Finding hot query patterns over an XQuery stream

  • Authors:

  • Huai Yang;Li Lee;Wynne Hsu

  • Affiliations:

  • School of Computing, National University of Singapore, Singapore and School of Electronics Engineering and Computer Science, Peking University, P.R. China;School of Computing, National University of Singapore, Singapore;School of Computing, National University of Singapore, Singapore

  • Venue:
  • The VLDB Journal — The International Journal on Very Large Data Bases
  • Year:
  • 2004

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Abstract

Caching query results is one efficient approach to improving the performance of XML management systems. This entails the discovery of frequent XML queries issued by users. In this paper, we model user queries as a stream of XML query pattern trees and mine the frequent query patterns over the query stream. To facilitate the one-pass mining process, we devise a novel data structure called DTS to summarize the pattern trees seen so far. By grouping the incoming pattern trees into batches, we can dynamically mark the active portion of the current batch in DTS and limit the enumeration of candidate trees to only the currently active pattern trees. We also design another summary data structure called ECTree that provides for the incremental computation of the frequent tree patterns over the query stream. Based on the above two constructs, we present two mining algorithms called XQSMinerI and XQSMinerII. XQSMinerI is fast, but it tends to overestimate, while XQSMinerII adopts a filter-and-refine approach to minimize the amount of overestimation. Experimental results show that the proposed methods are both efficient and scalable and require only small memory footprints.