A Cost Model for Querying Distributed RDF-Repositories with SPARQL

In the last years, the query language SPARQL has evolved into the widely accepted standard for querying RDF. Since many Semantic Web applications make use of data whose storage and management is distributed, distributed SPARQL query processing becomes necessary. In the relation and object-oriented database community the efficiency gain by cost-based, adaptive optimizers for distributed querying is proven, though such optimizers are not available for SPARQL. Thus we describe in this paper a cost model which is meant to act as a sub component of a query optimizer for distributed SPARQL query processing to serve as a cost indicator for other subcomponents of the optimizer, e.g. query decomposition, query rewriting and choosing join algorithms and their order. The cost model is tailored for a heterogeneous grid of SPARQL processors and represents query plans as SPARQL Query Graph Models (SQGM). Costs are assigned in an System-R-like fashion relying on recursive cost and cardinality functions. Therefore evaluation complexities of basic operations in SPARQL queries are derived from the complexities of best practice algorithms for the algebraically equivalent basic operations in relational query languages.