Physical Data Independence, Constraints, and Optimization with Universal Plans
Physical Data Independence, Constraints, and Optimization with Universal Plans
复制标题
物理数据独立性、约束和通用计划的优化
DOI：
--
复制
发表时间：
1999
期刊：
影响因子：
--
通讯作者：
V. Tannen
中科院分区：
文献类型：
--
作者：
Alin Deutsch;Lucian Popa;V. Tannen
我们提出了一种针对三个目标设计的优化方法和Al Gorithm：物理数据独立性，语义优化和广义图表最小化。该方法依赖于Chase的广义形式和具有约束的“回电”（依赖CIES）。通过在物理模式中使用字典（有限函数），我们可以使用有用的访问结构（例如索引，实现的视图，源能力，访问支持关系，GMAPS等）捕获。方式：Chase阶段将原始查询重写为“通用”计划，该计划集成了Appli Cable约束允许的所有访问结构和替代途径。然后，回电阶段再次根据约束，通过消除各种裁员组合来产生最佳计划。此方法适用于大量查询，物理访问结构和语义约束。我们证明，实际上，使用复杂的对象，类和dictio naries的“路径连接”查询和视图是完整的，这超出了使用实体视图的处理查询的先前理论工作。评论后版本。发表在国际大型数据库会议上（VLDB）（1999），第459-470页。发布者URL：http：//www.dcs.napier.ac.uk/~vldb99/本会议论文可通过ScholarlyCommons获得：http：//repositority.upenn.edu/db_research/26物理数据独立约束和优化计划Alin Deutsch Lucian Popa Val Val Tannen宾夕法尼亚大学
We present an optimization method and al gorithm designed for three objectives: physi cal data independence, semantic optimization, and generalized tableau minimization. The method relies on generalized forms of chase and "backchase" with constraints (dependen cies). By using dictionaries (finite functions) in physical schemas we can capture with con straints useful access structures such as indexes, materialized views, source capabilities, access support relations, gmaps, etc. The search space for query plans is defined and enumerated in a novel manner: the chase phase rewrites the original query into a "universal" plan that integrates all the access structures and alternative pathways that are allowed by appli cable constraints. Then, the backchase phase produces optimal plans by eliminating various combinations of redundancies, again according to constraints. This method is applicable (sound) to a large class of queries, physical access structures, and semantic constraints. We prove that it is in fact complete for "path-conjunctive" queries and views with complex objects, classes and dictio naries, going beyond previous theoretical work on processing queries using materialized views. Comments Postprint version. Published in International Conference on Very Large Databases (VLDB) (1999), pages 459-470. Publisher URL: http://www.dcs.napier.ac.uk/~vldb99/ This conference paper is available at ScholarlyCommons: http://repository.upenn.edu/db_research/26 Physical Data Independence Constraints and Optimization with Universal Plans Alin Deutsch Lucian Popa Val Tannen University of Pennsylvania