Paper Info
Title
Distributed Processing of Generalized Graph-Pattern Queries in SPARQL 1.1.
Abstract
We propose an efficient and scalable architecture for processing generalized graph-pattern queries as they are specified by the current W3C recommendation of the SPARQL 1.1 Query Language component. Specifically, the class of queries we consider consists of sets of SPARQL triple patterns with labeled property paths. From a relational perspective, this class resolves to conjunctive queries of relational joins with additional graph-reachability predicates. For the scalable, i.e., distributed, processing of this kind of queries over very large RDF collections, we develop a suitable partitioning and indexing scheme, which allows us to shard the RDF triples over an entire cluster of compute nodes and to process an incoming SPARQL query over all of the relevant graph partitions (and thus compute nodes) in parallel. Unlike most prior works in this field, we specifically aim at the unified optimization and distributed processing of queries consisting of both relational joins and graph-reachability predicates. All communication among the compute nodes is established via a proprietary, asynchronous communication protocol based on the Message Passing Interface.
Year
Venue
Field
2016
arXiv: Databases
Data mining,Joins,Query language,Computer science,Search engine indexing,Theoretical computer science,SPARQL,Message Passing Interface,RDF,Distributed computing,Conjunctive query,Database,Scalability
DocType
Volume
Citations 
Journal
abs/1609.05293
0
PageRank 
References 
Authors
0.34
3
2
Name
Order
Citations
PageRank
Sairam Gurajada11187.83
Martin Theobald2147472.06