Using OLAP queries for data analysis on graph databases
Autor(a) principal: | |
---|---|
Data de Publicação: | 2017 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFPE |
dARK ID: | ark:/64986/001300000jm34 |
Texto Completo: | https://repositorio.ufpe.br/handle/123456789/43476 |
Resumo: | Graph Databases (GDB) are an alternative to traditional Relational Databases and allow a better scalability for the system, in addition to representing highly connected data in a more natural way. GDBs also support different kind of network analysis, such as cen- trality measures and community detection algorithms. Despite this, there are still no tools available in the market for multidimensional analysis in graphs, such as existing OLAP systems that operate on Relational DBs. In the academic field, there are some framework proposals that aim at the construction of a multidimensional cube composed by aggre- gate graphs, which are obtained from the combination of vertices and edges of the original graph, according to the dimensions and measures being analysed. However, most part of the researches in this area are focused on the OLAP analysis for homogeneous graphs, while the works dedicated to heterogeneous graphs require an intermediate data model in order to execute the multidimensional analysis. This project proposes a system to execute OLAP queries in a Graph Database without the need to generate an intermediate data model to do multidimensional analysis on heterogeneous graphs. The proposed system is able to answer OLAP queries using aggregate graphs obtained from the original graph, as well as execute analysis about the topology of the graph. In this work, we present experiments showing the effectiveness of the system to answer the analytical queries and some qualitative comparisons between the proposed system and existing solutions. |
id |
UFPE_5d5e9faa0cb93c82685889b96c3ffee4 |
---|---|
oai_identifier_str |
oai:repositorio.ufpe.br:123456789/43476 |
network_acronym_str |
UFPE |
network_name_str |
Repositório Institucional da UFPE |
repository_id_str |
2221 |
spelling |
CYSNEIROS, Nicolle Chaveshttp://lattes.cnpq.br/3312048097574861http://lattes.cnpq.br/1095193209251351SALGADO, Ana Carolina Brandão2022-03-22T17:21:04Z2022-03-22T17:21:04Z2017-09-01CYSNEIROS, Nicolle Chaves. Using OLAP queries for data analysis on graph databases. 2017. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Pernambuco, Recife, 2017.https://repositorio.ufpe.br/handle/123456789/43476ark:/64986/001300000jm34Graph Databases (GDB) are an alternative to traditional Relational Databases and allow a better scalability for the system, in addition to representing highly connected data in a more natural way. GDBs also support different kind of network analysis, such as cen- trality measures and community detection algorithms. Despite this, there are still no tools available in the market for multidimensional analysis in graphs, such as existing OLAP systems that operate on Relational DBs. In the academic field, there are some framework proposals that aim at the construction of a multidimensional cube composed by aggre- gate graphs, which are obtained from the combination of vertices and edges of the original graph, according to the dimensions and measures being analysed. However, most part of the researches in this area are focused on the OLAP analysis for homogeneous graphs, while the works dedicated to heterogeneous graphs require an intermediate data model in order to execute the multidimensional analysis. This project proposes a system to execute OLAP queries in a Graph Database without the need to generate an intermediate data model to do multidimensional analysis on heterogeneous graphs. The proposed system is able to answer OLAP queries using aggregate graphs obtained from the original graph, as well as execute analysis about the topology of the graph. In this work, we present experiments showing the effectiveness of the system to answer the analytical queries and some qualitative comparisons between the proposed system and existing solutions.Bancos de Dados (BDs) em Grafo são uma alternativa aos tradicionais BDs Rela- cionais e permitem uma melhor escalabilidade do sistema, além de uma maneira mais natural de representar dados altamente conectados. Os BDs em Grafo também permitem diferentes tipos de análises em grafos, como medidas de centralidade e algoritmos de de- tecção de comunidades. Apesar disso, ainda não existem ferramentas disponíveis no mer- cado para fazer análise multidimensional em grafos, como os sistemas OLAP existentes que operam sobre BDs Relacionais. No meio acadêmico, existem algumas propostas de frameworks que visam a construção de um cubo multidimensional composto por grafos agregados, obtidos a partir da combinação de nós e arestas do grafo original de acordo com as dimensões e medidas analisadas. Contudo, a maior parte das pesquisas são voltadas para a análise de grafos homogêneos, enquanto os trabalhos que se dedicam a grafos het- erogêneos realizam a análise multidimensional a partir de um modelo intermediário do dado original. Esse projeto propõe um sistema para a realização de consultas OLAP em um Banco de Dados em Grafo sem a necessidade da geração de um modelo intermediário de dados para realizar análise em grafos heterogêneos. O sistema proposto é capaz de re- sponder consultas OLAP a partir de grafos agregados extraídos do grafo original, além de também realizar análises acerca da topologia do grafo. Neste trabalho são apresentados experimentos mostrando a eficácia do sistema para responder às consultas analíticas e comparações específicas entre o sistema descrito e as soluções existentes.engUniversidade Federal de PernambucoPrograma de Pos Graduacao em Ciencia da ComputacaoUFPEBrasilAttribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessOLAPBando de dados em grafoGrafosAnálise de dadosUsing OLAP queries for data analysis on graph databasesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesismestradoreponame:Repositório Institucional da UFPEinstname:Universidade Federal de Pernambuco (UFPE)instacron:UFPEORIGINALDISSERTAÇÃO Nicolle Chaves Cysneiros.pdfDISSERTAÇÃO Nicolle Chaves Cysneiros.pdfapplication/pdf5524403https://repositorio.ufpe.br/bitstream/123456789/43476/1/DISSERTA%c3%87%c3%83O%20Nicolle%20Chaves%20Cysneiros.pdf9a56279be511b22095ae9da90c80c469MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-82142https://repositorio.ufpe.br/bitstream/123456789/43476/3/license.txt6928b9260b07fb2755249a5ca9903395MD53CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8811https://repositorio.ufpe.br/bitstream/123456789/43476/2/license_rdfe39d27027a6cc9cb039ad269a5db8e34MD52TEXTDISSERTAÇÃO Nicolle Chaves Cysneiros.pdf.txtDISSERTAÇÃO Nicolle Chaves Cysneiros.pdf.txtExtracted texttext/plain100476https://repositorio.ufpe.br/bitstream/123456789/43476/4/DISSERTA%c3%87%c3%83O%20Nicolle%20Chaves%20Cysneiros.pdf.txtd679674576a835b11d735d77bc72470bMD54THUMBNAILDISSERTAÇÃO Nicolle Chaves Cysneiros.pdf.jpgDISSERTAÇÃO Nicolle Chaves Cysneiros.pdf.jpgGenerated Thumbnailimage/jpeg1218https://repositorio.ufpe.br/bitstream/123456789/43476/5/DISSERTA%c3%87%c3%83O%20Nicolle%20Chaves%20Cysneiros.pdf.jpge33ee68e8cc47b7e103ef1e25fc9e236MD55123456789/434762022-03-23 02:14:31.802oai:repositorio.ufpe.br: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ório InstitucionalPUBhttps://repositorio.ufpe.br/oai/requestattena@ufpe.bropendoar:22212022-03-23T05:14:31Repositório Institucional da UFPE - Universidade Federal de Pernambuco (UFPE)false |
dc.title.pt_BR.fl_str_mv |
Using OLAP queries for data analysis on graph databases |
title |
Using OLAP queries for data analysis on graph databases |
spellingShingle |
Using OLAP queries for data analysis on graph databases CYSNEIROS, Nicolle Chaves OLAP Bando de dados em grafo Grafos Análise de dados |
title_short |
Using OLAP queries for data analysis on graph databases |
title_full |
Using OLAP queries for data analysis on graph databases |
title_fullStr |
Using OLAP queries for data analysis on graph databases |
title_full_unstemmed |
Using OLAP queries for data analysis on graph databases |
title_sort |
Using OLAP queries for data analysis on graph databases |
author |
CYSNEIROS, Nicolle Chaves |
author_facet |
CYSNEIROS, Nicolle Chaves |
author_role |
author |
dc.contributor.authorLattes.pt_BR.fl_str_mv |
http://lattes.cnpq.br/3312048097574861 |
dc.contributor.advisorLattes.pt_BR.fl_str_mv |
http://lattes.cnpq.br/1095193209251351 |
dc.contributor.author.fl_str_mv |
CYSNEIROS, Nicolle Chaves |
dc.contributor.advisor1.fl_str_mv |
SALGADO, Ana Carolina Brandão |
contributor_str_mv |
SALGADO, Ana Carolina Brandão |
dc.subject.por.fl_str_mv |
OLAP Bando de dados em grafo Grafos Análise de dados |
topic |
OLAP Bando de dados em grafo Grafos Análise de dados |
description |
Graph Databases (GDB) are an alternative to traditional Relational Databases and allow a better scalability for the system, in addition to representing highly connected data in a more natural way. GDBs also support different kind of network analysis, such as cen- trality measures and community detection algorithms. Despite this, there are still no tools available in the market for multidimensional analysis in graphs, such as existing OLAP systems that operate on Relational DBs. In the academic field, there are some framework proposals that aim at the construction of a multidimensional cube composed by aggre- gate graphs, which are obtained from the combination of vertices and edges of the original graph, according to the dimensions and measures being analysed. However, most part of the researches in this area are focused on the OLAP analysis for homogeneous graphs, while the works dedicated to heterogeneous graphs require an intermediate data model in order to execute the multidimensional analysis. This project proposes a system to execute OLAP queries in a Graph Database without the need to generate an intermediate data model to do multidimensional analysis on heterogeneous graphs. The proposed system is able to answer OLAP queries using aggregate graphs obtained from the original graph, as well as execute analysis about the topology of the graph. In this work, we present experiments showing the effectiveness of the system to answer the analytical queries and some qualitative comparisons between the proposed system and existing solutions. |
publishDate |
2017 |
dc.date.issued.fl_str_mv |
2017-09-01 |
dc.date.accessioned.fl_str_mv |
2022-03-22T17:21:04Z |
dc.date.available.fl_str_mv |
2022-03-22T17:21:04Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
CYSNEIROS, Nicolle Chaves. Using OLAP queries for data analysis on graph databases. 2017. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Pernambuco, Recife, 2017. |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufpe.br/handle/123456789/43476 |
dc.identifier.dark.fl_str_mv |
ark:/64986/001300000jm34 |
identifier_str_mv |
CYSNEIROS, Nicolle Chaves. Using OLAP queries for data analysis on graph databases. 2017. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Pernambuco, Recife, 2017. ark:/64986/001300000jm34 |
url |
https://repositorio.ufpe.br/handle/123456789/43476 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de Pernambuco |
dc.publisher.program.fl_str_mv |
Programa de Pos Graduacao em Ciencia da Computacao |
dc.publisher.initials.fl_str_mv |
UFPE |
dc.publisher.country.fl_str_mv |
Brasil |
publisher.none.fl_str_mv |
Universidade Federal de Pernambuco |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFPE instname:Universidade Federal de Pernambuco (UFPE) instacron:UFPE |
instname_str |
Universidade Federal de Pernambuco (UFPE) |
instacron_str |
UFPE |
institution |
UFPE |
reponame_str |
Repositório Institucional da UFPE |
collection |
Repositório Institucional da UFPE |
bitstream.url.fl_str_mv |
https://repositorio.ufpe.br/bitstream/123456789/43476/1/DISSERTA%c3%87%c3%83O%20Nicolle%20Chaves%20Cysneiros.pdf https://repositorio.ufpe.br/bitstream/123456789/43476/3/license.txt https://repositorio.ufpe.br/bitstream/123456789/43476/2/license_rdf https://repositorio.ufpe.br/bitstream/123456789/43476/4/DISSERTA%c3%87%c3%83O%20Nicolle%20Chaves%20Cysneiros.pdf.txt https://repositorio.ufpe.br/bitstream/123456789/43476/5/DISSERTA%c3%87%c3%83O%20Nicolle%20Chaves%20Cysneiros.pdf.jpg |
bitstream.checksum.fl_str_mv |
9a56279be511b22095ae9da90c80c469 6928b9260b07fb2755249a5ca9903395 e39d27027a6cc9cb039ad269a5db8e34 d679674576a835b11d735d77bc72470b e33ee68e8cc47b7e103ef1e25fc9e236 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional da UFPE - Universidade Federal de Pernambuco (UFPE) |
repository.mail.fl_str_mv |
attena@ufpe.br |
_version_ |
1815172838610436096 |