The implementation and performance evaluation of the ADMS query optimizer: Integrating query result caching and matching

  • ChungMin Melvin Chen
  • Nicholas Roussopoulos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 779)


In this paper, we describe the design and evaluation of the ADMS optimizer. Capitalizing on a structure called Logical Access Path Schema to model the derivation relationship among cached query results, the optimizer is able to perform query matching coincidently with the optimization and generate more efficient query plans using cached results. The optimizer also features data caching and pointer caching, alternative cache replacement strategies, and different cache update strategies. An extensive set of experiments were conducted and the results showed that pointer caching and dynamic cache update strategies substantially speedup query computations and, thus, increase query throughput under situations with fair query correlation and update load. The requirement of the cache space is relatively small and the extra computation overhead introduced by the caching and matching mechanism is more than offset by the time saved in query processing.


Query Processing Data Cache Query Optimizer Query Graph Cache Management 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • ChungMin Melvin Chen
    • 1
  • Nicholas Roussopoulos
    • 1
  1. 1.Department of Computer ScienceUniversity of MarylandCollege ParkUSA

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