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Efficient Exploitation of Similar Subexpressions for Query Processing

机译:高效利用类似子表达的查询处理

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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:复杂查询通常包含常见或类似的子表单,无论是单一查询中还是在作为批处理提交的多个查询中。如果是,则可以通过评估一次常见的子表达式并在多个位置重用结果来提高查询执行时间。但是,即使在同一查询中,当前查询优化器也不识别和利用类似的子表单抑制。我们对这种长期优化问题提出了效率,可扩展性和原则性的解决方案。我们介绍了一种轻量级和有效的机制,以检测表达中的潜在共享机会。构建候选覆盖子表单抑制,恢复优化以确定哪些子表单抑制在?nal查询计划中包含。所选择的子表达式仅计算一次,并且结果重复使用以应答查询的其他部分。我们的解决方案自动适用于查询批处理,嵌套查询和维护多个物流视图的优化。它是第一个全面的解决方案,涵盖了问题的各个方面:检测,结构和基于成本的优化。 Microsoft SQL Server的实验显示Signi?Cant性能改进,最小的开销。

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