RDF Query Optimization Technique based on Program Analysis
최낙민, Eun-Sun Cho · Journal of the Institute of Electronics Engineers of Korea · 2010
Semantic Web programming is such an immature area that it is yet based on API calls, and does not provide high productivity in compiler time and sufficient efficiency in runtime. To get over this limitation, some efforts have been devoted on dedicated programming languages for Semantic Web. In this paper, we introduce a sophisticated cashing technique to enhance the runtime efficiency of RDF (Resource Description Framework) processing programs with SPARQL queries. We use static program analysis on those programs to determine what to be cashed, so as to decrease the cash miss ratio. Our method is implemented on programs in 'Jey' language, which is one of the programming languages devised for RDF data processing.