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.
Lingua originale | English |
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Titolo della pubblicazione ospite | European Workshop on Performance Engineering International Conference on Analytical and Stochastic Modeling Techniques and Applications |
Pagine | 115-130 |
Numero di pagine | 16 |
Volume | 13104 |
DOI | |
Stato di pubblicazione | Pubblicato - 2021 |
Evento | 17th European Performance Engineering Workshop, EPEW 2021, and the 26th International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2021 - Tokio Durata: 9 dic 2021 → 10 dic 2021 |
Workshop
Workshop | 17th European Performance Engineering Workshop, EPEW 2021, and the 26th International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2021 |
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Città | Tokio |
Periodo | 9/12/21 → 10/12/21 |
Keywords
- Data lake
- Queuing networks
- JMT