FedAggs: Optimizing Aggregate Queries Evaluation in Federated RDF Systems

Ningchao Ge, Peng Peng, Zheng Qin, Mingdao Li

Abstract: With the increasing scale of RDF datasets and the security requirements of data management, federated RDF systems are becoming a research hotspot. However, the existing federated RDF systems only support basic queries in SPARQL 1.0, and cannot be compatible with complex queries in SPARQL 1.1 well, such as aggregate queries. In this demo, we develop a demonstration system, named FedAggs, which can support efficient aggregate queries in federated RDF system. It implements five common aggregate operators in federated RDF system: MAX, MIN, AVG, SUM and COUNT. FedAggs improves the efficiency of aggregate query processing by adopting a query decomposition optimization method, employing a cost-based optimal query plan generation algorithm and an incremental execution strategy according to the characteristics of five aggregate operators. Experimental results show that FedAggs has good query performance.