Using Semi-Joins to Solve Relational Queries
Journal of the ACM (JACM)
Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
Integrating Semi-Join-Reducers into State of the Art Query Processors
Proceedings of the 17th International Conference on Data Engineering
LA-WEB '03 Proceedings of the First Conference on Latin American Web Congress
A path-based relational RDF database
ADC '05 Proceedings of the 16th Australasian database conference - Volume 39
Optimizing bitmap indices with efficient compression
ACM Transactions on Database Systems (TODS)
Scalable semantic web data management using vertical partitioning
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
SPARQL basic graph pattern optimization using selectivity estimation
Proceedings of the 17th international conference on World Wide Web
Efficiently querying rdf data in triple stores
Proceedings of the 17th international conference on World Wide Web
The SPARQL Query Graph Model for Query Optimization
ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
Hexastore: sextuple indexing for semantic web data management
Proceedings of the VLDB Endowment
Column-store support for RDF data management: not all swans are white
Proceedings of the VLDB Endowment
Scalable join processing on very large RDF graphs
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
The RDF-3X engine for scalable management of RDF data
The VLDB Journal — The International Journal on Very Large Data Bases
Matrix "Bit" loaded: a scalable lightweight join query processor for RDF data
Proceedings of the 19th international conference on World wide web
YARS2: a federated repository for querying graph structured data from the web
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
x-RDF-3X: fast querying, high update rates, and consistency for RDF databases
Proceedings of the VLDB Endowment
gStore: answering SPARQL queries via subgraph matching
Proceedings of the VLDB Endowment
BRAHMS: a workbench RDF store and high performance memory system for semantic association discovery
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Delta-reasoner: a semantic web reasoner for an intelligent mobile platform
Proceedings of the 21st international conference companion on World Wide Web
Efficient data partitioning model for heterogeneous graphs in the cloud
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Editorial: Efficient incremental update and querying in AWETO RDF storage system
Data & Knowledge Engineering
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The volume of RDF data continues to grow over the past decade and many known RDF datasets have billions of triples. A grant challenge of managing this huge RDF data is how to access this big RDF data efficiently. A popular approach to addressing the problem is to build a full set of permutations of (S, P, O) indexes. Although this approach has shown to accelerate joins by orders of magnitude, the large space overhead limits the scalability of this approach and makes it heavyweight. In this paper, we present TripleBit, a fast and compact system for storing and accessing RDF data. The design of TripleBit has three salient features. First, the compact design of TripleBit reduces both the size of stored RDF data and the size of its indexes. Second, TripleBit introduces two auxiliary index structures, ID-Chunk bit matrix and ID-Predicate bit matrix, to minimize the cost of index selection during query evaluation. Third, its query processor dynamically generates an optimal execution ordering for join queries, leading to fast query execution and effective reduction on the size of intermediate results. Our experiments show that TripleBit outperforms RDF-3X, MonetDB, BitMat on LUBM, UniProt and BTC 2012 benchmark queries and it offers orders of mangnitude performance improvement for some complex join queries.