A correlation-aware data placement strategy for key-value stores
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | , |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/14988 |
Resumo: | Key-value stores hold the unprecedented bulk of the data produced by applications such as social networks. Their scalability and availability requirements often outweigh sacri cing richer data and pro- cessing models, and even elementary data consistency. Moreover, existing key-value stores have only random or order based placement strategies. In this paper we exploit arbitrary data relations easily expressed by the application to foster data locality and improve the performance of com- plex queries common in social network read-intensive workloads. We present a novel data placement strategy, supporting dynamic tags, based on multidimensional locality-preserving mappings. We compare our data placement strategy with the ones used in existing key-value stores under the workload of a typical social network appli- cation and show that the proposed correlation-aware data placement strategy o ers a major improvement on the system's overall response time and network requirements. |
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A correlation-aware data placement strategy for key-value storesPeer-to-peerDHTCloud ComputingDependabilityScience & TechnologyKey-value stores hold the unprecedented bulk of the data produced by applications such as social networks. Their scalability and availability requirements often outweigh sacri cing richer data and pro- cessing models, and even elementary data consistency. Moreover, existing key-value stores have only random or order based placement strategies. In this paper we exploit arbitrary data relations easily expressed by the application to foster data locality and improve the performance of com- plex queries common in social network read-intensive workloads. We present a novel data placement strategy, supporting dynamic tags, based on multidimensional locality-preserving mappings. We compare our data placement strategy with the ones used in existing key-value stores under the workload of a typical social network appli- cation and show that the proposed correlation-aware data placement strategy o ers a major improvement on the system's overall response time and network requirements.SpringerUniversidade do MinhoVilaça, RicardoOliveira, Rui Carlos Mendes dePereira, José, 1973-20112011-01-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/14988eng97836422138610302-974310.1007/978-3-642-21387-8_17info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-05-11T04:31:58Zoai:repositorium.sdum.uminho.pt:1822/14988Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-11T04:31:58Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
A correlation-aware data placement strategy for key-value stores |
title |
A correlation-aware data placement strategy for key-value stores |
spellingShingle |
A correlation-aware data placement strategy for key-value stores Vilaça, Ricardo Peer-to-peer DHT Cloud Computing Dependability Science & Technology |
title_short |
A correlation-aware data placement strategy for key-value stores |
title_full |
A correlation-aware data placement strategy for key-value stores |
title_fullStr |
A correlation-aware data placement strategy for key-value stores |
title_full_unstemmed |
A correlation-aware data placement strategy for key-value stores |
title_sort |
A correlation-aware data placement strategy for key-value stores |
author |
Vilaça, Ricardo |
author_facet |
Vilaça, Ricardo Oliveira, Rui Carlos Mendes de Pereira, José, 1973- |
author_role |
author |
author2 |
Oliveira, Rui Carlos Mendes de Pereira, José, 1973- |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Vilaça, Ricardo Oliveira, Rui Carlos Mendes de Pereira, José, 1973- |
dc.subject.por.fl_str_mv |
Peer-to-peer DHT Cloud Computing Dependability Science & Technology |
topic |
Peer-to-peer DHT Cloud Computing Dependability Science & Technology |
description |
Key-value stores hold the unprecedented bulk of the data produced by applications such as social networks. Their scalability and availability requirements often outweigh sacri cing richer data and pro- cessing models, and even elementary data consistency. Moreover, existing key-value stores have only random or order based placement strategies. In this paper we exploit arbitrary data relations easily expressed by the application to foster data locality and improve the performance of com- plex queries common in social network read-intensive workloads. We present a novel data placement strategy, supporting dynamic tags, based on multidimensional locality-preserving mappings. We compare our data placement strategy with the ones used in existing key-value stores under the workload of a typical social network appli- cation and show that the proposed correlation-aware data placement strategy o ers a major improvement on the system's overall response time and network requirements. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011 2011-01-01T00:00:00Z |
dc.type.driver.fl_str_mv |
conference paper |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/14988 |
url |
http://hdl.handle.net/1822/14988 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
9783642213861 0302-9743 10.1007/978-3-642-21387-8_17 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
mluisa.alvim@gmail.com |
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1817544340601307136 |