Abstract
RDF is an increasingly popular data model for many practical applications, leading to large volumes of RDF data; efficient RDF data management methods are crucial to allow applications to scale. We propose to demonstrate CliqueSquare, an RDF data management system built on top of a MapReduce-like infrastructure. The main technical novelty of CliqueSquare resides in its logical query optimization algorithm, guaranteed to find a logical plan as flat as possible for a given query, meaning: a plan having the smallest possible number of join operators on top of each other. CliqueSquare's ability to build flat plans allows it to take advantage of a parallel processing framework in order to shorten response times. We demonstrate loading and querying the data, with a particular focus on query optimization, and on the performance benefits of CliqueSquare's flat plans.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - International Conference on Data Engineering |
| Publisher | IEEE Computer Society |
| Pages | 1432-1435 |
| Number of pages | 4 |
| Volume | 2015-May |
| ISBN (Print) | 9781479979639 |
| DOIs | |
| Publication status | Published - 26 May 2015 |
| Event | 2015 31st IEEE International Conference on Data Engineering, ICDE 2015 - Seoul, Korea, Republic of Duration: 13 Apr 2015 → 17 Apr 2015 |
Other
| Other | 2015 31st IEEE International Conference on Data Engineering, ICDE 2015 |
|---|---|
| Country | Korea, Republic of |
| City | Seoul |
| Period | 13/4/15 → 17/4/15 |
Fingerprint
ASJC Scopus subject areas
- Information Systems
- Signal Processing
- Software
Cite this
CliqueSquare in action : Flat plans for massively parallel RDF queries. / Djahandideh, Benjamin; Goasdoué, François; Kaoudi, Zoi; Manolescu, Ioana; Quiane Ruiz, Jorge Arnulfo; Zampetakis, Stamatis.
Proceedings - International Conference on Data Engineering. Vol. 2015-May IEEE Computer Society, 2015. p. 1432-1435 7113394.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - CliqueSquare in action
T2 - Flat plans for massively parallel RDF queries
AU - Djahandideh, Benjamin
AU - Goasdoué, François
AU - Kaoudi, Zoi
AU - Manolescu, Ioana
AU - Quiane Ruiz, Jorge Arnulfo
AU - Zampetakis, Stamatis
PY - 2015/5/26
Y1 - 2015/5/26
N2 - RDF is an increasingly popular data model for many practical applications, leading to large volumes of RDF data; efficient RDF data management methods are crucial to allow applications to scale. We propose to demonstrate CliqueSquare, an RDF data management system built on top of a MapReduce-like infrastructure. The main technical novelty of CliqueSquare resides in its logical query optimization algorithm, guaranteed to find a logical plan as flat as possible for a given query, meaning: a plan having the smallest possible number of join operators on top of each other. CliqueSquare's ability to build flat plans allows it to take advantage of a parallel processing framework in order to shorten response times. We demonstrate loading and querying the data, with a particular focus on query optimization, and on the performance benefits of CliqueSquare's flat plans.
AB - RDF is an increasingly popular data model for many practical applications, leading to large volumes of RDF data; efficient RDF data management methods are crucial to allow applications to scale. We propose to demonstrate CliqueSquare, an RDF data management system built on top of a MapReduce-like infrastructure. The main technical novelty of CliqueSquare resides in its logical query optimization algorithm, guaranteed to find a logical plan as flat as possible for a given query, meaning: a plan having the smallest possible number of join operators on top of each other. CliqueSquare's ability to build flat plans allows it to take advantage of a parallel processing framework in order to shorten response times. We demonstrate loading and querying the data, with a particular focus on query optimization, and on the performance benefits of CliqueSquare's flat plans.
UR - http://www.scopus.com/inward/record.url?scp=84940888134&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84940888134&partnerID=8YFLogxK
U2 - 10.1109/ICDE.2015.7113394
DO - 10.1109/ICDE.2015.7113394
M3 - Conference contribution
SN - 9781479979639
VL - 2015-May
SP - 1432
EP - 1435
BT - Proceedings - International Conference on Data Engineering
PB - IEEE Computer Society
ER -