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Differential approximation and sprinting for multi-priority big data engines

Today’s big data clusters based on the MapReduce paradigm are capable of executing analysis jobs with multiple priorities, providing differential latency guarantees. Traces from production systems show that the latency advantage of high-priority jobs comes at the cost of severe latency degradation o...

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Detalles Bibliográficos
Autores Principales: Birke R., Rocha I., Pérez, Juan F., Schiavoni V., Felber P., Chen L.Y.
Formato: Objeto de conferencia (Conference Object)
Lenguaje:Inglés (English)
Publicado: Association for Computing Machinery, Inc 2019
Materias:
Electric sparks
Energy conservation
Energy utilization
Engines
Middleware
Differential approximations
Latency reduction
Priorities
Production system
Resource management
Resource wastes
Spark processing
Sprinting
Big data
Differential approximation
Energy savings
Spark
Acceso en línea:https://repository.urosario.edu.co/handle/10336/22595
https://doi.org/10.1145/3361525.3361547

Internet

https://repository.urosario.edu.co/handle/10336/22595
https://doi.org/10.1145/3361525.3361547

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