Abstract
A structural join finds all occurrences of structural, or containment, relationship between two sets of XML node elements: ancestor and descendant. Prior approaches to structural joins mostly focus on maintaining offline indexes on disks or requiring the elements in both sets to be sorted. However, either one can be expensive. More important, not all node elements are beforehand indexed or sorted. We present an on-demand, in-memory indexing approach to performing structural joins. There is no need to sort the elements. We discover that there are similarities between the problems of structural joins and stabbing queries. However, previous work on stabbing queries, although efficient in search time, is not directly applicable to structural joins because of high storage costs. We develop two storage reduction techniques to alleviate the problem of high storage costs. Simulations show that our new method outperforms prior approaches.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Al-Khlifa, S., Jagadish, H.V., Koudas, N., Patel, J.M., Srivastava, D., Wu, Y.: Structural joins: A primitive for efficient XML query pattern matching. In: Proc.of IEEE ICDE (2002)
Bruno, N., Koudas, N., Srivastava, D.: Holistic twig joins: Optimal XML patternmatching. In: Proc. of ACM SIGMOD (2002)
Chien, S.-Y., Vagena, Z., Zhang, D., Tsotras, V.J., Zaniolo, C.: Efficient structural joins on indexed XML documents. In: Proc. of VLDB (2002)
Dietz, P.F., Sleator, D.D.: Two algorithms for maintaining order in a list. In: Proc. of ACM Conf. on Theory of Computing (1987)
Grust, T., van Keulen, M., Teubner, J.: Staircase join: Teach a relational DBMSto watch its (axis) steps. In: Proc. of VLDB (2003)
Jiang, H., Lu, H., Wang, W., Ooi, B.C.: XR-Tree: Indexing XML data for efficient structural joins. In: Proc. of IEEE ICDE (2003)
Jiang, H., Wang, W., Lu, H., Yu, J.: Holistic twig join on indexed XML documents.In: Proc. of VLDB (2003)
Li, Q., Moon, B.: Indexing and querying XML data for regular path expressions. In: Proc. of VLDB (2001)
McHugh, J., Widom, J.: Query optimization for XML. In: Proc. of VLDB (1999)
XML Data Repository. Dept. of Computer Science and Engineering, University of Washington, http://www.cs.washington.edu/research/xmldatasets
Samet, H.: Design and Analysis of Spatial Data Structures. Addison-Wesley, Reading (1990)
Vagena, Z., Moro, M.M., Tsotras, V.J.: Efficient processing of XML containmentqueries using partition-based schemes. In: Proc. of IDEAS (2004)
Wang, W., Jiang, H., Lu, H., Yu, J.X.: PBi Tree coding and efficient processing of containment joins. In: Proc. of IEEE ICDE (2003)
Wu, K.-L., Chen, S.-K., Yu, P.S.: Query indexing with containment-encoded intervals for efficient stream processing. Knowledge and Information Systems 9(1), 62–90 (2006)
Zhang, C., Naughton, J., DeWitt, D., Luo, Q., Lohman, G.: On supporting containment queries in Relational database management systems. In: Proc. of ACM SIGMOD (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wu, KL., Chen, SK., Yu, P.S. (2006). On-Demand Index for Efficient Structural Joins. In: Yu, J.X., Kitsuregawa, M., Leong, H.V. (eds) Advances in Web-Age Information Management. WAIM 2006. Lecture Notes in Computer Science, vol 4016. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11775300_1
Download citation
DOI: https://doi.org/10.1007/11775300_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35225-9
Online ISBN: 978-3-540-35226-6
eBook Packages: Computer ScienceComputer Science (R0)