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Adaptive Join Processing in Pipelined Plans

机译:流水线计划中的自适应联接处理

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摘要

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.
机译:在自适应查询处理中,根据查询评估期间从环境获得的反馈来更改查询评估的方式。例如,这种反馈可以确定在编译查询时使用了误导性的选择性估计,从而导致优化程序选择了不合适的连接顺序或不合适的连接算法。本文描述了如何在流水线计划中评估联接时如何对联接进行重新排序以及如何替换联接算法。在评估过程中对连接进行重新排序和/或替换的地方,该方法通过从先前计划的中断位置继续执行,避免了重复进行的工作。已经对该方法进行了经验评估,并根据误导的选择性估计显示了对改善查询性能的有效方法。

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