Name
Abstract | ||
|---|---|---|
The increasing use of data analytics on Linked Data leads to the requirement for SPARQL engines to efficiently execute Online Analytical Processing (OLAP) queries. While SPARQL 1.1 provides basic constructs, further development on optimising OLAP queries lacks benchmarks that mimic the data distributions found in Link Data. Existing work on OLAP benchmarking for SPARQL has usually adopted queries and data from relational databases, which may not well represent Linked Data. We propose an approach that maps typical OLAP operations to SPARQL and a tool named ASPG to automatically generate OLAP queries from real-world Linked Data. We evaluate ASPG by constructing a benchmark called DBOBfrom the online DBpedia endpoint, and use DBOB to measure the performance of the Virtuoso engine. |
Year | Venue | Field |
|---|---|---|
2016 | JIST | Data analysis,Information retrieval,Relational database,Computer science,Linked data,SPARQL,Online analytical processing,Named graph,Benchmarking,Database |
DocType | Citations | PageRank |
Conference | 1 | 0.34 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin Wang | 1 | 10 | 2.86 |
| Steffen Staab | 2 | 6658 | 593.89 |
| Thanassis Tiropanis | 3 | 196 | 37.49 |