Storage and Retrieval of Large RDF Graph Using Hadoop and MapReduce

Autor:	Bhavani Thuraisingham, Pankil Doshi, Mohammad Farhan Husain, Latifur Khan
Rok vydání:	2009
Předmět:	Database Computer science RDF Schema InformationSystems_DATABASEMANAGEMENT computer.file_format Linked data computer.software_genre RDF/XML Schema (psychology) SPARQL Semantic Web Stack RDF computer Semantic Web
Zdroj:	Lecture Notes in Computer Science ISBN: 9783642106644 CloudCom
DOI:	10.1007/978-3-642-10665-1_72
Popis:	Handling huge amount of data scalably is a matter of concern for a long time. Same is true for semantic web data. Current semantic web frameworks lack this ability. In this paper, we describe a framework that we built using Hadoop to store and retrieve large number of RDF triples. We describe our schema to store RDF data in Hadoop Distribute File System. We also present our algorithms to answer a SPARQL query. We make use of Hadoop's MapReduce framework to actually answer the queries. Our results reveal that we can store huge amount of semantic web data in Hadoop clusters built mostly by cheap commodity class hardware and still can answer queries fast enough. We conclude that ours is a scalable framework, able to handle large amount of RDF data efficiently.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::5f24b049a1223ec02ddddaf606febe47 https://doi.org/10.1007/978-3-642-10665-1_72 Zobrazit plný text záznamu