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Estatística
Título: TUNINGCHEF: AN APPROACH FOR CHOOSING THE BEST COST-BENEFIT DATABASE TUNING ACTIONS
Autor: VICTOR AUGUSTO LIMA LINS DE SOUZA
Colaborador(es): SERGIO LIFSCHITZ - Orientador
Catalogação: 29/NOV/2022 Língua(s): PORTUGUESE - BRAZIL
Tipo: TEXT Subtipo: THESIS
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/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=61428&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=61428&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.61428
Resumo:
While many research works propose a way to list a set of fine-tuning options for a given workload, only a few offer a way to help the DBA make better decisions when encountering a set of available options, especially when taking his possibilities into consideration. We propose and develop a step-by-step decision process. Given a set of fine-tuning options, we recommend a subset with good cost-benefit proportion. Enough context for the DBA accompanies the recommendation to understand its reasoning, with the possibility of letting the user build his own subset and check the expected impact. Some experimental results are also described, showing the importance of the decision step when fine tuning a database, where in a set on 50+ fine tuning actions suggested by an external tool, only 8 are considered beneficial for the a specific workload.
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