sybase ASE 15中的排序、区别性、聚合、分区和DQP优化

Mihnea Andrei, Xun Cheng, Sudipto Chowdhuri, Curtis Johnson, Edwin Seputis
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引用次数: 3

摘要

Sybase ASE RDBMS版本15进行了主要的增强,包括语义分区和完整的QP重写。新的ASE QP支持对语义分区表的水平和垂直并行处理,以及许多其他现代QP技术,如基于成本的渴望聚合和基于成本的连接重定位DQP。在新的查询优化器中,排序、区别性、聚合、分区和DQP优化基于一个公共框架:计划片段等价类和逻辑属性。我们的主要成果是a)排序、分区和DQP位置的急切执行策略;B)一种区别性和聚合性优化策略,机会性地基于渴望排序执行,其优化时间计算复杂度与连接处理相似;c)支持用户强制所有上述优化器决策,仍然保证有效的计划,基于抽象计划技术。我们描述了该解决方案在ASE 15优化器中的实现。最后,我们给出了我们的实验结果:生成如此复杂的计划伴随着优化器的SS大小的小幅增加,因此在可接受的优化时间内;在执行时,我们已经获得了一些查询的数量级性能改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ordering, distinctness, aggregation, partitioning and DQP optimization in sybase ASE 15
The Sybase ASE RDBMS version 15 was subject to major enhancements, including semantic partitions and a full QP rewrite. The new ASE QP supports horizontal and vertical parallel processing over semantically partitioned tables, and many other modern QP techniques, as cost-based eager aggregation and cost-based join relocation DQP. In the new query optimizer, the ordering, distinctness, aggregation, partitioning, and DQP optimizations were based on a common framework: plan fragment equivalence classes and logical properties. Our main outcomes are a) an eager enforcement policy for ordering, partitioning and DQP location; b) a distinctness and aggregation optimization policy, opportunistically based on the eager ordering enforcement, and which has an optimization-time computational complexity similar to join processing; c) support for the user to force all of the above optimizer decisions, still guaranteeing a valid plan, based on the Abstract Plan technology. We describe the implementation of this solution in the ASE 15 optimizer. Finally, we give our experimental results: the generation of such complex plans comes with a small increase of the optimizer's SS size, hence within an acceptable optimization time; at execution, we have obtained performance improvements of orders of magnitude for some queries.
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