Scalable SPARQL querying of large RDF graphs
نویسندگان
چکیده
منابع مشابه
Scalable SPARQL Querying of Large RDF Graphs
The generation of RDF data has accelerated to the point where many data sets need to be partitioned across multiple machines in order to achieve reasonable performance when querying the data. Although tremendous progress has been made in the Semantic Web community for achieving high performance data management on a single node, current solutions that allow the data to be partitioned across mult...
متن کاملBitMat – Scalable Indexing and Querying of Large RDF Graphs
The growing size of Semantic Web data expressed in the form of Resource Description Framework (RDF) has made it necessary to develop effective ways of storing this data to save space and to query it in a scalable manner. SPARQL – the query language for RDF data – closely follows SQL syntax. As a natural consequence most of the RDF storage and querying engines are based on modern database storag...
متن کاملQuerying Distributed RDF Data Sources with SPARQL
Integrated access to multiple distributed and autonomous RDF data sources is a key challenge for many semantic web applications. As a reaction to this challenge, SPARQL, the W3C Recommendation for an RDF query language, supports querying of multiple RDF graphs. However, the current standard does not provide transparent query federation, which makes query formulation hard and lengthy. Furthermor...
متن کاملS2RDF: RDF Querying with SPARQL on Spark
RDF has become very popular for semantic data publishing due to its flexible and universal graph-like data model. Thus, the ever-increasing size of RDF data collections raises the need for scalable distributed approaches. We endorse the usage of existing infrastructures for Big Data processing like Hadoop for this purpose. Yet, SPARQL query performance is a major challenge as Hadoop is not inte...
متن کاملMapReduce-based Solutions for Scalable SPARQL Querying
The use of RDF to expose semantic data on the Web has seen a dramatic increase over the last few years. Nowadays, RDF datasets are so big and interconnected that, in fact, classical mono-node solutions present significant scalability problems when trying to manage big semantic data. MapReduce, a standard framework for distributed processing of great quantities of data, is earning a place among ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proceedings of the VLDB Endowment
سال: 2011
ISSN: 2150-8097
DOI: 10.14778/3402707.3402747