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Loading RDF/OWL File into Oracle NoSQL database using a Bulk Loading and Parallelization Techniques

机译:使用批量加载和并行化技术将RDF / OWL文件加载到Oracle NoSQL数据库中

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Processing and loading large RDF/OWL data files often involves the transfer of large amounts of data from source operational systems to the target data store. It requires a proper loading techniques and more expressive methods to ensure the RDF/OWL data files are correctly loaded into the database, or the loading process will end up finishing all memory space which resulted in performance deterioration in the entire application. The Bulk loading is one of the predominant scientific techniques and with fastest loading method to load large amounts of data into the database; however, this study has found out that the bulk loading alone, cannot handle triples files containing object values with more than 4000 bytes. To solve these tidy problems, we propose to implement bulk loading techniques concurrently with parallelization methods to load RDF/OWL data file into the database. To accomplish this goal, the Oracle NOSQL database is chosen as the backend persistent storage for the RDF/OWL data files. In addition, loading model and techniques are provided to utilize the loading process, and finally algorithms, methods and parallelization techniques are given with the aim of increasing loading performance of RDF/OWL within the Oracle NOSQL database.
机译:处理和加载大型RDF / owl数据文件通常涉及将大量数据从源操作系统传输到目标数据存储。它需要适当的加载技术和更多的表达方法,以确保RDF / OWL数据文件正确加载到数据库中,或者加载过程将结束完成所有内存空间,导致整个应用程序中的性能恶化。批量负载是主要的科学技术之一,最快的加载方法将大量数据加载到数据库中;但是,本研究发现,单独的批量加载,不能处理包含超过4000字节的对象值的三元组文件。要解决这些整理问题,我们建议使用并行化方法同时实现批量加载技术,将RDF / OWL数据文件加载到数据库中。要完成此目标,请选择Oracle NoSQL数据库作为RDF / OWL数据文件的后端持久存储。此外,提供了加载模型和技术来利用加载过程,最后给出了算法,方法和并行化技术,目的是在Oracle NoSQL数据库中增加RDF / owl的加载性能。

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