Efficient query evaluation techniques over large amount of distributed linked data
| Autor: | Eleftherios Kalogeros, Manolis Gergatsoulis, Matthew Damigos, Christos Nomikos |
|---|---|
| Rok vydání: | 2023 |
| Předmět: |
FOS: Computer and information sciences
Computer Science - Databases Computer Science - Distributed Parallel and Cluster Computing Hardware and Architecture Computer Science - Data Structures and Algorithms Databases (cs.DB) Data Structures and Algorithms (cs.DS) Distributed Parallel and Cluster Computing (cs.DC) Software Information Systems |
| Zdroj: | Information Systems. 115:102194 |
| ISSN: | 0306-4379 |
| DOI: | 10.1016/j.is.2023.102194 |
| Popis: | As RDF becomes more widely established and the amount of linked data is rapidly increasing, the efficient querying of large amount of data becomes a significant challenge. In this paper, we propose a family of algorithms for querying large amount of linked data in a distributed manner. These query evaluation algorithms are independent of the way the data is stored, as well as of the particular implementation of the query evaluation. We then use the MapReduce paradigm to present a distributed implementation of these algorithms and experimentally evaluate them, although the algorithms could be straightforwardly translated into other distributed processing frameworks. We also investigate and propose multiple query decomposition approaches of Basic Graph Patterns (subclass of SPARQL queries) that are used to improve the overall performance of the distributed query answering. A deep analysis of the effectiveness of these decomposition algorithms is also provided. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect