and Di s t r i b u t e d Databases on the Web Nathaniel Ayewah CSE 8330 Presentation SMU

Introduction  Why XML?  In Databases? Structured Content Data Model

Overview  XML Technologies  XML and Databases  Will XML supplant Relational DBs? Querying XML Different Approaches

XML Origins  SGML  HTML  XML

XML Example (a)HTML Southern Methodist Universiy PO Box 0133, Dallas, TX SMU is a private university of more than 11,000 students near the vibrant heart of Dallas. (b)XML Southern Methodist University PO Box 0133 Dallas TX SMU is a private university of more than 11,000 students near the vibrant heart of Dallas. meta language

On Data and Documents Data-centric. Regular Structure Computer Science 23 Excellent Electrical Engineering 4353 O.K.. Document-centric Irregular Structure Rock the SEAS Vote! Vote for your favorite faculty member. Once a year, you get to choose your favorite faculty member. That time has come again. March 25 to April 1 Stop by the CSE office because you care vs

XML Technologies XSLT XQuery XML-QL XPath XQL XSL-FO XPointer XML Schema DTD SAX DOM XML Encryption XML Signature SOAP UDDI WSDL

XML Technologies  Validation and Structure  Query Languages**  Parsing and Processing  Transformation and Presentation

Validation and Structure DTD

Query Languages  Document Community  Database Community  W3C [XPath/XQL] [XML-QL] [XQuery]

“What is the size of the Computer Science Faculty?” XQL Document(“departments.xml”)//department = “CSE”]/facultysize Output: 23

“What is the size of the Computer Science Faculty?” XML-QL WHERE $n $f $r IN “departments.xml”, $c = “CSE” CONSTRUCT $f Output: 23

“What is the size of the Computer Science Faculty?” XQuery for $b in doc(“departments.xml”)//department let $d := $b/facultysize where = “CSE” return {$d} Output: 23

{ for $i in fn:doc("catalog.xml")//item, $p in fn:doc("parts.xml")//part[partno = $i/partno], $s in fn:doc("suppliers.xml")//supplier[suppno = $i/suppno] order by $p/description, $s/suppname return { $p/description, $s/suppname, $i/price } } XQuery: Joins Source:

XML and Databases

Why distribute?  Data Integration  Data Distribution

Classification Data viewVirtual viewQuery view (d)(d)(v)(v)(q)(q) Classification: T d,v,q d, v, q  {R, X, H, N} R = Relational Data Model X = XML Data Model H = Hybrid Data Model N = View does not exist

Products  Native XML  XML Enabled  Middleware or XML Server  Wrappers  Standalone XML XQuery Engine  Content Management System T X,X,X T R,X,X T R,R,X ? T R,R,R T R,X,X T R,X,N T X,R,R T X,N,X T X,X,X

XML-Enabled Relation: DepartmentsXML IDNameSize CSE Computer Science 234 EE Electrical Engineering 334 CSEComputer Science234 EEElectrical Engineering334 Default View

Native XML Database Native Relational XML Document Collection Physical Storage Tuple(s) Relation XML::DB Initiative

Berkeley DB XML  XML Data Model over Physical Berkeley DB storage system  Native XML Storage  Supports transactions, recovery, indexing, replication, multiple users and concurrency, query processing, standards  C++/Java APIs

Berkeley DB XML Source: Berkeley DB XML Documentation

Current/Future Research Issues  Physical Storage  Query Optimization  Distributed Processing/Optimization  Static vs Dynamic Processing  First, Last, Partial Results  Updates

Conclusion and Future  Will XML replace existing DBs? Document-centric applications XML Sources Data warehousing (Xyleme) Data-centric applications Business Transactions