Enabling structural summaries for efficient update and workload adaptation

  • Authors:

  • Qun Chen;Andrew Lim;Kian Win Ong

  • Affiliations:

  • School of Computer, Northwestern Polytechnical University, Xi'an, China;Department of Industrial Engineering and Engineering Management, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong;Department of Computer Science and Engineering, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0114, United States

  • Venue:
  • Data & Knowledge Engineering
  • Year:
  • 2008

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Abstract

To facilitate queries over semi-structured data, various structural summaries have been proposed. Structural summaries are derived directly from data and serve as the indexes for evaluating path expressions. We introduce D(k)-index, an adaptive structural summary, for general graph-structured data. Building on previous 1-index and A(k)-index, D(k)-index is also based on the concept of bisimilarity. However, as a generalization of 1-index and A(k)-index, D(k)-index possesses the adaptive ability to adjust its structure to changes in query load. It also enables efficient update algorithms, which are crucial to real applications but have not been adequately addressed in previous literatures. Our experiments show that D(k)-index is a more effective structural summary than previous static ones as a result of its query load sensitivity. In addition, the update operations on it can be performed more efficient than on its predecessors.