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XML Salman Azhar

XML Salman Azhar. Semi-structured Data XML (Extensible Markup Language) Well-formed and Valid XML Document Type Definitions IDs and IDREFs.

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XML Salman Azhar

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  1. XMLSalman Azhar Semi-structured Data XML (Extensible Markup Language) Well-formed and Valid XML Document Type Definitions IDs and IDREFs These slides use some figures, definitions, and explanations from Elmasri-Navathe’s Fundamentals of Database Systemsand Molina-Ullman-Widom’s Database Systems Salman Azhar: Database Systems

  2. Framework • Information Integration : • Making databases from various places work as one. • Semi-structured Data : • A new data model designed to cope with problems of information integration. • XML : • A standard language for describing semi-structured data schemas and representing data. Salman Azhar: Database Systems

  3. 1. Information Integration • Generally databases in an enterprises have: • Several underlying database management systems • Oracle, MS SQL Server, DB2, • Informix, Sybase (SQL Server), MS Access, etc. • Several underlying database schemas • Information in an employee table can contain • Employee Name, SSN, DOB, title, hrsPerWeek.modifiedTime, modifiedBy • Employee Name, SSN, DOB, title, degree, createTime, createBy • Employee Name, SSN, DOB, title, salary,modifiedTime, modifiedBy, createTime, createBy Salman Azhar: Database Systems

  4. 2. Semi-structured Data • A new data model designed to cope with problems of information integration • Accommodates of different DBMS • Oracle, MS SQL Server, DB2, • Informix, Sybase (SQL Server), MS Access, etc. • Integrates different schemas • Employee Name, SSN, DOB, title, hrsPerWeek,modifiedTime, modifiedBy • Employee Name, SSN, DOB, title,degree, createTime, createBy • Employee Name, SSN, DOB, title,salary,createTime, createBy, modifiedTime, modifiedBy Salman Azhar: Database Systems

  5. 3. XML • A standard language for describing semi-structured data schemas and representing data. Salman Azhar: Database Systems

  6. The Information-Integration Problem • Major bottleneck in enterprise application integration • For example… • Hewlett Packard split into HP and Agilent • Need to separate data into different destinations • HP bought Compaq • Need to integrate data from different sources Salman Azhar: Database Systems

  7. The Information-Integration Problem • Related data exists in many places and could, in principle, work together. • But different databases differ in: • Model • relational, object-oriented? • Schema • normalized/denormalized? • Terminology • are consultants employees? Retirees? Subcontractors? • Conventions • meters versus feet? Salman Azhar: Database Systems

  8. Example • Consider merger of two stores in a Mall • may be some overlap in the products sold • but the databases are different Salman Azhar: Database Systems

  9. Example • Each company has a database • One may use a relational DBMS • the other keeps the data in an MS-Word document • One stores the phones of distributors, • the other does not • One distinguishes products in one department • the other doesn’t • One counts inventory by number of items, • the other by cases Salman Azhar: Database Systems

  10. Two Approaches to Integration • Warehousing • Makes a copy of the data • More developed of the two • Mediation • Creates a view of the data • Newer and less developed Salman Azhar: Database Systems

  11. Result User query Warehouse Diagram Warehouse Wrapper Wrapper Source 1 Source 2 Salman Azhar: Database Systems

  12. Result User query Query Result Result Query Query Result Query Result A Mediator Mediator Wrapper Wrapper Source 1 Source 2 Salman Azhar: Database Systems

  13. Warehousing • Make copies of the data sources at a central site and transform it to a common schema • Reconstruct data daily/weekly • Do not try to keep it more up-to-date than that. • Pro: • very well-developed • several commercial tools are available • Con: • data can be old since updates are expensive • 24-hour availability threatened by large data updates Salman Azhar: Database Systems

  14. Mediation • Create a view of all sources, as if they were integrated • Answers a view query by translating it to terminology of the sources and querying them • Pro: • Current data • Con: • Can be slow as it requires real time merger of different data sources • Lack of tools available Salman Azhar: Database Systems

  15. Result User query Warehouse Diagram Warehouse Wrapper Wrapper Source 1 Source 2 Salman Azhar: Database Systems

  16. Result User query Query Result Result Query Query Result Query Result A Mediator Mediator Wrapper Wrapper Source 1 Source 2 Salman Azhar: Database Systems

  17. Semi-structured: Motivation • Most effective approach to Information Integration: • Semi-structured Data Model • or Semi-structured Objects Salman Azhar: Database Systems

  18. Semi-structured: Motivation • Main limitation of Object-Oriented Models: • Object Models are Strongly Typed • Objects of a class have one structure only • Semi-structured approach solves this problem Salman Azhar: Database Systems

  19. Semi-structured Data • Purpose: • Represent data from independent sources more flexibly than • either relational • or object-oriented models Salman Azhar: Database Systems

  20. Semi-structured Data • Each object has a class of their own and properties are defined whatever labels are attached to that object • Properties mean • attributes, • relationships, • methods, etc. Salman Azhar: Database Systems

  21. Semi-structured Data • Think of objects • but with the type of each object is the objects its own business • not that of its “class” • Labels to indicate meaning of substructures Salman Azhar: Database Systems

  22. Semi-structured Graphs • Easy to think of Semi-structured data as Graphs • Nodes = objects • Labels on arcs = • attributes leading to a leaf node • relationships leading to another node Salman Azhar: Database Systems

  23. Semi-structured Graphs • Atomic values at leaf nodes • nodes with no arcs out • Flexibility: no restriction on… • labels out of a node • number of successors with a given label Salman Azhar: Database Systems

  24. The soda object for Pepsi (arc-in called soda; arc-out called name to Pepsi) Example: Data Graph Root object represents the entire DB. Often look like trees, but are not. root Notice a new kind of data. soda soda rest The restaurant object for KFC (arc-in called rest; arc-out labeled name to KFC) manf manf prize name PepsiCo name year award sellsAt Pepsi Sobe 2003 BestSeller name addr KFC Main St Salman Azhar: Database Systems

  25. Stage is Now Set for XML • A technology has application to different situations • foundations remain the same • applications changes Salman Azhar: Database Systems

  26. Extensible Markup Language (XML) • XML • uses tags for semantics (e.g., “this is an address”) • HTML • uses tags for formatting (e.g., “italic”), • Key idea: • create tag sets for a domain (e.g., genomics) • translate all data into properly tagged XML docs Salman Azhar: Database Systems

  27. Well-Formed and Valid XML • Well-Formed XML • allows you to invent your own tags • similar to labels in semi-structured data graph • Valid XML • involves a DTD (Document Type Definition) • DTD gives • a grammar for the use of labels • limits the set of labels our of node • the order and number of times a label occurs Salman Azhar: Database Systems

  28. Well-Formed XML • All XML documents have • Header • Body • Header defines • version • specifies that the document is in well-formed XML • Body can include • root tag • several properly matching tags Salman Azhar: Database Systems

  29. Well-Formed XML: Header • Start the document with a declaration • surrounded by <? … ?> . • Normal declaration for Well-Formed XML is: <? XML VERSION = “1.0” STANDALONE = “yes” ?> • Version indicates version number • Standalone = “yes” means no DTD • no DTD means well-formed XML Salman Azhar: Database Systems

  30. Well-Formed XML: Body • Body of document is a root tag surrounding nested tags. • Body can include: • several properly matching tags • (as in html structure) • special tag called root tag • can have a special meaning such as document type • or can be generic Salman Azhar: Database Systems

  31. Tags • Tags, as in HTML • are normally matched pairs, as • <BLAH> … </BLAH> • may be nested arbitrarily • some tags requiring no matching ending • such as <P> in HTML, are also permitted • however, we will not use these in examples Salman Azhar: Database Systems

  32. Example: Well-Formed XML Root tag RESTS surrounds the entire document <? XML VERSION = “1.0” STANDALONE = “yes” ?> <RESTS> <REST> <NAME>Taco Bell</NAME> <SODA><NAME>Pepsi</NAME> <PRICE>1.00</PRICE></ SODA> <SODA><NAME>Sobe</NAME> <PRICE>2.00</PRICE></SODA> </REST > <REST> … </REST > … </RESTS> One of several nested REST tags representing information about a single REST <NAME> tag specifies the REST name <SODA> tags have names and price for each Soda nested in <NAME> and <PRICE> tags Literal Data items are contained at the atomic level Salman Azhar: Database Systems

  33. XML and Semi-structured Data • Consider this… • Is Well-Formed XML documents with nested tags is exactly the same idea as trees of semi-structured data? • Tags • are the labels on edges • Nodes • represent data between matching tags • Parent-child relationship • is immediate nesting in XML Salman Azhar: Database Systems

  34. XML and Semi-structured Data • Semi-structured approach allows for non-tree structures • We shall see that XML also enables non-tree structures • mimics the semi-structured data model Salman Azhar: Database Systems

  35. Group Exercise • Convert the following into a Semi-structured representation <? XML VERSION = “1.0” STANDALONE = “yes” ?> <RESTS> <REST> <NAME>Taco Bell</NAME> <SODA><NAME>Pepsi</NAME> <PRICE>1.00</PRICE></ SODA> <SODA><NAME>Sobe</NAME> <PRICE>2.00</PRICE></SODA> </REST > <REST> … </REST > … </RESTS> Note: Do not turn over to the next page before attempting this exercise yourself! Salman Azhar: Database Systems

  36. Solution:The semi-structured representation <? XML VERSION = “1.0” STANDALONE = “yes” ?> <RESTS> <REST> <NAME>Taco Bell</NAME> <SODA><NAME>Pepsi</NAME> <PRICE>1.00</PRICE></ SODA> <SODA><NAME>Sobe</NAME> <PRICE>2.00</PRICE></SODA> </REST > <REST> … </REST > … </RESTS> RESTS REST REST REST NAME . . . SODA SODA Note: Data is stored in leaf nodes and structure (tags) in internal nodes Taco Bell PRICE NAME PRICE NAME Pepsi 1.00 Sobe 2.00 Salman Azhar: Database Systems

  37. Valid XML • Switching gears: Well-formed to Valid XML • Valid XML is the most interesting use of XML • Essentially a context-free grammar for describing XML tags and their nesting • Specified by DTD • Each domain of interest creates one DTD that describes all the documents this group will share • For example, electronic components, travel industry, etc., will have their own DTDs Salman Azhar: Database Systems

  38. DTD Structure <!DOCTYPE<root tag> [ <!ELEMENT<name> ( <components> ) <more elements> ]> Note: !DOCTYPE is key word with <root tag> being the name of DOCTYPE Between [ … ] list of ELEMENT definition Each !ELEMENT has a <name> with the allowed list of <components> usually in the order listed Salman Azhar: Database Systems

  39. DTD Elements • Element definition consists • of its name (tag) • and a parenthesized description of any nested tags • includes order of subtags • and their multiplicity (0, 1, or many times) • Leaves (text elements) • have #PCDATA in place of nested tags Salman Azhar: Database Systems

  40. Example: DTD <!DOCTYPE RESTS [ <!ELEMENT RESTS (REST*)> <!ELEMENT REST (RNAME, SODA+)> <!ELEMENT NAME (#PCDATA)> ]> RESTS can have * (0 or more) REST REST has NAME and then + (1 or more) SODA… Order matters! NAME and PRICE are data (#PCDATA): No more tags just text SODA has NAME followed PRICE SODA’s NAME and PRICE are data (#PCDATA) GROUP EXERCISE: COMPLETE THE DTD Note: Do not turn over to the next page before attempting this exercise yourself! Salman Azhar: Database Systems

  41. Example: DTD <!DOCTYPE RESTS [ <!ELEMENT RESTS (REST*)> <!ELEMENT REST (RNAME, SODA+)> <!ELEMENT NAME (#PCDATA)> <!ELEMENT SODA (NAME, PRICE)> <!ELEMENT NAME (#PCDATA)> <!ELEMENT PRICE (#PCDATA)> ]> RESTS can have * (0 or more) REST REST has NAME and then + (1 or more) SODA… Order matters! NAME and PRICE are data (#PCDATA): No more tags just text SODA has NAME followed PRICE Salman Azhar: Database Systems

  42. Element Descriptions Rules • Subtags must appear in order shown • A tag may be followed by a symbol to indicate its multiplicity: • Identical to UNIX regular expressions. • * = zero or more. • + = one or more. • ? = zero or one. • Alternative sequences of tags can be connected by • the symbol | Salman Azhar: Database Systems

  43. Example: Element Description • A name is • Either an optional title (e.g., “Dr.”), a first name, and a last name, in that order, • or it is an IP address <!ELEMENT NAME ( (TITLE?, FIRST, LAST) | IPADDR )> Alternative symbol Salman Azhar: Database Systems

  44. Use of DTDs • In order to specify a document follows a particular DTD • Set STANDALONE = “no” • Either include the DTD as a preamble of the XML document • Follow DOCTYPE and the <root tag> by SYSTEM and a path to the file where the DTD is stored Salman Azhar: Database Systems

  45. Example (a) <? XML VERSION = “1.0” STANDALONE = “no” ?> <!DOCTYPE RESTS [ <!ELEMENT RESTS (REST*)> <!ELEMENT REST (NAME, SODA+)> <!ELEMENT NAME (#PCDATA)> <!ELEMENT SODA (NAME, PRICE)> <!ELEMENT NAME (#PCDATA)> <!ELEMENT PRICE (#PCDATA)> ]> <RESTS> <REST> <NAME>Taco Bell</NAME> <SODA><NAME>Pepsi</NAME> <PRICE>1.00</PRICE></ SODA> <SODA><NAME>Sobe</NAME> <PRICE>2.00</PRICE></SODA> </REST > <REST> … </REST > … </RESTS> DTD Document Same as earlier but this time it conforms to the above DTD Salman Azhar: Database Systems

  46. Example (b) • Assume the RESTS DTD is in file rest.dtd <? XML VERSION = “1.0” STANDALONE = “no” ?> <!DOCTYPE Rests SYSTEM “rest.dtd”> <RESTS> <REST> <NAME>Taco Bell</NAME> <SODA><NAME>Pepsi</NAME> <PRICE>1.00</PRICE></ SODA> <SODA><NAME>Sobe</NAME> <PRICE>2.00</PRICE></SODA> </REST > <REST> … </REST > … </RESTS> Get the DTD from the file rest.dtd DocumentSame as earlier but this time it conforms to the DTD in rest.dtd Salman Azhar: Database Systems

  47. Attributes • Attributes are another important component of DTD and XML docs • Opening tags in XML can have attributes • like <A HREF = “…”> in HTML • In DTD <!ATTLIST <elementname>… > • gives a list of attributes and their data types for this element Salman Azhar: Database Systems

  48. Example: Attributes • Rests can have an attribute kind • which is either qsr, family, or other. • The element definition is unchanged • However, we add an ATTLIST. <!ELEMENT REST (NAME SODA*)> <!ATTLIST REST kind “qsr” | “family” | “other”> Salman Azhar: Database Systems

  49. Example: Attribute Use • In a document that allows REST tags, we might see: <REST kind = “qsr”> <NAME>KFC</NAME> <SODA><NAME>Pepsi</NAME> <PRICE>1.00</PRICE></SODA> ... </REST> New info: kind = “qsr” Salman Azhar: Database Systems

  50. IDs and IDREFs • Introduce links from one object to another • Allows the structure of an XML document to be a general graph • rather than just a tree. • These are pointers from one object to another • in analogy to HTML’s NAME = “blah” and HREF = “#blah” Salman Azhar: Database Systems

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