Abstract
The implementation of parallel applications is always a challenge. It embraces many distinctive design decisions that are to be taken. The paper presents issues of parallel processing with use of .NET applications and popular database management systems. In the paper, three design dilemmas are addressed: how efficient is the auto-parallelism implemented in the .NET TPL library, how do popular DBMSes differ in serving parallel requests, and what is the optimal size of data chunks in the data parallelism scheme. All of them are analyzed in the context of the typical and practical business case originated from IT solutions which are dedicated for the energy market participants.
The paper presents the results of experiments conducted in a controlled, on-premises environment. The experiments allowed to compare the performance of the TPL auto-parallelism with a wide range of manually-set numbers of worker threads. They also helped to evaluate 4 DBMSes: Oracle, MySQL, PostgreSQL, and MSSQL in the scenario of serving parallel queries. Finally, they showed the impact of data chunk sizes on the overall performance.
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References
Sumic, Z., Harrison, K.: Magic Quadrant for Meter Data Management Products. Market report, Gartner (2018)
CSIRE Information Exchange Standards. https://www.pse.pl/web/pse-eng/oire/information-exchange-standards-ies. Accessed 12 Apr 2022
Entity Framework Documentation. https://docs.microsoft.com/en-us/ef. Accessed 24 Jan 2022
Task Parallel Library (TPL) Documentation. https://docs.microsoft.com/en-us/dotnet/standard/parallel-programming/task-parallel-library-tpl. Accessed 24 Jan 2022
Hoag, F.E.: TPL Performance Improvements in .NET 4.5. Technical report, Microsoft (2011)
Vištica, M., Haseljić, H., Maksumić, A., Nosović, N.: Comparison of speedups for computing π using .NET TPL and OpenMP parallelization technologies. In: X International Symposium on Telecommunications (BIHTEL), pp. 1–4 (2014). https://doi.org/10.1109/BIHTEL.2014.6987657
Kaldéren, G.A., From, A.: A comparative analysis between parallel models in C/C++ and C#/Java. KTH BSc Thesis (2013). http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-128606
Luo, Z., Zheng, Q., Hei, X., Giacaman, N.: Parallel programming based on Microsoft .NET TPL. In: Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013) (2013). https://doi.org/10.2991/iccsee.2013.129
Zmaranda, D., Pop-Fele, L.-L., Győrödi, R., Győrödi, C.: Actor Model versus TPL for applications development. In: Proceedings of the 16th International Conference on Engineering of Modern Electric Systems (EMES) (2021). https://doi.org/10.1109/EMES52337.2021.9484154
TPC Council. https://www.tpc.org. Accessed 24 Jan 2022
Funke, F., Kemper, A., Neumann, T.: Benchmarking hybrid OLTP&OLAP database systems. In: Härder, T., Lehner, W., Mitschang, B., Schöning, H., Schwarz, H. (eds.) Datenbanksysteme für Business, Technologie und Web (BTW), pp. 390–409. Gesellschaft für Informatik e.V., Bonn (2011)
Lachewicz, K.: Performance analysis of selected database systems: MySQL, MS SQL, PostgerSQL in the context of web applications. J. Comput. Sci. Inst. 14, 94–100 (2020). https://doi.org/10.35784/jcsi.1583
Kleweka, R., Truskowski, W., Skublewska-Paszkowska, M.: Comparison of MySQL, MSSQL, PostgreSQL, Oracle databases performance, including virtualization. J. Comput. Sci. Inst. 16, 279–284. https://doi.org/10.35784/jcsi.2026
Difallah, D.E., Pavlo, A., Curino, C., Cudre-Mauroux, P.: OLTP-Bench: an extensible testbed for benchmarking relational databases. Proc. VLDB Endow. 7(4), 277–288 (2013). https://doi.org/10.14778/2732240.2732246
Liarokapis, D., O’Neil, E., O’Neil, P.: Testing concurrency in databases still matters. In: International Conference on Information Technologies (InfoTech), pp. 1–6 (2020). https://doi.org/10.1109/InfoTech49733.2020.9211014
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Part of this work has been funded by the European Regional Development Fund under the Smart Growth Operational Programme (contract number POIR.01.01.01-00-0112/21-00), www.sygnity.pl/dotacje/.
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Karwaczyński, P., Sitko, M., Pietras, S., Marczuk, B., Kwiatkowski, J., Fraś, M. (2022). Impact of Design Decisions on Performance of Embarrassingly Parallel .NET Database Application. In: Szczerbicki, E., Wojtkiewicz, K., Nguyen, S.V., Pietranik, M., Krótkiewicz, M. (eds) Recent Challenges in Intelligent Information and Database Systems. ACIIDS 2022. Communications in Computer and Information Science, vol 1716. Springer, Singapore. https://doi.org/10.1007/978-981-19-8234-7_19
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DOI: https://doi.org/10.1007/978-981-19-8234-7_19
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