TuningChef: an approach for choosing the best cost-benefit database tuning actions

  • Victor Augusto Lima Lins de Souza Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio)
  • Sérgio Lifschitz Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio)


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 the most cost-benefit subset. 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. We show some experimental results on actual database systems that further explain our approach and solution.

Palavras-chave: RDBMS, tuning, database, materialized view


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SOUZA, Victor Augusto Lima Lins de; LIFSCHITZ, Sérgio. TuningChef: an approach for choosing the best cost-benefit database tuning actions. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 37. , 2022, Búzios. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2022 . p. 391-396. ISSN 2763-8979. DOI: https://doi.org/10.5753/sbbd.2022.226196.