XSEED: Accurate and fast cardinality estimation for XPath queries

Ning Zhang, M. Tamer Özsu, Ashraf Aboulnaga, Ihab F. Ilyas

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

43 Citations (Scopus)

Abstract

We propose XSEED, a synopsis of path queries for cardinality estimation that is accurate, robust, efficient, and adaptive to memory budgets. XSEED starts from a very small kernel, and then incrementally updates information of the synopsis. With such an incremental construction, a synopsis structure can be dynamically configured to accommodate different memory budgets. Cardinality estimation based on XSEED can be performed very efficiently and accurately. Extensive experiments on both synthetic and real data sets show that even with less memory, XSEED could achieve accuracy that is an order of magnitude better than that of other synopsis structures. The cardinality estimation time is under 2% of the actual querying time for a wide range of queries in all test cases.

Original languageEnglish
Title of host publicationProceedings of the 22nd International Conference on Data Engineering, ICDE '06
Number of pages1
DOIs
Publication statusPublished - 17 Oct 2006
Event22nd International Conference on Data Engineering, ICDE '06 - Atlanta, GA, United States
Duration: 3 Apr 20067 Apr 2006

Publication series

NameProceedings - International Conference on Data Engineering
Volume2006
ISSN (Print)1084-4627

Other

Other22nd International Conference on Data Engineering, ICDE '06
CountryUnited States
CityAtlanta, GA
Period3/4/067/4/06

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems

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  • Cite this

    Zhang, N., Özsu, M. T., Aboulnaga, A., & Ilyas, I. F. (2006). XSEED: Accurate and fast cardinality estimation for XPath queries. In Proceedings of the 22nd International Conference on Data Engineering, ICDE '06 [1617429] (Proceedings - International Conference on Data Engineering; Vol. 2006). https://doi.org/10.1109/ICDE.2006.178