XSEED: Accurate and Fast Cardinality Estimation for XPath Queries

Authors:
Ning Zhang;M. Tamer Ozsu;Ashraf Aboulnaga;Ihab F. Ilyas
Affiliations:
University of Waterloo;University of Waterloo;University of Waterloo;University of Waterloo
Venue:
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Year:
2006

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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.