Abstract. Adaptive query processors make decisions as to the most effective evaluation strategy for a query based on feedback received while the query is being evaluated. In essence, any of the decisions made by the optimizer (e.g., on operator order or on which operators to use) may be revisited in an adaptive query processor. This paper focuses on changes to physical operators (e.g., the specific join operators used, such as hash-join or merge-join) in pipelined query evaluators. In so doing, the paper characterizes the runtime properties of pipelined operators in a way that makes explicit when specific operators may be replaced, and that allows the validity of operator replacements to be proved. This is illustrated with reference to the substitution of join operators during their evaluation.

In adaptive query processing, the way in which a query is evaluated is changed in the light of feedback obtained from the environment during query evaluation. Such feedback may, for example, establish that misleading selectivity estimates were used when the query was compiled, leading to the optimizer choosing an inappropriate join order or unsuitable join algorithms. This paper describes how joins can be reordered, and the join algorithms used replaced, while they are being evaluated in pipelined plans. Where joins are reordered and/or replaced during their evaluation, the approach avoids duplicating work that has already been carried out, by resuming from where the previous plan left off. The approach has been evaluated empirically, and shown to be effective for improving query performance in the light of misleading selectivity estimates.

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