Cite

[1] PÖLÖSKEI, I. ‒ BUB, U.: “Enterprise-level migration to micro frontends in a multi-vendor environment,” Acta Polytech. Hungarica, vol. 18, no. 8, pp. 7–25, 2021.10.12700/APH.18.8.2021.8.1 Search in Google Scholar

[2] OUSSOUS, A. ‒ BENJELLOUN, F. Z. ‒ AIT LAHCEN, A. ‒ BELFKIH, S.: “Big Data technologies: A survey,” J. King Saud Univ. -Comput. Inf. Sci., vol. 30, no. 4, pp. 431–448, 2018.10.1016/j.jksuci.2017.06.001 Search in Google Scholar

[3] MAVRIDIS, I. ‒ KARATZA, H.: “Performance evaluation of cloud-based log file analysis with Apache Hadoop and Apache Spark,” J. Syst. Softw., vol. 125, pp. 133–151, 2017.10.1016/j.jss.2016.11.037 Search in Google Scholar

[4] GRZEGOROWSKI, M. ‒ ZDRAVEVSKI, E. ‒ JANUSZ, A. ‒ LAMESKI, P. ‒ APANOWICZ, C. ‒ ŚLĘZAK, D.: “Cost Optimization for Big Data Workloads Based on Dynamic Scheduling and Cluster-Size Tuning,” Big Data Res., vol. 25, 2021.10.1016/j.bdr.2021.100203 Search in Google Scholar

[5] KARIM, M. R. ‒ COCHEZ, M. ‒ BEYAN, O. D. ‒ AHMED, C. F. ‒ DECKER, S.: “Mining maximal frequent patterns in transactional databases and dynamic data streams: A spark-based approach,” Inf. Sci. (Ny)., vol. 432, pp. 278–300, 2018.10.1016/j.ins.2017.11.064 Search in Google Scholar

[6] SADDAD, E. ‒ EL-BASTAWISSY, A. ‒ MOKHTAR, H. M. O. ‒ HAZMAN, M.: “Lake data warehouse architecture for big data solutions,” Int. J. Adv. Comput. Sci. Appl., vol. 11, no. 8, pp. 417–424, 2020.10.14569/IJACSA.2020.0110854 Search in Google Scholar

[7] RESKA, D. et al.: “Integration of solutions and services for multi-omics data analysis towards personalized medicine,” Biocybern. Biomed. Eng., vol. 41, no. 4, pp. 1646–1663, 2021. Search in Google Scholar

[8] Databricks, “Databricks.com.” [Online]. Available: https://databricks.com/glossary/what-are-transformations. Search in Google Scholar

[9] SHMEIS, Z. ‒ JABER, M.: “A rewrite-based optimizer for spark,” Futur. Gener. Comput. Syst., vol. 98, pp. 586–599, 2019.10.1016/j.future.2019.03.044 Search in Google Scholar

[10] KOLAJO, T. ‒ DARAMOLA, O. ‒ ADEBIYI, A.: “Big data stream analysis: a systematic literature review,” J. Big Data, vol. 6, no. 1, 2019.10.1186/s40537-019-0210-7 Search in Google Scholar

[11] CUI, Y. ‒ KARA, S. ‒ CHAN, K. C.: “Manufacturing big data ecosystem: A systematic literature review,” Robot. Comput. Integr. Manuf., vol. 62, 2020.10.1016/j.rcim.2019.101861 Search in Google Scholar

[12] MACHADO, I. A. ‒ COSTA, C. ‒ SANTOS, M. Y.: “Data Mesh: Concepts and Principles of a Paradigm Shift in Data Architectures,” Procedia Comput. Sci., vol. 196, no. 2021, pp. 263–271, 2021. Search in Google Scholar

[13] Microsoft Corporation, “Microsoft Azure documentation.” Search in Google Scholar

[14] BUREVA, V.: “Short remarks on index matrices Short remarks on Data Warehouse (DW), Data Lake (DL) and Data Lakehouse (DLH),” pp. 81–105, 2020. Search in Google Scholar

[15] GRIBAUDO, M. ‒ IACONO, M. ‒ KIRAN, M.: “A performance modeling framework for lambda architecture based applications,” Futur. Gener. Comput. Syst., vol. 86, pp. 1032–1041, 2018. Search in Google Scholar

[16] PERSICO, V. ‒ PESCAPÉ, A. ‒ PICARIELLO, A. ‒ SPERLÍ, G.: “Benchmarking big data architectures for social networks data processing using public cloud platforms,” Futur. Gener. Comput. Syst., vol. 89, pp. 98–109, 2018.10.1016/j.future.2018.05.068 Search in Google Scholar

[17] POLOSKEI, I.: “Data engineering case-study in digitalized manufacturing,” SAMI 2021 - IEEE 19th World Symp. Appl. Mach. Intell. Informatics, Proc., pp. 491–494, 2021.10.1109/SAMI50585.2021.9378691 Search in Google Scholar

[18] POLOSKEI, I.: “Continuous natural language processing pipeline strategy,” SACI 2021 - IEEE 15th Int. Symp. Appl. Comput. Intell. Informatics, Proc., pp. 221–224, 2021.10.1109/SACI51354.2021.9465571 Search in Google Scholar

[19] SLEEMAN IV, W. C. ‒ KRAWCZYK, B.: “Multi-class imbalanced big data classification on Spark,” Knowledge-Based Syst., vol. 212, p. 106598, 2021. Search in Google Scholar

[20] ZVARA, Z. ‒ SZABÓ, P. G. N. ‒ BALÁZS, B. ‒ BENCZÚR, A.: “Optimizing distributed data stream processing by tracing,” Futur. Gener. Comput. Syst., vol. 90, pp. 578–591, 2019.10.1016/j.future.2018.06.047 Search in Google Scholar

[21] AL-ZOBBI, M. ‒ SHAHRESTANI, S. ‒ RUAN, C.: “Experimenting sensitivity-based anonymization framework in apache spark,” J. Big Data, vol. 5, no. 1, 2018.10.1186/s40537-018-0149-0 Search in Google Scholar

[22] ROVNYAGIN, M. M. ‒ SHIPUGIN, V. A. ‒ OVCHINNIKOV, K. A. ‒ DURACHENKO, S. V.: “Intelligent container orchestration techniques for batch and micro-batch processing and data transfer.,” Procedia Comput. Sci., vol. 190, pp. 684–689, 2021.10.1016/j.procs.2021.06.079 Search in Google Scholar

eISSN:
1338-3957
Idioma:
Inglés
Calendario de la edición:
4 veces al año
Temas de la revista:
Computer Sciences, Information Technology, Databases and Data Mining, Engineering, Electrical Engineering