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首页> 外文期刊>International Journal of Innovative Research in Science, Engineering and Technology >Optimizing Evaluated Preference Data in Relational Database Using Query Optimization
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Optimizing Evaluated Preference Data in Relational Database Using Query Optimization

机译：使用查询优化在关系数据库中优化评估的偏好数据

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Preference-aware queries are needed to be processed closer to the DBMS. Preference database tuples are elaborated from the preference-aware relational data model and the queries with the preferences are processed using an extended algebra. Query optimization strategies are provided for extended query plan based on the set of algebraic properties and cost model. Further illustration of an query execution algorithm that blends preference evaluation with query execution, simultaneously utilizing the native query engine. The framework and methods have been implemented in a prototype system, PrefDB. Transparent and efficient evaluations of preferential queries of a relational DBMS are allowed by PrefDB. This results in experimenting extensive evaluation on two real world data sets which illustrates the feasibility and advantages of the framework. Early pruning of results based on score or confidence during query processing are enabled by combining the prefer operator with the rank and rank join operators.
机译：需要将偏好感知查询处理得更靠近DBMS。从偏好感知的关系数据模型中详细说明了偏好数据库元组，并使用扩展代数来处理具有偏好的查询。提供了基于一组代数属性和成本模型的扩展查询计划的查询优化策略。同时使用本机查询引擎的将偏好评估与查询执行融合在一起的查询执行算法的进一步说明。该框架和方法已在原型系统PrefDB中实现。 PrefDB允许对关系DBMS的优先查询进行透明而有效的评估。这导致对两个真实世界的数据集进行广泛评估的实验，这些数据集说明了该框架的可行性和优势。通过将Preferred运算符与rank和rank join运算符相结合，可以在查询处理期间基于分数或置信度对结果进行早期修剪。

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