XML%20Research%20Issues%20in%20Database%20Perspective

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XML Research Issues in Database Perspective

• Kyuseok Shim
• shim_at_cs.kaist.ac.kr
• http//cs.kaist.ac.kr/shim
• Korea Advanced Institute of Science and Technology

2
XML Working Groups

• Core XML
• XML, namespaces, XML Inforset
• XML Linking
• Xpath, Xpointer, Xlink
• XML Schema
• XML Schema
• XML Query
• XML Query, XML Query Data Model
• Document Object Model (DOM)
• XSL

3
XML

• A W3C standard to complement HTML
• An instance of semistructured data Abi97
• Document Type Descriptor (DTD)
• Origin SGML
• Tags describe the semantics of the data
• HTML simply specify how the data time is to be
  displayed
• An element can contain a sequence of nested
  sub-elements
• Sub-elements may themselves be tagged elements or
  character data

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Document Type Definition (DTD)

• A part of XML specification
• An XML document may have a DTD
• Grammar for describing the structure of XML
  document
• The structure of an element is specified by a
  regular expression
• Terminology for XML
• well-formed if tags are correctly closed
• valid if it has a DTD and conforms to it
• For exchanges of data, validation is useful

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Document Type Definition (DTD)

• Syntax
• comma sequence
• or
• () grouping
• ?, , zero or one, zero or more, one or more
  occurrences
• ANY allows an arbitrary XML fragment to be
  nested within the element

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A DTD Example

• lt!ENTITY USA United States of Americagt
• lt!ELEMENT book (booktitle, author)gt
• lt!ATTLIST book id ID IMPLIEDgt
• lt!ELEMENT booktitle (PCDATA)gt
• lt!ELEMENT author (name, (address affiliation))gt
• lt!ELEMENT name (PCDATA)gt
• lt!ELEMENT address ANYgt
• lt!ELEMENT affiliation (PCDATA)gt

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An XML Document Example

• ltbook id123gt
• ltbooktitlegt The Selfish Gene lt/booktitlegt
• ltauthor iddawkinsgt
• ltnamegt Richard Dawkins lt/namegt
• ltaddressgt
• ltcitygt Timbuktu lt/citygt
• ltzipgt 99999 lt/zipgt
• lt/addressgt
• lt/authorgt
• lt/bookgt
• ltbookgt
• ltbooktitlegt The C Programming Languagelt/booktitle
  gt
• ltauthorgt
• ltnamegt Brian W. Kernighan lt/namegt
• ltaddressgt ltcountrygt USA lt/countrygt lt/addressgt
• lt/authorgt
• ltauthorgt
• ltnamegt Dennis M. Ritchie lt/namegt
• ltaffiliationgt Bell Labs lt/affiliationgt

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An XML Namespace

• Provides a simple method for qualifying element
  and attribute names used in Extensible Markup
  Language documents by associating them with
  namespaces identified by URI references.
• Is a collection of names, identified by a URI
  reference, which are used in XML documents as
  element types and attribute names.
• ltx xmlnsedi'http//ecommerce.org/schema'gt
•  lt!the 'price' element's namespace is http//ecom
  merce.org/schema --gt
•   ltediprice units'Euro'gt32.18lt/edipricegt
• lt/xgt

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XML Schemas

• Recently proposed
• http//www.w3c.org/TR/xmlschema-1
• http//www.w3c.org/TR/xmlschema-2
• Unifies previous schema proposals
• Generalizes DTDs
• Use XML syntax

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XML Schema

• ltelementType name articlegt
• ltsequencegt
• ltelementTypeRef name title/gt
• ltelementTypeRef name author
  minOccurs0/gt
• lt/sequencegt
• lt/elementTypegt
• DTD lt!ELEMENT article (title, author)gt

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XTRACT Extracting DTD from XML Documents

• Garofalakis, Gionis, Rastogi, Seshadri, Shim 99
• DTDs contain valuable information on the
  structure of the documents
• play a critical role in the storage as well as
  formulation and optimization of queries
• DTDs are not mandatory
• it is frequently possible the XML database does
  not have accompanying DTDs
• XTRACT can infer concise and semantically
  meaningful DTDs for XML documents

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XTRACT Motivation

• DTD is very useful!
• Plays a crucial role in efficient storage of XML
  data
• SHT99, DFS99 DTDT is exploited to generate
  effective relational schema
• Devise efficient plans for queries
• GW97, FS97 DTD allows to restrict the search
  only relevant portions of the data
• Aids users to form meaningful queries over the
  XML database
• However, XML document may not always have an
  accompanying DTD

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XTRACT Related Work

• Mining DTDs from a collection of XML documents
  has not been addressed in the literature
• Extraction of schema from semistructured data
• NAM98, GW97, FS97
• attempts to find typing for semistructured data
• finding a typing is tantamount to grouping
  objects that have similar edges
• In DTD, outgoing edges from a type can be
  described by an arbitrary regular expression
• No ordering is imposed for edges

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XTRACT Related Work

• Gol67, Gol78, Ang78
• Infer formal languages from examples
• Purely theoretical and focus on investigating the
  computational complexity of the language
  inference problem
• KMU95
• Infers a pattern language from positive examples
• MDL principle was used
• Assume the set of simple patterns is available
• Cannot find general regular expressions
• Patterns are not known apriori

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XTRACT Problem Formulation

• Given a set I of N input sequences nested within
  elements e
• Compute a DTD for e such that every sequence in I
  conforms to the DTD

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XTRACT Naive Approaches

• Factor as much as possible
• e.g. t, ta, taa, taaa, taaaa
• t t (a a(a a(a aa)))
• much more voluminous and a lot less intuitive
• Find the automaton with the smallest number of
  states that accepts I and drive regular
  expressions from automaton
• may not be the shortest regular expression

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XTRACT Desirable DTDs

• The DTD should be concise (i.e. small in size)
• easy to understand and succinct
• The DTD should be precise
• not cover too many sequences not contained in I
• not too general and captures the structure f
  input sequences
• Trade-off!

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XTRACT Example

• I ab, abab, ababab
• (a b)
• a gross over-generalization of the input
• completely fails to capture any structure
  inherent in input
• ab abab ababab, ab ab(ab abab)
• accurately reflect the structure of the input
  sequences but do not generalize
• (ab)
• succinct and generalizes the input sequence
  without loosing too much structure information

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XTRACT MDL Principle

• An information-theoretic measure for quantifying
  and thereby resolving the tradeoff between the
  conciseness and preciseness
• MDL principle has been successfully applied in a
  variety of situations
• e.g. decision tree classifiers
• Roughly speaking, the best theory to infer from a
  set of data is the one that minimizes the sum of
• the length of the theory, in bits (conciseness)
• the length of the data, in bits, when encoded
  with the help of the theory (preciseness)

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XTRACT Example

• I ab, abab, ababab
• (a b)
• abab cost of 5 (the number of repetitions (4)
  4 characters to represent chosen character)
• MDL cost 6 (encoding DTD) 3 5 7 21
• ab abab ababab
• MDL cost 14 3 17
• ab ab(ab abab)
• MDL cost 14 1 2 2 19
• (ab)
• MDL cost 5 3 8

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XTRACT

• Generalization
• generalizes zero or more candidate DTDs by
  replacing patters in the input sequence with
  meta-characters like
• e.g. abab gt (ab), bbbe gt be
• Factorization
• factors common subexpressions from the
  generalized candidate DTDs
• e.g. bd be gt b (d e)
• Minimum Description Length (MDL) Principle
• MDL ranks each candidate DTD and chooses the
  minimum cost DTD

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XTRACT Example
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XML Storage

• Existing approaches either sacrifice efficiency
  or flexibility unnecessary
• Traditional DBMSs (RDB or OODB) have rigid
  schemas.
• Integrating a new site requires complex mapping
  and potential loss of information
• Integrating a new site may require schema
  evolution.
• Existing fully semi-structured data storage
  techniques sacrifice query efficiency and space.
• they require excessive interpretation (harming
  query efficiency) and
• redundant storage

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XML Storage

• Need to store and query XML data flexibly and
  efficiently
• improve the tradeoffs for storage space and
  query efficiency for a given degree of
  flexibility.
• allows user to choose the degree of storage
  flexibility

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XML Storage

• text file
• relational DBMS
• object-oriented DBMS
• build special purpose repository

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XML Storage Text File

• To store the flat streams, file system or a BLOB
  manager in DBMS is used
• e.g. Abiteboul, Cluet, Milo VLDB93
• Pros
• simple
• fast for storing and retrieving whole documents
• less space than one think
• reasonable clustering
• Cons
• incremental update is difficult
• require special purpose query processor
• accessing documents structure is only possible
  through parsing

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XML Storage Relational DBMS

• Advantages
• RDBMS products are mature and scales well
• Traditional and semi-structured data can co-exist
• RDBMS can process even complex queries on large
  databases within seconds
• Disadvantages
• expensive to reconstruct the original XML data
  from relational data
• updates are both complicated and expensive for a
  certain cases
• extra efforts to translate XML queries and
  updates into SQL

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XML Storage RDMBS (1)

• Florescu, Kossmann IEEE Data Eng. Bulletin 99

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XML Storage RDBMS (2)

• Shanmugasundaram et al. 99
• process DTD to generate a relational schema
• Use DTD graph and element graph
• three approaches
• Basic
• Shared
• Hybrid

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DTD
31
XML Document
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The Basic Inline Technique

• Creates relations for every element
• an XML document can be rooted at any element in a
  DTD
• element graph is used to decide the relations
• Inlines as many descendants as possible
• e.g. the author relation has attributes
  firstname, lastname, address and authorid
• Creates a separate relation to handle in DTD
  graph using a foreign key
• Expresses the recursive relationship using the
  notion of relational keys

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Building an Element Graph

• Do a depth first traversal of the DTD graph
  starting at the element node
• Each node is marked as visited the first time
  reached
• Each node is unmarked once all of its children
  have been traversed
• If an unmarked node in DTD graph is reached, a
  new node with the same name is created in the
  element graph
• If an attempt is made to traverse marked DTD
  node, backpointer edge is added

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DTD Graph
35
An Example Element Graph
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Creation of Relations

• Given an element graph, relations are created as
  follows
• A relation is produced for the root element
• All descendent elements are inlined into that
  relation except
• children directly below a node
• each node having a backpointer edge pointing to
  it
• A separate relation is created for each of the
  above exception node
• Each relation has ID and parentID fields

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Basic Inline Schema
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Basic Inline Technique

• Pros
• List all authors of books
• Cons
• List all authors having first name Jack (5
  separate queries)
• Large number of relations are created

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Shared Inline Technique

• Relations are created for all elements in the DTD
  graph whose nodes have in-degree greater than one
• Nodes with an in-degree of one are inlined
• Nodes with an in-degree of zero are made separate
  relations
• Of mutually recursive elements all having
  in-degree one, one of them is made a separate
  relation
• e.g. monograph and editor

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Shared Inlining Technique

• Small number of relations compared to Basic
  schema
• Use isRoot field for inlining problems
• Requires only one query for finding all authors
• Still Basic is superior for reducing the number
  of joins

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Shared Inlining Technique

• Additionally inlines elements with in-degree
  greater than one that are not recursive or
  reached through a node
• e.g. author is inlined with book and monograph

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XML Storage STORED

• Deutsch, Fernandez, Suciu SIGMOD99
• Semistructured data into relational data
• Integrate both relational and overflow systems
• Use data mining algorithm to find out frequent
  subtrees
• due to the fact that there is no notion of DTD in
  semistructured data
• Overflow mapping is used to insure lossless
• overflow objects or object parts are stored in a
  separate semistructured data object repository
• Incremental updates and ordering of elements are
  not considered

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XML Storage STORED

• Derive schema from data with data mining algorithm

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XML Storage OODBMS

• Stores XML elements with the structured semantics
• Flexible locking down to element level
• In RDBMS, due to disassembly of XML data into
  various tables, implementing an effective locking
  scheme is hard
• In using flat file, no portion of a document
  being modified is available to other users
• Use a separate record for each tree node
• Systems available
• POET (POET Content Management system)
• Excelon (ObjectDesign)
• LORE

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XML Storage NATIX

• Kanne, Moerkotte ICDE00
• Native repository
• Classical record manager
• Accesses raw disk or file system files
• Provides a memory space divided into segments
  (equal sized pages)
• Tree storage manager
• maps treed used to model documents
• Schema manager
• maintains the system catalog data (e.g. DTD)
• system catalog is stored in XML format

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NATIX

• Store whole document in one record, instead of
  storing each tree node in a separate record
• Semantically split large tree based on underlying
  tree structure
• Partition the data into subtrees and store each
  subtree in a record
• Connected subtrees residing in other records are
  represented by proxy objects
• proxy objects consist of RID
• substituting all proxies by the respective
  subtrees reconstruct the original data tree

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XML Query Processing

• McHugh, Widom Workshop 99
• Expand regular path expressions at compile time
  using structural summary
• Guarantee to visit, at run-time, a subset of the
  objects visited with the original path expression
  
• e.g. Library. -
• Proceedings.Conference.Paper
• Books.Book
• Movies.Movie.BasedOn

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XML Query Processing

• Fernandez, Suciu ICDE 98
• Optimize regular path expressions
• Restrict navigation to only a fragment of the
  data
• Use state extents to eliminate and reduce
  navigation
• McHugh, Widom VLDB 99
• Propose cost-based query optimizer
• Transform a query into a logical query plan
• Explore the space of possible physical plans
• Introduce new types of indexes for efficient
  traversals through data graphs
• Suggest an appropriate set of statistics and
  devise methods for computing and storing
  statistics

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XML Query Processing

• Christophides, Cluet, Simeon SIGMOD 00
• Propose an XML algebra
• Captures the expressive power of semistructured
  or XML query languages
• Can wrap more structures languages such as SQL or
  OQL
• New optimization techniques
• Exploit type information
• Push query evaluation to external source

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XML View of Relational Data

• Fernandez, Tan, Suciu WWW 00
• Mediator system
• Automatically convert the relational data into
  XML
• An XML view of the relational database is defined
  using a declarative query language
• Some other application formulates a query over
  the virtual view
• Exploit fully underlying RDBMS query engine

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XML View of Relational Data

• Shanmugasundaram et al. VLDB 00
• Propose to use new scalar and aggregate in SQL to
  construct complex XML document
• Explore different execution plans for generating
  the contents of XML documents
• Construct XML document inside the relational
  engine benefits most for performance
• Outer union plan

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Metadata Management

• Generic data model
• Not impossible, but unlikely
• Proliferation of data models
• No proof anyone is superior
• Semantics arent fully captured in any data model

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Metadata Management

• Philip Bernstein VLDB 00s Panel
• Generality - representation of metadata must
  apply to all application areas
• Usefulness exploit application-specific
  semantics
• Is there an effective middle-ground?
• Define generic high-level operations on models
  and mappings, e.g., Match, Merge, Select,
  Compose,
• Match(M1, M2, ?, map), Merge(M1, M2, map),
  Compose(map1, map2)
• Implement operations on a DBMS

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Metadata Management
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Metadata Management Clio

• Miller, Haas, Hernandez VLDB 00
• Tool to support mapping between data
  representations
• Mapping represented as SQL
• Heterogeneous query middleware to examine data
  and schemas
• Build database competencies in query and schema
  management, data mining
• Exploit user knowledge of target semantics
• Enhance user knowledge of source schema and data
• Provide knowledge of query subtleties,
  alternative mappings

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Metadata Management Clio

• User indicates what schema and data values are
  needed for target
• Tool enumerates and ranks mappings
• Many possible subtle differences
• Best mappings are simple, but lose least
  information possible
• Allows immediate user feedback

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Filtering XML Documents

• Altinel, Franklin VLDB 00
• Xfilter provides highly efficient matching of
  XML documents to user profiles
• Event filtering system
• Highly scalable
• Use XPath as a profile language

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XML Data Compression

• Liefke, Suciu SIGMOD 00
• Structure, consisting of tags and attributes, is
  compressed separately
• Group related data items and compress each
  related group separately
• Apply semantic compression
• Automatic data mining tools to cluster data needs
  to be developed

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Future Research Issues

• XML views of traditional databases
• Relational database
• Object-relational database
• XML Storage
• Object-relational databases
• Alternative storage methods
• Indexes for XML data
• XML query processing and optimization
• Centralized and distributed processing

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Future Research Issues

• Schema mapping
• Mixing structure search with full-text search
• XML-based mediators
• XML data compression

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Summary

• XML provides a lot of challenges to database
  community
• XML Storage Issues
• XML Indexes
• DTD Extraction
• Query language
• Query processing
• Metadata Management

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Biography of Kyuseok Shim

• Kyuseok Shim is an Assistant Professor in
  Computer Science Department at KAIST in Korea. He
  is also currently an Advisory Committee Member
  for ACM SIGKDD. Before joining KAIST, he was a
  member of technical staff (MTS) in the Database
  Systems Research Department at Bell Laboratories.
  While he was in Bell Laboratories, he started and
  worked for Serendip data mining project and
  eXcalibur XML storage project. Before joining
  Bell Laboratories, he worked for Rakesh Agrawal's
  Quest data mining project at IBM Almaden Research
  Center. He also worked with Surajit Chaudhuri as
  a summer intern for two summers at Hewlett
  Packard Laboratories. He received B.S. degree in
  Electrical Engineering from Seoul National
  University, and the MS and Ph.D. degree in
  Computer Science from University of Maryland,
  College Park.
• Kyuseok Shim has been working in the area
  of databases focusing on XML, data mining, data
  warehousing, query processing and query
  optimization. He has published more than 30
  research papers in prestigious international
  conferences and journals. He has also served as a
  program committee member on several international
  conferences including ICDE'97, SIGKDD'98,
  SIGMOD'99, SIGKDD'99, ICDE'00, VLDB'00 and
  SIGKDD01.