Arquitetura dinâmica para o balanceamento de réplicas em sistemas de arquivos distribuídos

Detalhes bibliográficos
Autor(a) principal: Fazul, Rhauani Weber Aita
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Manancial - Repositório Digital da UFSM
Texto Completo: http://repositorio.ufsm.br/handle/1/26470
Resumo: Distributed file systems are essential to support applications that handle large volumes of data. One of the most widely used file systems is the HDFS, Apache Hadoop’s Distributed File System. Data replication, which is at the core of the HDFS storage model, is essential for fault tolerance and performance since the placement of the data across the cluster directly affects replica balancing and data locality. As new data is loaded into the system, it is common for the distribution of the replicas among the nodes to become unbalanced. HDFS Balancer is the official solution for data balancing by rearranging the replicas already stored in the cluster. Nevertheless, its current balancing policy does not address the characteristics and specific needs of the applications during data rearrangement. Besides that, it is up to the system administrator to monitor the HDFS status and, when considered necessary, run the balancer daemon, which creates a dependency that is inadequate and inefficient in many situations. To address these limitations, this work presents DARB, a dynamic architecture that promotes reactive and proactive replica balancing. The reactive strategy arises from the PRBP, a customized and prioritized replica balancing policy for the HDFSBalancer. The PRBP is based on an adaptable and configurable system of priorities, from which association rules were defined to allow the use of multiple priorities simultaneously. Along with the rules, a set of usage guidelines has been formalized and evaluated through practical experiments, which validated the behavior and applicability of the PRBP. The proactive strategy of DARB, in contrast, consists of an event-driven strategy to make the replica balancing process in HDFS transparent. To this end, a metrics observation model and a structure were created to automatically determine when corrective actions should be taken and trigger the balancing process in the file system based on standardized trigger events. The evaluation results reinforce that the proposed solution removes the need for manual configuration and utilization of the HDFS Balancer while actively acting to keep the cluster balanced taking into account performance, reliability, and data availability perspectives. In this way, DARB presents itself as a specialized solution, flexibilizing the balancing process and introducing to HDFS the concept of context-aware replica balancing.
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spelling 2022-10-13T18:58:56Z2022-10-13T18:58:56Z2022-09-28http://repositorio.ufsm.br/handle/1/26470Distributed file systems are essential to support applications that handle large volumes of data. One of the most widely used file systems is the HDFS, Apache Hadoop’s Distributed File System. Data replication, which is at the core of the HDFS storage model, is essential for fault tolerance and performance since the placement of the data across the cluster directly affects replica balancing and data locality. As new data is loaded into the system, it is common for the distribution of the replicas among the nodes to become unbalanced. HDFS Balancer is the official solution for data balancing by rearranging the replicas already stored in the cluster. Nevertheless, its current balancing policy does not address the characteristics and specific needs of the applications during data rearrangement. Besides that, it is up to the system administrator to monitor the HDFS status and, when considered necessary, run the balancer daemon, which creates a dependency that is inadequate and inefficient in many situations. To address these limitations, this work presents DARB, a dynamic architecture that promotes reactive and proactive replica balancing. The reactive strategy arises from the PRBP, a customized and prioritized replica balancing policy for the HDFSBalancer. The PRBP is based on an adaptable and configurable system of priorities, from which association rules were defined to allow the use of multiple priorities simultaneously. Along with the rules, a set of usage guidelines has been formalized and evaluated through practical experiments, which validated the behavior and applicability of the PRBP. The proactive strategy of DARB, in contrast, consists of an event-driven strategy to make the replica balancing process in HDFS transparent. To this end, a metrics observation model and a structure were created to automatically determine when corrective actions should be taken and trigger the balancing process in the file system based on standardized trigger events. The evaluation results reinforce that the proposed solution removes the need for manual configuration and utilization of the HDFS Balancer while actively acting to keep the cluster balanced taking into account performance, reliability, and data availability perspectives. In this way, DARB presents itself as a specialized solution, flexibilizing the balancing process and introducing to HDFS the concept of context-aware replica balancing.Sistemas de arquivos distribuídos são essenciais para suportar aplicações que lidam com grandes volumes de dados. Um dos sistemas mais utilizados é o HDFS, o sistema de arquivos distribuído do Apache Hadoop. A replicação de dados, que é o elemento central do modelo de armazenamento do HDFS, é essencial para a tolerância a falhas e o desempenho, sendo que o posicionamento das réplicas no cluster afeta diretamente o balanceamento de réplicas e a localidade dos dados. À medida que novos dados são escritos no sistema de arquivos, é comum que a distribuição das réplicas entre os nodos fique desequilibrada. O HDFS Balancer é a solução oficial para o balanceamento de dados por meio do rearranjo das réplicas já armazenadas no cluster. No entanto, sua política de operação atual não considera as características e necessidades específicas das aplicações. Além disso, cabe ao administrador monitorar o estado do HDFS e, quando julgar necessário, executar o balanceador, o que cria uma dependência manual e ineficiente em muitas situações. Para endereçar tais limitações, este trabalho apresenta a DARB, uma arquitetura dinâmica que promove o balanceamento reativo e proativo. Para a parte reativa, foi desenvolvida a PRBP, uma política personalizada com base em prioridades para o HDFS Balancer. A PRBP é formada por um sistema de prioridades adaptável e configurável, a partir do qual foram definidas regras de associação que permitem o uso de múltiplas prioridades em simultâneo. Em conjunto com as regras, guidelines de uso foram formalizadas e avaliadas experimentalmente, validando o comportamento e a aplicabilidade da PRBP. Já para a parte proativa da DARB, foi desenvolvida uma estratégia orientada a eventos que visa tornar transparente o processo de balanceamento de réplicas no HDFS. Para isso, criou-se um modelo de observação de métricas e uma estrutura que, por meio de eventos de disparo, determina automaticamente quando ações corretivas devem ser tomadas no sistema de arquivos. Os resultados da avaliação reforçam que a solução proposta remove a necessidade de configuração e uso manual do HDFS Balancer, enquanto atua ativamente para manter o cluster em umestadobalanceado emproldeperspectivas de desempenho, confiabilidade e disponibilidade dos dados. Desse modo, a DARB apresenta-se como uma solução especializada, flexibilizando o processo de balanceamento e introduzindo ao HDFS o conceito de balanceamento de réplicas sensível ao contexto.Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPqporUniversidade Federal de Santa MariaCentro de TecnologiaPrograma de Pós-Graduação em Ciência da ComputaçãoUFSMBrasilCiência da ComputaçãoAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessArquitetura dinâmicaPolítica de balanceamentoBalanceamento de réplicasReplicação de dadosTolerância a falhasSistemas de arquivos distribuídosDynamic architectureBalancing policyReplica balancingData replicationFault toleranceDistributed file systemsCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAOArquitetura dinâmica para o balanceamento de réplicas em sistemas de arquivos distribuídosDynamic architecture for replica balancing in distributed file systemsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisBarcelos, Patrícia Pitthan de Araújohttp://lattes.cnpq.br/6069105173950277Lima, João Vicente FerreiraMendizabal, Odorico Machadohttp://lattes.cnpq.br/5175618357450515Fazul, Rhauani Weber Aita100300000007600600600600600a421e37e-ac28-4452-9943-e257a19343cac8b2ac4b-3da3-42ec-9d1e-e5f1ef8070fbaec00059-8729-40bd-b989-bf07fcb3bdbdf919cfa2-8dac-4a9d-a070-e0819e7f3594reponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMLICENSElicense.txtlicense.txttext/plain; charset=utf-816http://repositorio.ufsm.br/bitstream/1/26470/3/license.txtf8fcb28efb1c8cf0dc096bec902bf4c4MD53ORIGINALDIS_PPGCC_2022_AITA_RHAUANI.pdfDIS_PPGCC_2022_AITA_RHAUANI.pdfDissertação de mestradoapplication/pdf927277http://repositorio.ufsm.br/bitstream/1/26470/1/DIS_PPGCC_2022_AITA_RHAUANI.pdf83e311e892f70ffd491c327fbf483db3MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805http://repositorio.ufsm.br/bitstream/1/26470/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD521/264702022-10-13 15:58:56.862oai:repositorio.ufsm.br:1/26470Q3JlYXRpdmUgQ29tbW9ucw==Repositório Institucionalhttp://repositorio.ufsm.br/PUBhttp://repositorio.ufsm.br/oai/requestopendoar:39132022-10-13T18:58:56Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)false
dc.title.por.fl_str_mv Arquitetura dinâmica para o balanceamento de réplicas em sistemas de arquivos distribuídos
dc.title.alternative.eng.fl_str_mv Dynamic architecture for replica balancing in distributed file systems
title Arquitetura dinâmica para o balanceamento de réplicas em sistemas de arquivos distribuídos
spellingShingle Arquitetura dinâmica para o balanceamento de réplicas em sistemas de arquivos distribuídos
Fazul, Rhauani Weber Aita
Arquitetura dinâmica
Política de balanceamento
Balanceamento de réplicas
Replicação de dados
Tolerância a falhas
Sistemas de arquivos distribuídos
Dynamic architecture
Balancing policy
Replica balancing
Data replication
Fault tolerance
Distributed file systems
CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
title_short Arquitetura dinâmica para o balanceamento de réplicas em sistemas de arquivos distribuídos
title_full Arquitetura dinâmica para o balanceamento de réplicas em sistemas de arquivos distribuídos
title_fullStr Arquitetura dinâmica para o balanceamento de réplicas em sistemas de arquivos distribuídos
title_full_unstemmed Arquitetura dinâmica para o balanceamento de réplicas em sistemas de arquivos distribuídos
title_sort Arquitetura dinâmica para o balanceamento de réplicas em sistemas de arquivos distribuídos
author Fazul, Rhauani Weber Aita
author_facet Fazul, Rhauani Weber Aita
author_role author
dc.contributor.advisor1.fl_str_mv Barcelos, Patrícia Pitthan de Araújo
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/6069105173950277
dc.contributor.referee1.fl_str_mv Lima, João Vicente Ferreira
dc.contributor.referee2.fl_str_mv Mendizabal, Odorico Machado
dc.contributor.authorLattes.fl_str_mv http://lattes.cnpq.br/5175618357450515
dc.contributor.author.fl_str_mv Fazul, Rhauani Weber Aita
contributor_str_mv Barcelos, Patrícia Pitthan de Araújo
Lima, João Vicente Ferreira
Mendizabal, Odorico Machado
dc.subject.por.fl_str_mv Arquitetura dinâmica
Política de balanceamento
Balanceamento de réplicas
Replicação de dados
Tolerância a falhas
Sistemas de arquivos distribuídos
topic Arquitetura dinâmica
Política de balanceamento
Balanceamento de réplicas
Replicação de dados
Tolerância a falhas
Sistemas de arquivos distribuídos
Dynamic architecture
Balancing policy
Replica balancing
Data replication
Fault tolerance
Distributed file systems
CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
dc.subject.eng.fl_str_mv Dynamic architecture
Balancing policy
Replica balancing
Data replication
Fault tolerance
Distributed file systems
dc.subject.cnpq.fl_str_mv CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
description Distributed file systems are essential to support applications that handle large volumes of data. One of the most widely used file systems is the HDFS, Apache Hadoop’s Distributed File System. Data replication, which is at the core of the HDFS storage model, is essential for fault tolerance and performance since the placement of the data across the cluster directly affects replica balancing and data locality. As new data is loaded into the system, it is common for the distribution of the replicas among the nodes to become unbalanced. HDFS Balancer is the official solution for data balancing by rearranging the replicas already stored in the cluster. Nevertheless, its current balancing policy does not address the characteristics and specific needs of the applications during data rearrangement. Besides that, it is up to the system administrator to monitor the HDFS status and, when considered necessary, run the balancer daemon, which creates a dependency that is inadequate and inefficient in many situations. To address these limitations, this work presents DARB, a dynamic architecture that promotes reactive and proactive replica balancing. The reactive strategy arises from the PRBP, a customized and prioritized replica balancing policy for the HDFSBalancer. The PRBP is based on an adaptable and configurable system of priorities, from which association rules were defined to allow the use of multiple priorities simultaneously. Along with the rules, a set of usage guidelines has been formalized and evaluated through practical experiments, which validated the behavior and applicability of the PRBP. The proactive strategy of DARB, in contrast, consists of an event-driven strategy to make the replica balancing process in HDFS transparent. To this end, a metrics observation model and a structure were created to automatically determine when corrective actions should be taken and trigger the balancing process in the file system based on standardized trigger events. The evaluation results reinforce that the proposed solution removes the need for manual configuration and utilization of the HDFS Balancer while actively acting to keep the cluster balanced taking into account performance, reliability, and data availability perspectives. In this way, DARB presents itself as a specialized solution, flexibilizing the balancing process and introducing to HDFS the concept of context-aware replica balancing.
publishDate 2022
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dc.date.issued.fl_str_mv 2022-09-28
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http://creativecommons.org/licenses/by-nc-nd/4.0/
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dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
Centro de Tecnologia
dc.publisher.program.fl_str_mv Programa de Pós-Graduação em Ciência da Computação
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dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv Ciência da Computação
publisher.none.fl_str_mv Universidade Federal de Santa Maria
Centro de Tecnologia
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