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Efficient Exploitation of Similar Subexpressions for Query Processing

机译:有效利用相似子表达式进行查询处理

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Complex queries often contain common or similar subexpressions, either within a single query or among multiple queries submitted as a batch. If so, query execution time can be improved by evaluating a common subexpression once and reusing the result in multiple places. However, current query optimizers do not recognize and exploit similar subexpressions, even within the same query. We present an effcient, scalable, and principled solution to this long-standing optimization problem. We introduce a light-weight and effective mechanism to detect potential sharing opportunities among expressions. Candidate covering subexpressions are constructed and optimization is resumed to determine which, if any, such subexpressions to include in the ?nal query plan. The chosen subexpression(s) are computed only once and the results are reused to answer other parts of queries. Our solution automatically applies to optimization of query batches, nested queries, and maintenance of multiple materialized views. It is the ?rst comprehensive solution covering all aspects of the problem: detection, construction, and cost-based optimization. Experiments on Microsoft SQL Server show signi?cant performance improvements with minimal overhead.
机译:复杂查询通常包含单个子查询中或成批提交的多个查询中的公共或相似子表达式。如果是这样,可以通过一次评估一个公共子表达式并在多个地方重用结果来缩短查询执行时间。但是,即使在同一查询中,当前的查询优化器也无法识别和利用相似的子表达式。我们为这个长期存在的优化问题提出了一种有效,可扩展且原则性的解决方案。我们引入了一种轻量级的有效机制来检测表达式之间的潜在共享机会。构建涵盖子表达式的候选对象,并继续进行优化以确定哪些子表达式(如果有的话)包含在最终查询计划中。所选的子表达式仅计算一次,结果被重用于回答查询的其他部分。我们的解决方案自动应用于查询批处理,嵌套查询的优化以及多个物化视图的维护。这是涵盖问题各个方面的第一个综合解决方案:检测,构造和基于成本的优化。在Microsoft SQL Server上进行的实验表明,以最小的开销就可以显着提高性能。

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