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TRABALHOS DE FIM DE CURSO @PUC-Rio
Consulta aos Conteúdos
Estatística
Título: AN INFRASTRUCTURE FOR TEACHING THE MAPREDUCE ARCHITECTURE IN DISTRIBUTED SYSTEMS DISCIPLINES
Autor(es): ELAINE CRISTINA FERREIRA DOS SANTOS
Colaborador(es): NOEMI DE LA ROCQUE RODRIGUEZ - Orientador
Catalogação: 01/SET/2022 Língua(s): PORTUGUESE - BRAZIL
Tipo: TEXT Subtipo: SENIOR PROJECT
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/TFCs/consultas/conteudo.php?strSecao=resultado&nrSeq=60429@1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/TFCs/consultas/conteudo.php?strSecao=resultado&nrSeq=60429@2
DOI: https://doi.org/10.17771/PUCRio.acad.60429
Resumo:
This project aims to create two frameworks, a local and a distributed, to familiarize students of courses on distributed systems with MapReduce and the Go programming language. The framework assumes the use of goroutines for the parallel local processing and the remote procedure calls (RPC) for the distributed parallel process. As examples of applications we used word counting, inverted index and movie statistics, with databases using texts from Machado de Assis and a table of data about movies and series from the streaming platform Netflix. For the local case we prepared a MapReduce sequential for the case of word counting, and for the distributed (RPC) we prepared a simple call of servers ready, to use as reference.
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