TY - GEN
T1 - Characteristic sets
T2 - 2011 IEEE 27th International Conference on Data Engineering, ICDE 2011
AU - Neumann, Thomas
AU - Moerkotte, Guido
PY - 2011
Y1 - 2011
N2 - Accurate cardinality estimates are essential for a successful query optimization. This is not only true for relational DBMSs but also for RDF stores. An RDF database consists of a set of triples and, hence, can be seen as a relational database with a single table with three attributes. This makes RDF rather special in that queries typically contain many self joins. We show that relational DBMSs are not well-prepared to perform cardinality estimation in this context. Further, there are hardly any special cardinality estimation methods for RDF databases. To overcome this lack of appropriate cardinality estimation methods, we introduce characteristic sets together with new cardinality estimation methods based upon them. We then show experimentally that the new methods are-in the RDF context-highly superior to the estimation methods employed by commercial DBMSs and by the open-source RDF store RDF-3X.
AB - Accurate cardinality estimates are essential for a successful query optimization. This is not only true for relational DBMSs but also for RDF stores. An RDF database consists of a set of triples and, hence, can be seen as a relational database with a single table with three attributes. This makes RDF rather special in that queries typically contain many self joins. We show that relational DBMSs are not well-prepared to perform cardinality estimation in this context. Further, there are hardly any special cardinality estimation methods for RDF databases. To overcome this lack of appropriate cardinality estimation methods, we introduce characteristic sets together with new cardinality estimation methods based upon them. We then show experimentally that the new methods are-in the RDF context-highly superior to the estimation methods employed by commercial DBMSs and by the open-source RDF store RDF-3X.
UR - http://www.scopus.com/inward/record.url?scp=79957850609&partnerID=8YFLogxK
U2 - 10.1109/ICDE.2011.5767868
DO - 10.1109/ICDE.2011.5767868
M3 - Conference contribution
AN - SCOPUS:79957850609
SN - 9781424489589
T3 - Proceedings - International Conference on Data Engineering
SP - 984
EP - 994
BT - 2011 IEEE 27th International Conference on Data Engineering, ICDE 2011
Y2 - 11 April 2011 through 16 April 2011
ER -