In this work, we propose a learning-based approach to select the most meaningful parameters and generate a performance model based on both the workload and the ...

Missing: Selection | Show results with:Selection

Aug 25, 2018 · Abstract. In-memory databases, just as hard drive ones, may offer hundreds of customizable settings, making the task of system tuning ...

Aug 25, 2018 · In this work, we propose a learning-based approach to select the most meaningful parameters and generate a performance model based on both the ...

We designed a workload-aware configuration tuning framework called K2vTune, which can recognize the configuration knobs of RocksDB according to the workload ...

Sep 5, 2023 · In this study, we present a configuration parameter tuning tool MMDTune+ for ArangoDB. First, the selection of configuration parameters is based on the random ...

Oct 20, 2009 · You should consider an in-memory database if: 1. The target system has data to manage, but no persistent media 2. The performance requirement simply cannot be ...

To fully realize the next generation of database clouds, we need to be able to accurately predict resource consumption and performance of a given workload.

Missing: Parameter | Show results with:Parameter

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