| Autor: |
Long Wang, John T. E. Timm, Phil Coulthard, Robin Arnold, Denis Ricard, Lee Suprenant, Senthil Bakthavachalam, Ahut Gupta, Valentina Salapura, HariGovind V. Ramasamy, Richard E. Harper, Xu Wang |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
DSN (Industry Track) |
| DOI: |
10.1109/dsn-industry.2019.00012 |
| Popis: |
Data pipeline platforms hosting big data analytics can span multiple clouds. Backup and restore service is typically applied to deal with data corruptions in such platforms. This paper proposes a novel approach to providing consistency to the restored state of a multi-cloud data pipeline platform from its backups, and also presents the performance of the approach demonstrated in a dry run test. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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