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Supporting SPARQL queries over relational databases becomes an active topic recently. However, it has not received enough consideration when SPARQL queries include restrictions on values (i.e filter expressions), whereas such a scenario is very common in real life applications. Challenges to solve this problem come from two aspects, (1) databases aspect. In order to fully utilize the well-developed SQL optimization engine, the generated SQL query is desired to be a single statement. (2) SPARQL query aspect. A practical SPARQL query often embeds several filters, which require comparisons between RDF results of different types. The type of RDF resources needs to be dynamically determined in the translation. In this paper, we propose an effective approach to support SPARQL queries over relational databases, with the above challenges in mind. To ensure the seamless translation, a novel facet-based scheme is designed to handle filter expressions. Optimization strategies are proposed to reduce the complexity of the generated SQL query. Experimental results confirm the effectiveness of our proposed techniques.