Querying Distributed RDF Data Sources with SPARQL

Abstract

Abstract. Integrated access to multiple distributed and autonomous RDF data sources is a key challenge for many semantic web applications. As a reaction to this challenge, SPARQL, the W3C Recommendation for an RDF query language, supports querying of multiple RDF graphs. However, the current standard does not provide transparent query federation, which makes query formulation hard and lengthy. Furthermore, current implementations of SPARQL load all RDF graphs mentioned in a query to the local machine. This usually incurs a large overhead in network traffic, and sometimes is simply impossible for technical or legal reasons. To overcome these problems we present DARQ, an engine for federated SPARQL queries. DARQ provides transparent query access to multiple SPARQL services, i.e., it gives the user the impression to query one single RDF graph despite the real data being distributed on the web. A service description language enables the query engine to decompose a query into sub-queries, each of which can be answered by an individual service. DARQ also uses query rewriting and cost-based query optimization to speed-up query execution. Experiments show that these optimizations significantly improve query performance even when only a very limited amount of statistical information is available. DARQ is available under GPL License at http://darq.sf.net/.

DAW: Duplicate-AWare Federated Query Processing over the Web of Data

“…Quilitz and Leser [21] propose an index-assisted federated query engine named DARQ for remote RDF data sources. DARQ combines service descriptions, query rewriting mechanisms and a cost-based optimisation approach to reduce the query processing time and the bandwidth usage.…”

“…We implemented our DAW approach on top of three different federated query engines: DARQ [21], SPLENDID [8], and FedX [22]. Both DARQ and SPLENDID already provide an index with some of the statistics needed in DAW.…”

“…As a result, certain queries can only be answered by retrieving information from several data sources. This type of queries, called federated queries, are becoming increasingly popular within the Web of Data [1,3,8,9,12,14,21,22].…”

“…We extend three well-known federated query engines -DARQ [21], SPLEN-DID [8], and FedX [22] -with DAW, and compare these extensions with the original frameworks. The comparison shows that DAW requires fewer sources for each of the query's triple pattern, therefore improving query execution times.…”

Benchmarking Federated SPARQL Query Engines: Are Existing Testbeds Enough?

“…In parallel to the development of federated SPARQL query evaluation systems, several testbeds have been created (e.g., as described in [2,7,8]), which complement those already used for single-endpoint query evaluation. The role of these testbeds is to allow evaluating and comparing the main characteristics of these systems, so as to provide enough information to improve them.…”