Adaptive join processing in pipelined plans
Adaptive join processing in pipelined plans
复制标题
流水线计划中的自适应连接处理
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
S. Lynden
中科院分区：
文献类型：
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作者：
Kwanchai Eurviriyanukul;N. Paton;A. Fernandes;S. Lynden
在自适应查询处理中，根据查询评估过程中从环境中获得的反馈来改变查询的评估方式。例如，这样的反馈可能确定在编译查询时使用了误导性的选择性估计，从而导致优化器选择了不合适的连接顺序或不合适的连接算法。本文描述了当连接在流水线计划中进行评估时，如何对连接进行重新排序，以及如何替换所使用的连接算法。如果连接在评估期间被重新排序和/或替换，该方法可以通过从上一个计划停止的地方恢复来避免重复已经执行的工作。该方法已经经过了经验评估，并被证明在误导性选择性估计的情况下有效地提高了查询性能。
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.