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Algebraic identities and query optimization in a parametric model for relational temporal databases

机译:关系时间数据库的参数模型中的代数恒等式和查询优化

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This paper presents algebraic identities and algebraic query optimization for a parametric model for temporal databases. The parametric model has several features not present in the classical model. In this model, a key is explicitly designated with a relation, and an operator is available to change the key. The algebra for the parametric model is three-sorted; it includes 1) relational expressions that evaluate to relations, 2) domain expressions that evaluate to time domains, and 3) Boolean expressions that evaluate to TRUE or FALSE. The identities in the parametric model are classified as weak identities and strong identities. Weak identities in this model are largely counterparts of the identities in classical relational databases. Rather than establishing weak identities from scratch, a meta inference mechanism, introduced in the paper, allows weak identities to be induced from their respective classical counterpart. On the other hand, the strong identities will be established from scratch. An algorithm is presented for algebraic optimization to transform a query to an equivalent query that will execute more efficiently.
机译:本文介绍了时态数据库参数模型的代数身份和代数查询优化。参数模型具有经典模型中不存在的几个功能。在此模型中,键是通过关系显式指定的,并且操作员可以更改键。参数模型的代数是三分类的。它包括1)评估为关系的关系表达式,2)评估为时域的域表达式和3)评估为TRUE或FALSE的布尔表达式。参数模型中的身份分为弱身份和强身份。该模型中的弱身份在很大程度上与经典关系数据库中的身份相对应。本文引入了一种元推理机制,而不是从头开始建立微弱的身份,而是允许从其各自的经典对应中诱发微弱的身份。另一方面,强身份将从头开始建立。提出了一种用于代数优化的算法,可将查询转换为等效查询,从而更高效地执行。

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