Autonomic Combination and Selection of Tuning Actions

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Standard

Autonomic Combination and Selection of Tuning Actions. / Oliveira, Rafael Pereira De; Baião, Fernanda; Machado, Javam; Almeida, Ana Carolina; Lifschitz, Sérgio.

Proceedings of the 37thBrazilian Symposium on Data B. Sociedade Brasileira de Computacao, 2022. p. 39-51 (BRAZILIAN SYMPOSIUM ON DATABASES, Vol. 37).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Harvard

Oliveira, RPD, Baião, F, Machado, J, Almeida, AC & Lifschitz, S 2022, Autonomic Combination and Selection of Tuning Actions. in Proceedings of the 37thBrazilian Symposium on Data B. Sociedade Brasileira de Computacao, BRAZILIAN SYMPOSIUM ON DATABASES, vol. 37, pp. 39-51, 37th Brazilian Symposium on Data Bases, Buzios, Brazil, 19/09/2022. https://doi.org/10.5753/sbbd.2022.225212

APA

Oliveira, R. P. D., Baião, F., Machado, J., Almeida, A. C., & Lifschitz, S. (2022). Autonomic Combination and Selection of Tuning Actions. In Proceedings of the 37thBrazilian Symposium on Data B (pp. 39-51). Sociedade Brasileira de Computacao. BRAZILIAN SYMPOSIUM ON DATABASES Vol. 37 https://doi.org/10.5753/sbbd.2022.225212

Vancouver

Oliveira RPD, Baião F, Machado J, Almeida AC, Lifschitz S. Autonomic Combination and Selection of Tuning Actions. In Proceedings of the 37thBrazilian Symposium on Data B. Sociedade Brasileira de Computacao. 2022. p. 39-51. (BRAZILIAN SYMPOSIUM ON DATABASES, Vol. 37). https://doi.org/10.5753/sbbd.2022.225212

Author

Oliveira, Rafael Pereira De ; Baião, Fernanda ; Machado, Javam ; Almeida, Ana Carolina ; Lifschitz, Sérgio. / Autonomic Combination and Selection of Tuning Actions. Proceedings of the 37thBrazilian Symposium on Data B. Sociedade Brasileira de Computacao, 2022. pp. 39-51 (BRAZILIAN SYMPOSIUM ON DATABASES, Vol. 37).

Bibtex

@inproceedings{c001efb73e5d41ef8d3190e2b936d00b,
title = "Autonomic Combination and Selection of Tuning Actions",
abstract = "Combining database tuning actions has neither a precise formulation nor a formal approach to solving it. It is a complex and relevant problem in database research, both for the DBA manual solutions and automatic ones using specialized software. This work proposes an automated method for generating and selecting combined tuning solutions for relational databases. It addresses how to mix solutions while still preserving both technological constraints and available computational resources. The results show that our technique can produce more efficient combined solutions than independent local solutions.",
author = "Oliveira, {Rafael Pereira De} and Fernanda Bai{\~a}o and Javam Machado and Almeida, {Ana Carolina} and S{\'e}rgio Lifschitz",
year = "2022",
doi = "10.5753/sbbd.2022.225212",
language = "English",
series = "BRAZILIAN SYMPOSIUM ON DATABASES",
publisher = "Sociedade Brasileira de Computacao",
pages = "39--51",
booktitle = "Proceedings of the 37thBrazilian Symposium on Data B",
address = "Brazil",
note = "null ; Conference date: 19-09-2022 Through 23-09-2022",

}

RIS

TY - GEN

T1 - Autonomic Combination and Selection of Tuning Actions

AU - Oliveira, Rafael Pereira De

AU - Baião, Fernanda

AU - Machado, Javam

AU - Almeida, Ana Carolina

AU - Lifschitz, Sérgio

PY - 2022

Y1 - 2022

N2 - Combining database tuning actions has neither a precise formulation nor a formal approach to solving it. It is a complex and relevant problem in database research, both for the DBA manual solutions and automatic ones using specialized software. This work proposes an automated method for generating and selecting combined tuning solutions for relational databases. It addresses how to mix solutions while still preserving both technological constraints and available computational resources. The results show that our technique can produce more efficient combined solutions than independent local solutions.

AB - Combining database tuning actions has neither a precise formulation nor a formal approach to solving it. It is a complex and relevant problem in database research, both for the DBA manual solutions and automatic ones using specialized software. This work proposes an automated method for generating and selecting combined tuning solutions for relational databases. It addresses how to mix solutions while still preserving both technological constraints and available computational resources. The results show that our technique can produce more efficient combined solutions than independent local solutions.

U2 - 10.5753/sbbd.2022.225212

DO - 10.5753/sbbd.2022.225212

M3 - Article in proceedings

T3 - BRAZILIAN SYMPOSIUM ON DATABASES

SP - 39

EP - 51

BT - Proceedings of the 37thBrazilian Symposium on Data B

PB - Sociedade Brasileira de Computacao

Y2 - 19 September 2022 through 23 September 2022

ER -

ID: 340702048