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|Title:||APPROXIMATE: A Query Processor That Produces Monotonically Improving Approximate Answers|
|Author(s):||Vrbsky, Susan Vlasta|
|Doctoral Committee Chair(s):||Liu, Jane W.S.|
|Department / Program:||Computer Science|
|Degree Granting Institution:||University of Illinois at Urbana-Champaign|
|Abstract:||For some applications, it may be better for a database to produce an approximate answer when it is not possible to produce an exact answer. We have designed and implemented a query processor, called APPROXIMATE, that makes approximate answers available if part of the database is unavailable or if there is not enough time to produce an exact answer. The accuracy of the approximate answers produced improves monotonically with the amount of data retrieved to produce the result. APPROXIMATE returns the exact answer if all of the needed data are available and if there is enough time to continue with the processing. The latest, best available approximate answer is returned if the user demands an answer before query processing is completed. The approximate query processing algorithm of APPROXIMATE works within a standard relational algebra framework.
In this thesis, we present the approximation semantics of APPROXIMATE that serves as the basis for meaningful approximations to set-valued and single-valued queries, and the approximate query processing algorithm used by APPROXIMATE. APPROXIMATE uses an object-oriented view of the database. This view provides semantic information about the initial approximations to a query and information about which segments of the database can be retrieved. A distance function is defined to provide additional semantic support needed to compare the accuracies of approximate answers to the exact answer and information about the convergence of approximate answers. We describe the overhead incurred by this semantic support and present an implementation of APPROXIMATE.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1993.
|Date Available in IDEALS:||2014-12-17|