| DC Field | Value | Language |
|---|
| dc.contributor.author | Zibitsker, B. | - |
| dc.date.accessioned | 2017-05-26T08:53:55Z | - |
| dc.date.accessioned | 2017-07-18T11:53:10Z | - |
| dc.date.available | 2017-05-26T08:53:55Z | - |
| dc.date.available | 2017-07-18T11:53:10Z | - |
| dc.date.issued | 2017 | - |
| dc.identifier.citation | Zibitsker, B. Incorporation of prescriptive analytics for performance engineering and dynamic performance management of Big Data applications / B. Zibitsker // BIG DATA and Advanced Analytics: collection of materials of the third international scientific and practical conference, Minsk, Belarus, May 3–4, 2017 / editorial board : М. Batura [et al.]. – Minsk : BSUIR, 2017. – С. 18. | ru_RU |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/12987 | - |
| dc.description.abstract | In a complex Big Data environment applications compete for resources and affect
each other performance. Selection of Machine Learning Algorithms and Machine Learning Libraries and Big Data YARN's Scheduler, Queues and Containers rules can significantly affect accuracy, performance and scalability of Big Data applications. | ru_RU |
| dc.language.iso | en | ru_RU |
| dc.publisher | БГУИР | ru_RU |
| dc.subject | материалы конференций | ru_RU |
| dc.subject | Big Data | ru_RU |
| dc.title | Incorporation of prescriptive analytics for performance engineering and dynamic performance management of Big Data applications | ru_RU |
| dc.type | Article | ru_RU |
| Appears in Collections: | BIG DATA and Advanced Analytics. Использование BIG DATA для оптимизации бизнеса и информационных технологий (2017)
|
