Klaus Peithner

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In this paper we develop a novel optimization strategy for disjunctive queries involving join predicates. This work is an extension of our previously published approach KMPS94] for optimizing disjunctive selection predicates by generating two output streams from selection operators: a \true"-stream for objects (tuples) satisfying the selection predicate and(More)
In this work, we propose and assess a technique called <italic>bypass processing</italic> for optimizing the evaluation of disjunctive queries with expensive predicates. The technique is particularly useful for optimizing selection predicates that contain terms whose evaluation costs vary tremendously; e.g., the evaluation of a nested subquery or the(More)
Adopting the blackboard architecture from the area of Articial Intelligence, a novel kind of optimizer enabling two desirable ideas will be proposed. Firstly, using such a well-structured approach backpropagation of the optimized queries allows an evolutionary improvement of (crucial) parts of the optimizer. Secondly, the A 3 search strategy can be applied(More)
ÐIt is striking that the optimization of disjunctive queriesÐi.e., those which contain at least one or-connective in the query predicateÐhas been vastly neglected in the literature, as well as in commercial systems. In this paper, we propose a novel technique, called bypass processing, for evaluating such disjunctive queries. The bypass processing technique(More)
We investigate the optimization and evaluation of queries with universal quantification in the context of the object-oriented and object-relational data models. The queries are classified into 16 categories depending on the variables referenced in the so-called range and quantifier predicates. For the three most important classes we enumerate the known(More)
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