Storage and Retrieval of Large RDF Graph Using Hadoop and MapReduce

被引：0

作者：

Husain, Mohammad Farhan ^{[1
]}

Doshi, Pankil ^{[1
]}

Khan, Latifur ^{[1
]}

Thuraisingham, Bhavani ^{[1
]}

机构：

[1] Univ Texas Dallas, Dallas, TX 75080 USA

来源：

CLOUD COMPUTING, PROCEEDINGS | 2009年 / 5931卷

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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(1) to store and retrieve large number of RDF(2) triples. We describe our schema to store RDF data in Hadoop Distribute File System. We also present our algorithms to answer a SPARQL(3) 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.

引用

页码：680 / 686

页数：7

共 50 条

[41] RC4 in Hadoop Security using MapReduce
Jayan, Anandu
Upadhyay, Bhargavi R.
2017 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE IN DATA SCIENCE (ICCIDS), 2017,
[42] Parallel computation of information gain using Hadoop and MapReduce
Zdravevski, Eftim
Lameski, Petre
Kulakov, Andrea
Filiposka, Sonja
Trajanov, Dimitar
Jakimovski, Boro
PROCEEDINGS OF THE 2015 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS, 2015, 5 : 181 - 192
[43] Parallelization of Vertical Search Engine using Hadoop and MapReduce
Pasari, Rajat
Chaudhari, Vaibhav
Borkar, Atharva
Joshi, Amit
INTERNATIONAL CONFERENCE ON ADVANCES IN INFORMATION COMMUNICATION TECHNOLOGY & COMPUTING, 2016, 2016,
[44] Sentiment analysis using semantic similarity and Hadoop MapReduce
Madani, Youness
Erritali, Mohammed
Bengourram, Jamaa
KNOWLEDGE AND INFORMATION SYSTEMS, 2019, 59 (02) : 413 - 436
[45] MapReduce Model of Improved K-Means Clustering Algorithm Using Hadoop MapReduce
Akthar, Nadeem
Ahamad, Mohd Vasim
Ahmad, Shahbaaz
2016 SECOND INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE & COMMUNICATION TECHNOLOGY (CICT), 2016, : 192 - 198
[46] Hadoop-EDF: Large-scale Distributed Processing of Electrophysiological Signal Data in Hadoop MapReduce
Wu, Yuanyuan
Li, Xiaojin
Liu, Jinze
Cui, Licong
2019 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM), 2019, : 2265 - 2271
[47] An Entity Based RDF Indexing Schema Using Hadoop And HBase
Abiri, Fateme
Kahani, Mohsen
Zarinkalam, Fatane
2014 4TH INTERNATIONAL CONFERENCE ON COMPUTER AND KNOWLEDGE ENGINEERING (ICCKE), 2014, : 68 - 73
[48] Secured Geospatial Data Storage and Retrieval using Spatial Hadoop Framework in Cloud Environment
Karthi, S.
Prabu, S.
2017 SECOND INTERNATIONAL CONFERENCE ON RECENT TRENDS AND CHALLENGES IN COMPUTATIONAL MODELS (ICRTCCM), 2017, : 73 - 76
[49] Large scale RDF storage solutions evaluation
Stantic, Bela
Bock, Juergen
Astrova, Irina
ICSOFT 2007: PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON SOFTWARE AND DATA TECHNOLOGIES, VOL ISDM/WSEHST/DC, 2007, : 103 - +
[50] Design of Large-scale Content-based Recommender System using Hadoop MapReduce Framework
Saravanan, S.
2015 EIGHTH INTERNATIONAL CONFERENCE ON CONTEMPORARY COMPUTING (IC3), 2015, : 302 - 307

← 1 2 3 4 5 →