Redundant processing is a key problem in the translation of initial queries posed over an ontology into SQL queries, through mappings, as it is performed by ontology-based data access systems. Examples of such processing are duplicate answers obtained during query evaluation, which must finally be discarded, or common expressions evaluated multiple times from different parts of the same complex query. Many optimizations that aim to minimize this problem have been proposed and implemented, mostly based on semantic query optimization techniques, by exploiting ontological axioms and constraints defined in the database schema. However, data operations that introduce redundant processing are still generated in many practical settings, and this is a factor that impacts query execution. In this work we propose a cost-based method for query translation, which starts from an initial result and uses information about redundant processing in order to come up with an equivalent, more efficient translation. The method operates in a number of steps, by relying on certain heuristics indicating that we obtain a more efficient query in each step. Through experimental evaluation using the Ontop system for ontology-based data access, we exhibit the benefits of our method.

冗余处理是在基于本体的数据访问系统执行的情况下，通过映射将存在于本体上的初始查询转换为SQL查询中的一个关键问题。此类处理的示例是在查询评估期间获得的重复答案（必须最终将其丢弃），或者从同一复杂查询的不同部分多次评估了通用表达式。已经提出并实施了许多旨在最小化此问题的优化方法，这些优化方法主要是基于语义查询优化技术，它是通过利用数据库模式中定义的本体公理和约束来实现的。但是，在许多实际设置中仍会生成引入冗余处理的数据操作，这是影响查询执行的一个因素。在这项工作中，我们提出了一种基于成本的查询翻译方法，它从初始结果开始，并使用有关冗余处理的信息，以提供等效的，更有效的转换。该方法通过依赖于某些启发式操作来分多个步骤进行操作，这些启发式操作表明我们在每个步骤中都获得了更有效的查询。通过使用Ontop系统进行基于本体的数据访问的实验评估，我们展示了该方法的优势。