An XML Index Advisor for DB2

Iman Elghandour, Ashraf Aboulnaga, Daniel C. Zilio, Fei Chiang, Andrey Balmin, Calisto Zuzarte, Kevin Beyer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

XML database systems are expected to handle increasingly complex queries over increasingly large and highly structured XML databases. An important problem that needs to be solved for these systems is how to choose the best set of indexes for a given workload. We have developed an XML Index Advisor that solves this XML index recommendation problem and is tightly coupled with the query optimizer of the database system. We have implemented our XML Index Advisor for DB2. In this demonstration we showcase the new query optimizer modes that we added to DB2, the index recommendation process, and the effectiveness of the recommended indexes.

Original languageEnglish
Title of host publicationSIGMOD 2008
Subtitle of host publicationProceedings of the ACM SIGMOD International Conference on Management of Data 2008
Pages1267-1270
Number of pages4
DOIs
Publication statusPublished - 10 Dec 2008
Event2008 ACM SIGMOD International Conference on Management of Data 2008, SIGMOD'08 - Vancouver, BC, Canada
Duration: 9 Jun 200812 Jun 2008

Publication series

NameProceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)0730-8078

Conference

Conference2008 ACM SIGMOD International Conference on Management of Data 2008, SIGMOD'08
CountryCanada
CityVancouver, BC
Period9/6/0812/6/08

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Keywords

  • Automatic Physical Database Design
  • Index Advisor
  • Xml Databases

ASJC Scopus subject areas

  • Software
  • Information Systems

Cite this

Elghandour, I., Aboulnaga, A., Zilio, D. C., Chiang, F., Balmin, A., Zuzarte, C., & Beyer, K. (2008). An XML Index Advisor for DB2. In SIGMOD 2008: Proceedings of the ACM SIGMOD International Conference on Management of Data 2008 (pp. 1267-1270). [1376752] (Proceedings of the ACM SIGMOD International Conference on Management of Data). https://doi.org/10.1145/1376616.1376752