TY - GEN
T1 - Federated SPARQL queries processing with replicated fragments
AU - Montoya, Gabriela
AU - Skaf-Molli, Hala
AU - Molli, Pascal
AU - Vidal, Maria Esther
PY - 2015/1/1
Y1 - 2015/1/1
N2 - Federated query engines provide a unified query interface to federations of SPARQL endpoints. Replicating data fragments from different Linked Data sources facilitates data re-organization to better fit federated query processing needs of data consumers. However, existing federated query engines are not designed to support replication and replicated data can negatively impact their performance. In this paper, we formulate the source selection problem with fragment replication (SSP-FR). For a given set of endpoints with replicated fragments and a SPARQL query, the problem is to select the endpoints that minimize the number of tuples to be transferred. We devise the Fedra source selection algorithm that approximates SSP-FR. We implement Fedra in the state-of-the-art federated query engines FedX and ANAPSID, and empirically evaluate their performance. Experimental results suggest that Fedra efficiently solves SSP-FR, reducing the number of selected SPARQL endpoints as well as the size of query intermediate results.
AB - Federated query engines provide a unified query interface to federations of SPARQL endpoints. Replicating data fragments from different Linked Data sources facilitates data re-organization to better fit federated query processing needs of data consumers. However, existing federated query engines are not designed to support replication and replicated data can negatively impact their performance. In this paper, we formulate the source selection problem with fragment replication (SSP-FR). For a given set of endpoints with replicated fragments and a SPARQL query, the problem is to select the endpoints that minimize the number of tuples to be transferred. We devise the Fedra source selection algorithm that approximates SSP-FR. We implement Fedra in the state-of-the-art federated query engines FedX and ANAPSID, and empirically evaluate their performance. Experimental results suggest that Fedra efficiently solves SSP-FR, reducing the number of selected SPARQL endpoints as well as the size of query intermediate results.
KW - Federated query processing
KW - Fragment replication
KW - Linked data
KW - Source selection
UR - http://www.scopus.com/inward/record.url?scp=84952315835&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-25007-6_3
DO - 10.1007/978-3-319-25007-6_3
M3 - Article in proceeding
AN - SCOPUS:84952315835
SN - 9783319250069
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 36
EP - 51
BT - The Semantic Web – ISWC 2015 - 14th International Semantic Web Conference, Proceedings
A2 - d’Aquin, Mathieu
A2 - Thirunarayan, Krishnaprasad
A2 - Srinivas, Kavitha
A2 - Groth, Paul
A2 - Arenas, Marcelo
A2 - Corcho, Oscar
A2 - Strohmaier, Markus
A2 - Heflin, Jeff
A2 - Simperl, Elena
A2 - Staab, Steffen
A2 - Dumontier, Michel
PB - Springer
T2 - 14th International Semantic Web Conference, ISWC 2015
Y2 - 11 October 2015 through 15 October 2015
ER -