@inproceedings{a1437459d1544c5680254039c77b4d27,
title = "Performance Evaluation of a Data Lake Architecture via Modeling Techniques",
abstract = "Data Lake is a term denoting a repository storing heterogeneous data, both structured and unstructured, resulting in a flexible organization that allows Data Lake users to reorganize and integrate dynamically the information they need according to the required query or analysis. The success of its implementation depends on many factors, notably the distributed storage, the kind of media deployed, the data access protocols and the network used. However, flaws in the design might become evident only in a later phase of the system development, causing significant delays in complex projects. This article presents an application of queuing networks modeling technique to detect significant issues, such as bottlenecks and performance degradation, for different workload scenarios.",
keywords = "Data lake, JMT, Queuing networks, Data lake, JMT, Queuing networks",
author = "Enrico Barbierato and Marco Gribaudo and Giuseppe Serazzi and Letizia Tanca",
year = "2021",
doi = "10.1007/978-3-030-91825-5_7",
language = "English",
isbn = "978-3-030-91825-5",
volume = "13104",
series = "LECTURE NOTES IN COMPUTER SCIENCE",
pages = "115--130",
booktitle = "European Workshop on Performance Engineering International Conference on Analytical and Stochastic Modeling Techniques and Applications",
note = "17th European Performance Engineering Workshop, EPEW 2021, and the 26th International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2021 ; Conference date: 09-12-2021 Through 10-12-2021",
}