Query Optimization in Multidatabase Systems

  • Authors:
  • D. K. Subramanian;K. Subramanian

  • Affiliations:
  • Department of Computer Science and Automation, Indian Institute of Science, Bangalore, 560 012, India. E-mail: dks@csa.iisc.ernet.in;Motorola India Electronics Ltd., Bangalore, 560 042, India. E-mail: ks@miel.mot.com

  • Venue:
  • Distributed and Parallel Databases
  • Year:
  • 1998

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Abstract

Global query execution in a multidatabase system can be doneparallelly, as all the local databases are independent. In this paper, acost model that considers parallel execution of subqueries for a globalquery is developed. In order to obtain maximum parallelism in queryexecution, it is required to find a query execution plan that isrepresented in the form of a bushy tree and this query tree should bebalanced to the maximal possible extent with respect to execution time. A new bottom up approach called Agglomerative Approach (AA) is proposed toconstruct balanced bushy trees with respect to execution time. By thedeterministic nature of this approach, it generates local optimal solutions. This local minima problem will be severe in the case of graph queries, i.e., queries that are represented with a graph structure. ASimulated annealing Approach (SA) is employed to obtain a (near) optimalsolution. These approaches (AA and SA) are suitable for handling on-lineand off-line queries respectively. A Hybrid Approach (HA), that is anintegration of AA and SA, is proposed to optimize queries for which theestimated time to be spent on optimization is known a priori. Resultsobtained with AA and SA on both tree and graph structured queries arepresented.