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Exploring Query Optimization in Programming Codes by Reducing Run-Time Execution

机译:通过减少运行时执行来探索编程代码中的查询优化

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Object querying is an abstraction of operations over collections, whereas manual implementations are performed at low level which forces the developers to specify how a task must be done. Some object-oriented languages allow the programmers to express queries explicitly in the code, which are optimized using the query optimization techniques from the database domain. In this regard, Java Query Language has been developed that allows object querying and performs the query optimization at run-time. Therefore, only one problem is how to reduce the task of query optimization at run-time as much as possible within the Java Query Language system. In this paper, we have developed a technique that performs query optimization at compile-time to reduce the burden of optimization at run-time to improve the performance of the code execution. The proposed approach uses histograms that are computed from the data and these histograms are used to get the estimate of selectivity for query joins and predicates in a query at compile-time. With these estimates, a query plan is constructed at compile-time and executed it at run-time. The experimental trials show that our method performs better in terms of run time comparisons than the existing query optimization techniques used in the Java Query Language.
机译:对象查询是对集合的操作的抽象,而手动实现是在较低级别上执行的,这迫使开发人员指定必须完成任务的方式。一些面向对象的语言允许程序员在代码中显式表达查询,这些查询使用数据库域中的查询优化技术进行了优化。在这方面,已经开发了Java查询语言,它允许对象查询并在运行时执行查询优化。因此,唯一的问题是如何在Java Query Language系统中尽可能减少运行时的查询优化任务。在本文中,我们开发了一种在编译时执行查询优化的技术,以减轻运行时的优化负担,从而提高代码执行的性能。所提出的方法使用从数据中计算出的直方图,并且这些直方图用于在编译时获取查询联接和查询中谓词的选择性估计值。利用这些估计,可以在编译时构造查询计划,并在运行时执行查询计划。实验表明,与Java查询语言中使用的现有查询优化技术相比,我们的方法在运行时比较方面表现更好。

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