Automatic configuration of the Cassandra database using irace
Database systems play a central role in modern data-centered applications. Their performance is thus a key factor in the efficiency of data processing pipelines. Modern database systems expose several parameters that users and database administrators can configure to tailor the database settings to...
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| Vydáno v: | PeerJ. Computer science Ročník 7; s. e634 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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05.08.2021
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| ISSN: | 2376-5992, 2376-5992 |
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| Abstract | Database systems play a central role in modern data-centered applications. Their performance is thus a key factor in the efficiency of data processing pipelines. Modern database systems expose several parameters that users and database administrators can configure to tailor the database settings to the specific application considered. While this task has traditionally been performed manually, in the last years several methods have been proposed to automatically find the best parameter configuration for a database. Many of these methods, however, use statistical models that require high amounts of data and fail to represent all the factors that impact the performance of a database, or implement complex algorithmic solutions. In this work we study the potential of a simple model-free general-purpose configuration tool to automatically find the best parameter configuration of a database. We use the irace configurator to automatically find the best parameter configuration for the Cassandra NoSQL database using the YCBS benchmark under different scenarios. We establish a reliable experimental setup and obtain speedups of up to 30% over the default configuration in terms of throughput, and we provide an analysis of the configurations obtained. |
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| AbstractList | Database systems play a central role in modern data-centered applications. Their performance is thus a key factor in the efficiency of data processing pipelines. Modern database systems expose several parameters that users and database administrators can configure to tailor the database settings to the specific application considered. While this task has traditionally been performed manually, in the last years several methods have been proposed to automatically find the best parameter configuration for a database. Many of these methods, however, use statistical models that require high amounts of data and fail to represent all the factors that impact the performance of a database, or implement complex algorithmic solutions. In this work we study the potential of a simple model-free general-purpose configuration tool to automatically find the best parameter configuration of a database. We use the irace configurator to automatically find the best parameter configuration for the Cassandra NoSQL database using the YCBS benchmark under different scenarios. We establish a reliable experimental setup and obtain speedups of up to 30% over the default configuration in terms of throughput, and we provide an analysis of the configurations obtained. Database systems play a central role in modern data-centered applications. Their performance is thus a key factor in the efficiency of data processing pipelines. Modern database systems expose several parameters that users and database administrators can configure to tailor the database settings to the specific application considered. While this task has traditionally been performed manually, in the last years several methods have been proposed to automatically find the best parameter configuration for a database. Many of these methods, however, use statistical models that require high amounts of data and fail to represent all the factors that impact the performance of a database, or implement complex algorithmic solutions. In this work we study the potential of a simple model-free general-purpose configuration tool to automatically find the best parameter configuration of a database. We use the irace configurator to automatically find the best parameter configuration for the Cassandra NoSQL database using the YCBS benchmark under different scenarios. We establish a reliable experimental setup and obtain speedups of up to 30% over the default configuration in terms of throughput, and we provide an analysis of the configurations obtained.Database systems play a central role in modern data-centered applications. Their performance is thus a key factor in the efficiency of data processing pipelines. Modern database systems expose several parameters that users and database administrators can configure to tailor the database settings to the specific application considered. While this task has traditionally been performed manually, in the last years several methods have been proposed to automatically find the best parameter configuration for a database. Many of these methods, however, use statistical models that require high amounts of data and fail to represent all the factors that impact the performance of a database, or implement complex algorithmic solutions. In this work we study the potential of a simple model-free general-purpose configuration tool to automatically find the best parameter configuration of a database. We use the irace configurator to automatically find the best parameter configuration for the Cassandra NoSQL database using the YCBS benchmark under different scenarios. We establish a reliable experimental setup and obtain speedups of up to 30% over the default configuration in terms of throughput, and we provide an analysis of the configurations obtained. |
| ArticleNumber | e634 |
| Audience | Academic |
| Author | Franzin, Alberto Silva-Muñoz, Moisés Bersini, Hugues |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34435094$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.14778/3329772.3329780 10.1007/978-3-319-09333-8_1 10.5220/0005846400490056 10.1016/j.orp.2016.09.002 10.1016/j.ejor.2019.01.018 10.1016/j.jnca.2016.01.010 10.1145/1012888.1005739 10.1007/978-3-319-13021-7_6 10.1007/978-3-319-92639-1_60 10.14778/3352063.3352129 10.1109/TKDE.2020.2994641 10.14778/3339490.3339503 10.1007/s12530-013-9072-y 10.1007/978-3-319-62410-5_11 10.1145/1353452.1353455 10.1023/A:1006556606079 10.1109/ACCESS.2020.2990735 10.1613/jair.2861 10.1007/978-3-319-44406-2_12 10.1155/2015/502795 10.14778/1687627.1687767 10.1016/j.suscom.2019.01.017 10.14778/2732977.2732995 10.14778/3352063.3352112 10.14778/3192965.3192971 |
| ContentType | Journal Article |
| Copyright | 2021 Silva-Muñoz et al. COPYRIGHT 2021 PeerJ. Ltd. 2021 Silva-Muñoz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2021 Silva-Muñoz et al. 2021 Silva-Muñoz et al. |
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| Keywords | Databases Automatic configuration Parameter tuning Cassandra Hyperparameter tuning |
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| SubjectTerms | Algorithms Artificial Intelligence Automatic configuration Cassandra Configurations Configurations (Computers) Data Mining and Machine Learning Data processing Database administration Design of experiments Hyperparameter tuning Machine learning Methods Optimization Parameter tuning Parameters Performance evaluation Software Statistical methods Statistical models Workloads |
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| Title | Automatic configuration of the Cassandra database using irace |
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