Structure and value synopses for XML data graphs

  • Authors:

  • Neoklis Polyzotis;Minos Garofalakis

  • Affiliations:

  • University of Wisconsin-Madison;Bell Labs, Lucent Technologies

  • Venue:
  • VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
  • Year:
  • 2002

Quantified Score

Hi-index 0.00

Visualization

Abstract

All existing proposals for querying XML (e.g., XQuery) rely on a pattern-specification language that allows (1) path navigation and branching through the label structure of the XML data graph, and (2) predicates on the values of specific path/branch nodes, in order to reach the desired data elements. Optimizing such queries depends crucially on the existence of concise synopsis structures that enable accurate compile-time selectivity estimates for complex path expressions over graph-structured XML data. In this paper, we extent our earlier work on structural XSKETCH synopses and we propose an (augmented) XSKETCH synopsis model that exploits localized stability and value-distribution summaries (e.g., histograms) to accurately capture the complex correlation patterns that can exist between and across path structure and element values in the data graph. We develop a systematic XSKETCH estimation framework for complex path expressions with value predicates and we propose an efficient heuristic algorithm based on greedy forward selection for building an effective XSKETCH for a given amount of space (which is, in general, an NP-hard optimization problem). Implementation results with both synthetic and real-life data sets verify the effectiveness of our approach.