Temporal Information and XML

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Temporal Informationand XML

• Carlo Zaniolo
• Department of Computer Science
• University of California, Los Angeles

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A Short History of Timein Databases

• Relational model between 33 and 48 temporal DB
  proposals counted
• A struggle to get around the limitations of
  relational (flat) tables and a rigid query
  language (SQL)
• A key issue Temporal interval coalescing is
  needed after each projection!
• Clustering, indexing, query optimization for
  temporal information add to the complexity

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Coalescing

• Time stamping the individual tuplesIf we
  want the salary history, we have to coalesce the
  last three tuples into one

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XML

• XML hierarchical views with temporal groups
• Temporal grouped models are more natural and
  powerful, but they did not fit in the flat
  relational model
• XML Query languages can easily express temporal
  queries on these views.

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History Tables

• Time-stamped tuples in relations

• Temporally grouped time-stamped attribute values

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Historical XML Database ArchitectureTwo
Approaches

• Native XML databases
• Historical data are stored in native XML database
• XML queries can be specified directly upon the
  database
• Native XML databasesTamino(Software AG),
  eXcelon(XIS)
• XML-enabled RDBMS
• Historical view decomposed into relational
  databases as binary tables
• Historical data can then be published as XML
  document through SQL/XML publishing functions or
  queried through a middleware as XML views

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Historical XML Views Architecture
SQL Queries
Relational Data Current Content
Temporal Queries
XML VIEWS
Historical Data
Historical Database
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Relational Storage of Temporal Relational Data

• Relational schema
• employee(empno, name, sal, title, deptno)
• Attribute history tables employee_sal
  (empno, sal, tstart, tend)
• employee_title(empno, title, tstart, tend)
• An internal relation for each time-varying
  attribute
• XQuery statements on the XML views translated
  into SQL statements on the internal relations

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Experiments

• Simulated data with history of 300,024 employees
• Comparing Native XML DBs
• SoftwareAGs Tamino (text-based storage). XPath
• eXcelons XIS (XML Information Server)
  (OODBMS-based storage). XQuery
• Against DB2.

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Preliminary Performance Comparisons
Storage Size
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Performance Comparisons (contd)
Query Performance of DB2 and Tamino
Q2 history query Q4,Q6 snapshot queries Q3,Q5
interval queries Q1 scan of databases Q7 join
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Performance Comparisons (contd)
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Related Problems

• Query Performance
• Indexing R trees
• Temporal clustering tuples from the same time
  period should be assigned to same page
• Page Usefulness method. A page with employee
  records for a department. After 60 quit that
  page is only 40 useful.
• Compression should not be ruled out
• sparingly used in DBs, but important for XML
• DB2 mainframes, Oracle
• Updates not a problem for histories.

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Research (cont.)

• XML Query languages are powerful and temporal
  queries can be expressed in XQuery without any
  extension, but not for all users
• User-friendly QBE-like language for temporally
  grouped model
• SQLXML temporal views and queries
• ROLLUPS-like temporal views (and SQL1999)
• Different viewsbut the same RDBMS-based
  implementation underneath.

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XML Representation of DB HistoryTable Columns as
XML Elements
ltemployees tstart"1995-01-01"
tend"1996-12-31"gt ltemployee tstart"1995-01-01"
tend"1996-12-31"gt ltempno tstart"1995-01-01"
tend"1996-12-31"gt10003lt/empnogt ltname
tstart"1995-01-01" tend"1996-12-31"gtBoblt/namegt
ltsalary tstart"1995-01-01" tend"1995-05-31"gt60
000lt/salarygt ltsalary tstart"1995-06-01"
tend"1996-12-31"gt70000lt/salarygt lttitle
tstart"1995-01-01" tend"1995-09-30"gtEngineerlt/ti
tlegt lttitle tstart"1995-10-01"
tend"1996-01-31"gtSr Engineerlt/titlegt lttitle
tstart"1996-02-01" tend"1996-12-31"gtTech
Leaderlt/titlegt ltdept tstart"1995-01-01"
tend"1995-09-30"gtQAlt/deptgt ltdept
tstart"1995-10-01" tend"1996-12-31"gtRDlt/deptgt
ltDOB tstart"1995-01-01" tend"1996-12-31"gt1945-0
4-09lt/DOBgt lt/employeegt lt!-- More
--gt lt/employeesgt
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Thank you!

• http//wis.cs.ucla.edu

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References

• S. Sarawagi, S. Thomas,R. Agrawal Integrating
  Association Rule Mining with Relational Database
  Systems Alternatives and Implications,SIGMOD
  1998
• Fusheng Wang, Carlo Zaniolo Publishing and
  Querying the Histories of Archived Relational
  Databases in XML. 4thInternational Conference on
  Web Information Systems Engineering, December
  10th - 12th, 2003 Roma, Italy.
• Haixun Wang, Carlo Zaniolo, Chang Richard Luo
  ATLaS a Small but Complete SQL Extension for
  Data Mining and Data Streams. VLDB 2003--Demo.
• Haixun Wang and Carlo Zaniolo ATLaS A Native
  Extension of SQL for Data Mining. SIAM
  International Conference on Data Mining 2003, San
  Francisco, CA, May 1-3, 2003
• Reza Sadri, Carlo Zaniolo, Amir M. Zarkesh, Jafar
  Adibi A Sequential Pattern Query Language for
  Supporting Instant Data Minining for e-Services,
  VLDB 2001.
• Haixun Wang, Carlo Zaniolo Using SQL to Build
  New Aggregates and Extenders for Object-
  Relational Systems. VLDB 2000.