On the upcoming colloquium, Muhammad Saleem will present his paper “LargeRDFBench: A Billion Triples Benchmark for SPARQL Endpoint Federation” about the benchmarking of federated SPARQL endpoints. The other talk will be an introduction to the Docker ecosystem by Tim Ermilov.
LargeRDFBench: A Billion Triples Benchmark for SPARQL Endpoint Federation
Authors: Muhammad Saleem, Ali Hasnain, Axel Ngonga
Abstract. Gathering information from the Web of Data is commonly carried out by using SPARQL query federation approaches. However, the fitness of current SPARQL query federation approaches for real applications is difficult to evaluate with current benchmarks as they are either synthetic, too small in size and complexity or do not provide means for a fine-grained evaluation. We propose LargeRDFBench, a billion-triple benchmark for SPARQL query federation which encompasses real data as well as real queries pertaining to real bio-medical use cases. We evaluate state-of-the-art SPARQL endpoint federation approaches on this benchmark with respect to their query runtime, triple pattern-wise source selection, result completeness and correctness. Our evaluation results suggest that the performance of current SPARQL query federation systems on simple queries (in terms of total triple patterns, query result set sizes, execution time, use of SPARQL features etc.) does not reflect the systems’ performance on more complex queries. Moreover, current federation systems seem unable to deal with real queries that involve processing large intermediate result sets or lead to large result sets.
Introduction To The Docker Ecosystem
Presented by: Tim Ermilov
Slides are available online
On the upcoming colloquium, Muhammad Saleem will present his paper “LargeRDFBench: A Billion Triples Benchmark for SPARQL Endpoint Federation” about the benchmarking of federated SPARQL endpoints. The other talk will be an introduction to the Docker ecosystem by Tim Ermilov.
LargeRDFBench: A Billion Triples Benchmark for SPARQL Endpoint Federation
Authors: Muhammad Saleem, Ali Hasnain, Axel Ngonga
Abstract. Gathering information from the Web of Data is commonly carried out by using SPARQL query federation approaches. However, the fitness of current SPARQL query federation approaches for real applications is difficult to evaluate with current benchmarks as they are either synthetic, too small in size and complexity or do not provide means for a fine-grained evaluation. We propose LargeRDFBench, a billion-triple benchmark for SPARQL query federation which encompasses real data as well as real queries pertaining to real bio-medical use cases. We evaluate state-of-the-art SPARQL endpoint federation approaches on this benchmark with respect to their query runtime, triple pattern-wise source selection, result completeness and correctness. Our evaluation results suggest that the performance of current SPARQL query federation systems on simple queries (in terms of total triple patterns, query result set sizes, execution time, use of SPARQL features etc.) does not reflect the systems’ performance on more complex queries. Moreover, current federation systems seem unable to deal with real queries that involve processing large intermediate result sets or lead to large result sets.
Introduction To The Docker Ecosystem
Presented by: Tim Ermilov
Slides are available online.
Each talk will last for 20 minutes. The audience will have 10 minutes to ask questions. There will be cookies and coffee break after the talks for discussion as well.
