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

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.