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BLUTune: Tuning Up IBM Db2 with ML | IEEE Conference Publication | IEEE Xplore

Abstract:

Nowadays, data systems, including IBM Db2 have dozens of knobs (configuration parameters). These knobs significantly affect the runtime of queries. We present the design ...Show More

Abstract:

Nowadays, data systems, including IBM Db2 have dozens of knobs (configuration parameters). These knobs significantly affect the runtime of queries. We present the design of and a demonstration plan for a query-informed, efficient tuning system, BLUTune, which utilizes deep reinforcement learning to tune configurations. Using synthetic and real workloads, we demonstrate how BLUTune can help users to understand the semantics of analytical queries, including their execution plans, and interactively tune data systems to improve performance.
Date of Conference: 03-07 April 2023
Date Added to IEEE Xplore: 26 July 2023
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ISSN Information:

Conference Location: Anaheim, CA, USA
Citations are not available for this document.

I. Introduction

Business data systems, including IBM Db2 have dozens of configuration parameters called knobs. Tuning the knobs have a huge influence on the performance of analytical query workloads. Configuration parameters control the accessible memory, including the sort-heap and buffer-pool, parallelism degree and adjusting the level of optimization.

Cites in Papers - |

Cites in Papers - Other Publishers (1)

1.
Alexander Bianchi, Andrew Chai, Vincent Corvinelli, Parke Godfrey, Jarek Szlichta, Calisto Zuzarte, "Db2une: Tuning Under Pressure via Deep Learning", Proceedings of the VLDB Endowment, vol.17, no.12, pp.3855, 2024.

References

References is not available for this document.