underintersection

z

Type assignmentz Type assignment can be ambiguous for regular tree grammar.

z Type assignment is unambiguous for local tree grammar/singletype tree grammar.


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Ambiguous Type Assignment

G = (N, T, P, S)N = {Book, Author1, Author2, Publisher, #PCDATA}

T = {book, author, publisher, pcdata}

S = {Book}Book book (Author1*, Author2*, Publisher)

Author1 author (#PCDATA)

Author2 author (#PCDATA)

Publisher publisher (@name::String)

#PCDATA pcdata ()book



name=

"Addison-

Wesley"

C t i t S ifi ti f


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Constraint Specification for

XML why?

ReviewPerson Book(0,*) (0,*)

name

zip

ISBN

title

year

rating

What constraint specification?

Key, Foreign Key

ID/IDREF

If we represent all relationships only by hierarchies,

then the logical model will have redundancy.

S if i C t i t f


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Specifying Constraints for

XML: Examplelibrary

person

book

review review

book paper

reviewreview

personname=

"CZ"name=

"RRM"

ISBN=

"I1"

title=

"T1"

BID=

"B1"ISBN=

"I2"

title=

"T2"

BID=

"B2"

title=

"T1"

journal

="J1"

PID=

"P1"

article

="P1"

article

="B2"article

="B1"

article

="B2"

rating

="9"

rating

="9"rating

="9"

rating

="10"

S if i C t i t f


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Specifying Constraints for

XMLz Keys are specified using (rel, sel, field)

z

rel is relative axisz sel is selector axis

z field is a set of path expressions

z For any element that belongs to rel, sel will give aset of elements. For this set of elements, field is the

key.

z rel and sel can be types or path expressionsz Foreign keys are specified as (rel1, sel1, field1)

references (rel2, sel2, field2)

C t i t S ifi ti


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Constraint Specification

Proposalsz W3C XML Schema

z Relative axis = typez Selector axis = path expression

z Keys for XML WWW10

z Relative axis = path expression

z Selector axis = path expression

z

UCM WWW10z No relative axis

z Selector axis = type


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Our proposalz Relative axis = type

z Selector axis = type

z IDREF and IDREFS identify target types

Example


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Examplelibrary

person

book

review review

book paper

reviewreview

personname=

"CZ"name=

"RRM"

ISBN=

"I1"

title=

"T1"

BID=

"B1"ISBN=

"I2"

title=

"T2"

BID=

"B2"

title=

"T1"

journal

="J1"

PID=

"P1"

article

="P1"

article

="B2"article

="B1"

article

="B2"

rating

="9"

rating

="9"rating

="9"

rating

="10"

(Library, Person, )(Library, Book, )

(Library, Paper, )

(Person, Review, )

@article::IDREF references(Book | Paper)


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Why use XML as logical data model?

Path Expressions vs Joins


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at p ess o s s Jo s

40MXM

55CZ

agepname

Professor

Student

advisoryearsname

MXM1998SD

CZ1999FC

MXM2000YC

Student (advisor) references

Professor (pname)

Query: Give names of students of professors of age 40

name ((age=40 (Professor)) Student) professor [@age=40]/student/@sname

year=

"1998"sname

="SD"

student

year=

"1999"sname

="FC"

year=

"2000"

sname

="YC"

age="55"pname="CZprofessor

age="40"pname="MXM"

student student

professor

university

Union Types - attributes


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Union Types - attributes

90034nullnullAN

nullCALos AAV

zipstatecityname

Person

person

city=

"Los A"

name

="AV"

person

university

state

=CA

name

="AN"zip=

90034

Person person (@name, ((@city, @state) | @zip))

Union Types - Relationships


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Person

01609RRM

90095CZ

zipnameRRMT1I1

RRMT2I2

authortitleISBN

Book

CZJ1T1authorjournaltitle

Paper

Person person (@name,

@zip, (Book* | Paper*)) library

person

book book paper

personzip="90095"

name=

"RRM"

ISBN=

"I1"

title=

"T1"ISBN=

"I2"

title=

"T2"

title=

"T1"

journal

="J1"

name=

"CZ"

zip="01609"

Union Types Relationships


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ChicagoER

venuename

Conference

ACMTOIT

publishernameJournal

nullERWPIT1

UCLA

inst

null

conf

TOITT2

journaltitle

Paper

Conference conference (@name, @venue, Paper*)

Journal journal (@name, @publisher, Paper*)

library

journal

paper

conferencepublisher="ACM"

name=

"ER"

title=

"T2"

inst=

"UCLA"

name=

"TOIT"

venue="Chicago"

paper

title=

"T1"

inst=

"WPI"

Recursive Types


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Recursive Types

null

bike

bike

wheel

frame

superPart

0bike

2wheel

1

1

1

qty

tire

frame

seat

name

Assembly

WITH RECURSIVE SubPart (name) AS

(SELECT name FROM Assembly

WHERE superPart=bike)

UNION(SELECT R2.name

FROM SubPart R1, Assembly R2

WHERE R2.superPart = R1.name)

SELECT * FROM SubPart

Query: What are subparts of bike?

part[@name=bike]//part/@name

partqty=0

name=bike

name=framepart

qty=1

name=seatpart

qty=1

partname=wheel

qty=2

partname=tireqty=1

assembly

IDREF vs Foreign Keys


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g y

@PRef::IDREF references (Professor)

40MXM

55CZ

agename

Professor

Studentadvisoryearname

MXM1998SD

CZ1999FCMXM2000YC


Professor (name)

student[@PRef

professor/@age=40]/@name

Query: Give names of students of professors of age 40

age="40"

name="MXM"

professor

PID="P1"

age="55"

name="CZ" PID="P2"

student student

year=

"1998"

name=

"SD"PRef

="P1"

student

year=

"2000"

name=

"YC"PRef

="P1"

year=

"1999"

name=

"FC"PRef

="P2"

professor

university

IDREF as union of foreign keys


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T2I2

T1I1

titleISBN

Book

J1T1

journaltitle

Paper 90095CZ

01609RRM

zipname

Person

null

null

T1

paper

10I2CZ

9I1CZ

9nullRRM

ratingbookname

Review



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@article::IDREF references (Book | Paper)

library

person

book

review

book paper

reviewreview

personzip=

"90095"name=

"RRM"

ISBN=

"I1"

title=

"T1"

BID=

"B1"ISBN=

"I2"

title=

"T2"

BID=

"B2"

title=

"T1"

journal

="J1"

PID=

"P1"

article

="P1" article="B1" article="B2"

rating

="9"rating

="9"

rating

="10"

zip="01609"

name=

"CZ"


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Conceptual Model:

ERex (ER extended for XML)


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Entity Relationship (ER) model

AdvisorProfessor Student

(0,*) (1,1)

pna

me

a

ge

year sn

ame

Entity Types, Relationship Types and their attributes


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Object Role Modeling (ORM)

Professor

(pname)

age has

Student

(sname)

is advisor

offor

Years

(year)

closer to natural language sentences

attributes/relationships are expressed uniformlyusing roles

Unified Modeling Language


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Unified Modeling Language

(UML)

pnameage

Professor

sname

Student

years

Advisor

11 0*

Modeling software systems

Class Diagrams, Association Classes

From ER model


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pname

age

year

sname

Binary 1:n relationships


n

ame

zip

ISBN

title

year

rating

Binary m:n relationships

From ER Model


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SuppliesCompany City(1,*) (0,*)

name

Product

name

name

(0,*)

quantity

N-ary relationships

Contains

Part(0,1)

qty

(0,*)

superpart

subpart

nam

e

Recursive relationships

Ordered Relationships


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AuthorPerson Book(0,*) (1,1)

name

zip

ISBN

title

90095

95123

zip

RRM

Ullman

namePerson

1

1

2

order

UllmanAutB2

B3

B1

ISBN

RRM

Ullman

author

MMSL

DB

title

Book

C S C


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Categories and Set Constraints

Person

PersonCity PersonZip

name

zip

city

state

PersonCity PersonZip =

PersonCity PersonZip = Person

Categories


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g

Review

Person

Article

name

Book Paper

(0,*)

(0,*)

S t t i t R l


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Set constraints on Roles

AuthorOf

Personname

Book

PaperAuthorOf

(0,*)

(0,*)

personBook

personPaper

(1,1)

(1,1)

personBook personPaper =

Set Constraints on Roles


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Set Constraints on Roles

confPaper journalPaper =

confPaper journalPaper = Paper

Presented

Paper

Conference

Journal Published

(0,1)

(0,1)

confPaper

journalPaper

(0,*)

(0,*)

name

venue

publisher

name

title


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Translating ERex schemas to

XML schemas


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System Architecture

TranslatorXML

Schemas

FinalXML

Schema

SchemaDesigner

ERex

Schemas


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1:n relationships


pname

age

year

sname

Representing 1:n Relationships - subelementProfessor


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University university (Professor*)

Professor professor (@name, @age, Student*)

Student student (@name, @year)

(University, Professor, )

(University, Student, )

62RRM

55CZ

agename

Student

advisoryearname

RRM1998MM

CZ1999FC

RRM2000YC


Professor (name)

year=

"1998"name=

"MM"

student

year=

"1999"name=

"FC"

year=

"2000"

name=

"YC"

age="55"name="CZ"professor

age="62"name="RRM"

student student

professor

university

Representing 1:n Relationships - IDREF

universityProfessor


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age=

"62"

name=

"RRM"

professor

PID=

"P1"

age=

"55"

name=

"CZ"PID=

"P2"

student student

year=

"1998"

name=

"MM"PRef

="P1"

student

year=

"2000"

name=

"YC"PRef

="P1"

year=

"1999"

name=

"FC"PRef

="P2"

professor

university

University university (Professor*, Student*)

Professor professor (@name, @age, @PID)

Student student (@name, @year, @PRef)



@PRef::IDREF references (Professor)

62RRM

55CZ

agename

Professor


RRM1998MM

CZ1999FCRRM2000YC


Professor (name)

Representing 1:n Relationships foreign keys

Professor university


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Professor professor (@name, @age)

Student student (@name, @year, @advisor)


(University, Student, )(University, Student, ) references


62RRM

55CZ

agename

Professor


RRM1998MM

CZ1999FCRRM2000YC


Professor (name)

age=

"62"

name=

"RRM"

professor

age=

"55"

name=

"CZ"

student student

year=

"1998"

name=

"MM"

student

year=

"2000"

name=

"YC"year=

"1999"

name=

"FC"

professor

y

advisor

="RRM"

advisor

="RRM"

advisor

="CZ"


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m:n relationships


name

ISBN

title

rating

Representing m:n relationshipsPerson Book

lib


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Review (pname) references

Person (name)

Review (ISBN) references

Book (ISBN)

CZ

RRM

name

T2I2

I3

I1

ISBN

T3

T1

title

Review

9I2RRM

9I1CZ

I1

I3

ISBN

CZ

RRM

pname

10

9

rating

library

person

book

review review

book book

reviewreview

personname=

"CZ"name=

"RRM"

ISBN="I1"

title="T1"

BID="B1"

ISBN="I2"

title="T2"

BID="B2"

ISBN="I3"

title="T3"

BID="B3"

article

="B3"

article

="B2"

article

="B1"

article

="B2"

rating

="9"

rating

="9"

rating

="9"

rating

="10"

Library library (Person*, Book*)

Person person (@name, Review*)

Book book (@ISBN, @title, @BID)

Review review (@article, @rating)

(Library, Person, ) (Library, Book, )

(Person, Review, )

@article::IDREF references (Book)


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N-ary relationshipsquantity


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SuppliesCompany City(1,*) (0,*)

name

Product

n

ame

name

(0,*)

Root root (Company*, Product*, City*)

Company company (@name, Supply+)

Supply supply (@ProdRef, @CityRef, @qty)

Product product (@name, @ProdID)City city (@name, @CityID)

(Root, Company, )

(Root, Product, )

(Root, City, )

@ProdRef::IDREF references

(Product)@CityRef::IDREF references

(City)

Recursive Relationships


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null

bikebike

wheel

frame

superPart

0bike

2wheel1

1

1

qty

tire

frame

seat

name

Assembly

Contains

Part(0,1)

qty

(0,*)

superpart

subpart

name

partqty=0

name=bike

name=frame partqty=1

name=seat partqty=1

part name=wheelqty=2

partname=tireqty=1

assembly

Assembly assembly (Part*)

Part part (@name, @qty, Part*)

(assembly, part, )

Ordered RelationshipsPerson


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90095

95123

zip

RRM

Ullman

name

Person

1

1

2

order

UllmanAutB2

B3

B1

ISBN

RRM

Ullman

author

MMS

DB

title

Book

title=

"Aut"ISBN=

"B1"

book

title="MMS"

ISBN=

"B3"

title=

"DB"

ISBN=

"B2"

zip="90095"name="RRM"

personzip="95123"

name="Ullman"

book book

person

library

Library library (Person*)

Person person (@name, @zip, Book*)

Book book (@ISBN, @title)

(Library, Person, )(Library, Book, )

Categories and set constraints


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Categories and set constraints

Person


name

zip

city

state



Person person (@name, ((@city, @state) | @zip))


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AuthorOf

Personname

Book

PaperAuthorOf

(0,*)

(0,*)

personBook

personPaper

(1,1)

(1,1)

Person person (@name, (Book* | Paper*))



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Converting ERex XML


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Converting ERex XML

z Goals

z Maximize relationships represented usingsubelement.

z Others try to represent using IDREF

Algorithm: ERex XML


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g

z A non-terminal symbol for each

z entity type with key

z m:n relationship

z n-ary relationship

z Root non-terminal symbol

z

Represent attributesz Represent relationships and identify top nodes

z 1:1 and 1:n relationships

z m:n relationshipsz n-ary relationships

z Identify key and IDREF constraints.

Review


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Person

Article

name

Book Paper

(0,*)

(0,*)

AuthorOf

Author

Of


(1,1)

(1,1)

(0,*)

(0,*)

ISBN btitle year ptitle year journal

city state zip

rating

personBook

personPaper


personBook personPaper = Person



Review

(0,*)


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Person

Article

name

Book Paper

(0,*)

Author

Of

Author

Of


(1,1)

(1,1)

(0,*)

(0,*)

ISBN btitle year ptitle year journal

city state zip

rating

personBook

personPaper

N = {Root, Person, Book, Paper, Review}

Book book (@ISBN, @btitle, @year)Paper paper (@ptitle, @year, @journal)Person person (@name,

((@city, @state) | @zip))

Person person (Book* | Paper*)Person person (Review*)Review review (@rating, @article)

(Root, Person, )(Root, Book, )

(Root, Paper, )

(Person, Review, )


Root root (Person*)

Conclusions


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Conclusions

TranslatorXML

Schemas

Final

XML

Schema

Schema

Designer

ERex

Schemas

Obtained good XML Schema from ERex schemas


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Part II:

Translation between Relational and XML

models.

Why publish relational

databases as XML?


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databases as XML?

z Provide an XML view for our legacy data

z Users/Applications can query our data over theweb using standards.

z Easier to query XML than legacy (relational) data?

z Convert our legacy data to XML

z We can exchange data with applications.

z Store data in XML databases?

z Easier to query?

Application Scenarios


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Application Scenarios

z Schema Matching Problem

z

Given a relational schema and an XML schemaby a standards body, how do we map this

relational schema to XML?

z Tools such as XML Extender from IBM, Clio(University of Toronto and IBM), MS SQL Server

z Schema Mapping Problem

z Given a relational schema, how do we come up

with a goodXML schema?

Schema Matching: MS SQL

Server Architecture


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Server Architecture

COPYRIGHT NOTICE. Copyright 2003 Microsoft Corporation, One MicrosoftWay, Redmond, Washington 98052-6399 U.S.A. All rights reserved.

Schema Mapping Problem


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14000062B

2000025A

SalaryAgeName

A

25

Users/Applications see a uniform XML view

Exchange data with other applications Store XML in native XML databases

Querying XML is easier?

Problem:

What is a good XML schema for a relational schema?

Goals


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z XML Schema should maintain constraints.

z Resulting XML should not introduce

redundancies.

z Most relationships can be navigated using

path expressions, rather than joins.z Minimal user interaction: Our translator

should suggest good XML schemas to thedatabase designer.

System Architecture


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System Architecture

CoTXML

SchemasRDB

Final

XML

Schema

Schema

Designer

NeT

Related Work


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e ated o

z XML-DBMS

z

Template driven mapping languagez SilkRoute

z Declarative Query Language (RXL) for viewing

relational data as XML

z Xperanto

z User specifies query in XML Query Language

Algorithms


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g

z Nave

z

FT (Flat Translation)z Consider relational data

z NeT (Nesting-based Translation)

z Consider relational schema

z CoT (Constraint-based Translation)

FT: Flat Translation


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z 1 : 1 mapping from relational to XML

z Ideaz A type (non-terminal) corresponding to every

relation

z Attributes of a relation form attributes of the type

z Keys and foreign keys are preserved

FT: Flat Translation - Example

agename

Professor

professorprofessor

university


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Professor professor (@name, @age)Student student (@name, @year, @advisor)


(University, Student, )(University, Student, ) references


62RRM

55CZ

agename

Student

advisoryearname

RRM1998MM

CZ1999FC

RRM2000YC


Professor (name)

age=

"62"

name=

"RRM"

professor

age=

"55"

name=

"CZ"

student student

year=

"1998"

name=

"MM"

student

year=

"2000"

name=

"YC"year=

"1999"

name=

"FC"

p

advisor

="RRM"

advisor

="RRM"

advisor

="CZ"

NeT: Nesting-based Translation


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g

z Idea:

Make use of non-flat features provided byXML: represent repeating groups using *, +

NeT: Example


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CLRGafniAlgorithmsUdi ManberMajidAlgorithms

CLRMajidAlgorithms

Udi ManberGafniAlgorithms

textprofcname

Course (cname, prof, text)

NeT: Example

Course (cname, prof+, text)


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Course (cname, prof+, text +)

{Udi Manber, CLR}{Gafni, Majid}Algorithms

textprofCname

Cou se (c a e, p o , te t)

Udi Manber{Gafni, Majid}Algorithms

CLR{Gafni, Majid}Algorithms

textprofcname

NeT: Exampleuniversity


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course coursecourse course

c

name="Algorithms"

prof="Gafni"

text="UdiManber"

prof="Majid"

text="CLR"

c

name="Algorithms"

prof="Gafni"

c

name="Algorithms"

prof="Majid"

text="CLR"

c

name="Algorithms"

text="UdiManber"

prof

university

course

prof text

Gafni CLRUdi Manber

cname="Algorithms"

text

Majid

ValueRatio=12/5

University university (Course*)

Course course (@cname, Prof+, Text+)

Prof prof (#PCDATA)

Text text (#PCDATA)

#PCDATA pcdata ()

(University, Course, )

University university (Course*)

Course course (@cname,

@prof, @text)


NeT: Example


82/110


90034CALos AngelesAN

90034CALos AngelesMM

zipstatecityname

Person (name, city, state, zip)

90034CALos Angeles{MM, AN}

Person (name+, city, state, zip)


83/110

NeT: Summary

z Consider Table twith column set C. Nesting on


84/110


columnXis defined as:

Any two tuples with the same values for

(C X) will be combined to one tuple

z Observation: We need to nest only on key

columns

z Advantages of NeT

z NeT removes redundancy if relation is not in 4NFz NeT provides more intuitive XML schemas with less

redundancy


85/110

CoT: Constraint-based

Translation


86/110


z Translating relational schema

z

Idea:Use foreign key constraints and our

knowledge of how to represent relationships

to come up with better XML models.

CoT: Step 1

Professor

university


87/110


University university (Professor*)

Professor professor(@pname, @age,Student*)

Student student (@sname, @cname)


(Professor, Student, )

62RRM

agepname

DBsRRMYC

QSsRRMYC

DBsRRMMM

cnameadvisorsname

Student


professorpname="RRM"

age="62"

studentstudent student

sname=

"MM"

sname=

"YC"

sname=

"YC"cname=

"DBs"

cname=

"DBs"

cname=

"QSs"

ValueRatio=11/8

CoT: Step 2

i

ProfessorCourse

University university (Professor*,Course*)

Professor professor (@pname,@age, Student*)

St d t t d t (@ @CR f)


88/110


1962QSs

1979DBs

sincecname

62RRM

agepname

DBsRRMYC

QSsRRMYC

DBsRRMMM

cnameadvisorsname

Student


Student (cname) references

Course (cname)

university

professorpname="RRM"

age="62"

studentstudent student

sname=

"MM"

sname=

"YC"

sname=

"YC"CRef=

"c1"

CRef=

"c1"

CRef=

"c2"

coursecourse

cname=

"DBs"

cname=

"QSs"

since=

"1979"

since=

"1962"CID=

"c1"

CID=

"c2"

Student student (@sname, @CRef)Course course (@cname, @since, @CID)


(University, Course, )(Professor, Student, )

CRef::IDREF references (Course)

ValueRatio=15/14

CoT: Example

Student (SID, name, advisor)

E (EID jN )


89/110


Emp (EID, name, projName)Prof (EID, name, teach)

Course (CID, title, room)

Dept (dno, mgr)

Proj (pname, pmgr)Student (advisor) references

Prof (EID)

Emp (projName) references

Proj (pname)Prof (teach) references

Course (CID)

Prof (EID, name) references

Emp (EID, name)

Dept (mgr) references

Emp (EID)

Proj (pmgr) references

Emp (EID)

studentstudent

prof

course dept

proj

emp

student

student

f

proj

emp


90/110


prof

course dept

emp

coursecourse

emp

Top nodes


(University, Emp, )

(University, Prof, )


(University, Proj, @pname)

(University, Dept, @dno)

@EmpRef::IDREF references(Emp)

@ProjRef::IDREF references

(Proj)University university (Course*, Emp*)

Course course (@CID, @title, @room, Prof*)

Prof prof (@EmpRef, Student*)Student student (@SID, @name)

Emp emp (@EID, @name, @ProjRef, @EmpID, Dept*, Proj*)

Proj proj (@pname, @ProjID)

Dept dept (@dno)

CoT Experimentation


91/110


z Ran on TPC-H data

z

Value ratio > 100/88 (size decreased by morethan 12%)

Conclusions

CoTXML

S hRDB

Final

XMLNeT


92/110


z We obtained good XML schemas from relationalschemas

z Constraints are maintained

z Redundancies are decreased

z Most relationships can be navigated using path

expressions.z Minimum user interaction

CoT SchemasRDB XMLSchema

Schema

Designer

NeT


93/110


Storing XML data in relational databases

Options for storing XML data


94/110


z Store in relational databasesz Relational databases are robust and efficient (IBM

XML Extender, Oracle, MS SQL Server)

z Store in native XML databasesz

More efficient for XML than relational databases(Natix, eXist, Tamino)

z Store in a combination of both

z Structured portion of XML data in relationaldatabase, and unstructured portion in native XMLstore.

Related Work

z STOREDz No Schema


95/110


z No Schema

z Use data mining techniques to find structured andfrequent patterns

z These are stored in relational DB, others in semi-structured overflow store

z Drawback: Requires integration of relational DBand semi-structured store

z Storing pathsz

One relation for storing nodes, one for storingedges.

z Drawback: Type information is lost.

Type-based relational storage


96/110


z Jayavel Shanmughasundaram

z Several key ideas such as schema simplification,

inlining, handling recursion

z LegoDB

z Use the query workload to come up with anefficient relational schema.

Main features


97/110


z The entire XML document is shredded and

stored in a relational database.

z All semantic constraints in XML schema are

not captured in relational schema.

z We do not discuss how operations on XMLare translated to SQL.

Why not capture all

constraints?


98/110


A a (@b, ((@c, D)* | (@e, F)*))

(Root, A, )

A (@b, @c, @e)

D (@aRef)F (@aRef)

Semantic constraints lost

if D refers to an A, then the corresponding @c should be non-null

if F refers to an A, then the corresponding @e should be non-null


99/110

Schema Simplification


100/110


A a (@d, (B, C, B)*)

A a (@d [1, 1], (B [2, 2], C [1, 1]) [0, *])A a (@d [1, 1], B [2, 2] [0, *], C [1, 1] [0, *])

A a (@d [1, 1], B [0, *], C [0, *])

A a (@d, B*, C*)

Semantic information lost

The number of Bs is two times the number of Cs for every C, there is a B that occurs before it, and one that occurs

after it.

Inlining


101/110


Conf conf (@ctitle, @date, Venue)

Venue venue (@city, @country)

Conf conf (@ctitle, @date, @city, @country)

Why inlining?

Lesser joins, hence more efficient

Mapping Collection Types


102/110


Conf conf (@ctitle, @date, Paper*)

Paper

paper (@ptitle, @author)

Conf (@ctitle, @date)

Paper (@ptitle, @author, @confRef)

Separate relation with foreign key for every collection type

IDREF attribute

P (@ @ i R i *)


103/110


Person person (@name, @zip, Review*)

Book book (@ISBN, @btitle, @BID)

Paper

paper (@ptitle, @journal, @PID)Review review (@article, @rating)


Person (@name, @zip)

Book (@ISBN, @btitle, @BID)

Paper (@ptitle, @journal, @PID)Review (@personRef, @bookRef, @paperRef, @rating)

Recursion using ?


104/110


A a (@d, A?)

A (@d, ARef)ARef refers to the child of A, and can be null

A a (@d, ARef)ARef refers to the parent of A and can be null.

Recursion using *


105/110


A a (@d, A*)

A (@d, ARef)ARef refers to the parent of A, and can be null

Recursion General technique


106/110


z For every cycle, we must have a separate

relation

z Algorithm

z For every strongly connected component, define

a separate relation for one of the types.z In a strongly connected component, if there is a

type which can be children of multiple types, then

define a separate relation for that type.

Capturing Order in theDocument


107/110


z Through order attributes

z

Corresponding to each type in XML schema,say A, we have an associated order attribute,

say aOrder

Conf conf (@ctitle, @date, Venue)

Venue venue (@city, @country)

Conf conf (@ctitle, @date, @confOrder, @city,

@country, @venueOrder)

Conclusions

z XML schema with no recursion can be translated tol ti l h ith ll


108/110


relational schema with no nulls.

z XML schema with recursion cannot be translated to

relational schema with no nulls.z If recursion, separate relation needed for every

cycle.

z All semantic constraints in XML cannot be capturedin relational schema.

z XML resulting from CoT can be translated to the

original relational schema; all semantic constraintsare maintained.

Open Problems

S d d ifi i Wh l d


109/110


z Standards specification: What structural and

constraint specification schemes for XML are

needed for database applications?

z XML used for text/document publishing:

Keyword Search in XML documentsz Storing data consisting of structured and

unstructured portions: integrating relationaland XML stores.

Open Problem (contd)

T l ti ti i XML d l t


110/110


z Translating operations in XML model to

underlying sources (relational)

z Use annotated schema (MS SQL Server)

z Use implicit annotations (LegoDB)

z Query minimization: When we do automatictranslation, we might perform unnecessary joins?

Date post:	14-Apr-2018
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Data Modeling Using XML

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