SGER: Staged Query Processing

在当今的数据管理环境中，查询处理分布在多个组件中，每个中间件组件执行其中的一些任务，并且某些任务执行多次，我们称之为阶段式查询处理。多个阶段的潜在存在限制了中间件组件可用的信息，特别是对查询优化的影响。传统的方法，基于成本的查询优化，其中列举了许多查询计划，并选择最便宜的一个，是不合适的，当详细的成本度量是不可用的，当后面的阶段执行自己的，复杂的优化。一种新的方法，称为成本为基础的图重写，是用来转换一个查询语言的查询可能是一种不同的语言，一个有效的输出查询。一种新颖的惯用成本估计器为重写器提供成本参数，使重写器能够确定应该在组件内进行的处理以及应该由后续阶段执行的处理。这个估计器比传统的估计器更粗粒度;特别是，它不会在查询计划中花费单个关系运算符。这个探索性研究项目的目标是开发一个初始原型，利用这些概念的时态中间件组件翻译TSQL 2到SQL，并评估这种方法的有效性，针对至少两个不同的商业DBMS，并证明中间件组件可以反映这些DBMS的差异，在生成的代码。

In today's data management environment, query processing is spread across multiple components, with each middleware component doing some of these tasks, and with some tasks done several times, which we term staged query processing. The potential presence of multiple stages restricts the information available to the middleware component, with particular impact on query optimization. The conventional approach, of cost-based query optimization, in which numerous query plans are enumerated and the cheapest one selected, is not appropriate when detailed cost metrics are not available and when the later stages perform their own, complex optimization. A new approach, termed cost-based graph rewriting, is used to transform a query in one query language into an efficient output query in perhaps a different language. A novel idiomatic cost estimator provides cost parameters to the rewriter, enabling the rewriter to determine the processing that should take place within the component, and the processing that should be performed by later stages. This estimator is more coarse-grained than conventional estimators; in particular, it does not cost individual relational operators in a query plan. The goal of this exploratory research project is to develop an initial prototype utilizing these concepts for a temporal middleware component translating TSQL2 into SQL, and to evaluate the efficacy of this approach by targeting at least two different commercial DBMSs and demonstrating that the middleware component can reflect the differences of these DBMSs in the generated code.