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- Stefanova, Silvia, et al.
(författare)
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Optimizing Unbound-property Queries to RDF Views of RelationalDatabases
- 2011
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Konferensbidrag (refereegranskat)abstract
- SAQ (Semantic Archive and Query) is a system for querying and long-term preservation of relational data in terms of RDF. In SAQ relational data in a back-end DBMS is exposed as an RDF view, called the RD-view. SAQ can process arbitrary SPARQL queries to the RD-view. In addition long-term preservation as RDF of selected parts of a relational database is specified by SPARQL queries to the RD-view. Such queries usually select sets of RDF properties and thus in the query definition a property p is unknown. We call such queries unbound-property queries. This class of queries is also present in the SPARQL benchmarks. We optimize unbound-property queries by introducing a query transformation algorithm called Group Common Terms, GCT. It pulls out from a DNF normalized query those common terms that can be translated to SQL predicates accessing the relational database. Our experiments using the Berlin SPARQL benchmark show that GCT improves substantially the query execution time to a back-end commercial relational DBMS for both selective and unselective unbound-property queries. We compared the performance of our approach with the performance of other systems processing SPARQL queries over views of relational databases and showed that GCT improves scalability compared to the approaches used by the other systems.
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| 2. |
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| 3. |
- Stefanova, Silvia, et al.
(författare)
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Viewing and Querying Topic Maps in terms of RDF
- 2008
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Ingår i: SEMMA2008: First International Workshop on Semantic Metadata Management and Applications.
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Konferensbidrag (refereegranskat)abstract
- Both Topic Maps and RDF are popular semantic web standards designed for machine processing of web documents. Since these representations were originally created for different purposes, they have conceptual differences in their data models, and therefore have different tools to parse, store, and query them. However, there are more tools to handle RDF data than those existing for Topic Maps. Our approach is to map Topic Maps to a view expressed in RDF and then query this view by the RDF query language SPARQL. To achieve this, a generic conceptual schema of Topic Maps is defined using a functional data model. Based on the conceptual schema of Topic Maps, an automatic mapping from Topic Maps to the RDF data model is developed. The mapping provides a general view of any Topic Map data in terms of RDF that can be queried using SPARQL. Query rewriting techniques based on partial evaluation enable realistic performance.
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| 4. |
- Zhu, Minpeng, et al.
(författare)
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Scalable Numerical SPARQL Queries over Relational Databases
- 2014
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Konferensbidrag (refereegranskat)abstract
- We present an approach for scalable processing of SPARQL queries to RDF views of numerical data stored in relational databases (RDBs). Such queries include numerical expressions, inequalities, comparisons, etc. inside FILTERs. We call such FILTERs numerical expressions and the queries - numerical SPARQL queries. For scalable execution of numerical SPARQL queries over RDBs, numerical operators should be pushed into SQL rather than executing the filters as post-processing outside the RDB; otherwise the query execution is slowed down, since a lot of data is transported from the RDB server and furthermore indexes on the server are not utilized. The NUMTranslator algorithm converts numerical expressions in numerical SPARQL queries into corresponding SQL expressions. We show that NUMTranslator improves substantially the scalability of SPARQL queries based on a benchmark that analyses numerical logs stored in an RDB. We compared the performance of our approach with the performance of other systems processing SPARQL queries to RDF views of RDBs and show that NUMTranslator improves substantially the scalability of numerical queries compared to the other systems’ approaches.
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