Capabilities-Based Query Rewriting in Mediator Systems

  • Authors:
  • Yannis Papakonstantinou;Ashish Gupta;Laura Haas

  • Affiliations:
  • UCSD, Computer Science & Engineering, La Jolla, CA 92093-0114. E-mail: yannis@cs.ucsd.edu;Junglee Corp., 4149B El Camino Way, Palo Alto, CA 94306. E-mail: ashish@junglee.com;IBM Almaden Research Center, 650 Harry Road, San Jose, CA 95120. E-mail: laura@almaden.ibm.com

  • Venue:
  • Distributed and Parallel Databases - Special issue on parallel and distributed information systems
  • Year:
  • 1998

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Abstract

Users today are struggling to integrate a broad range of informationsources providing different levels of query capabilities. Currently, datasources with different and limited capabilities are accessed either bywriting rich functional wrappers for the more primitive sources, or bydealing with all sources at a “lowest common denominator”. Thispaper explores a third approach, in which a mediator ensures that sourcesreceive queries they can handle, while still taking advantage of all of thequery power of the source. We propose an architecture that enables this, andidentify a key component of that architecture, the Capabilities-BasedRewriter (CBR). The CBR takes as input a description of the capabilities ofa data source, and a query targeted for that data source. From these, theCBR determines component queries to be sent to the sources, commensuratewith their abilities, and computes a plan for combining their results usingjoins, unions, selections, and projections. We provide a language todescribe the query capability of data sources and a plan generationalgorithm. Our description language and plan generation algorithm are schemaindependent and handle SPJ queries. We also extend CBR with a cost-basedoptimizer. The net effect is that we prune without losing completeness.Finally we compare the implementation of a CBR for the Garlic project withthe algorithms proposed in this paper.