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Adaptive Application Performance Management for Big Data Stream Processing

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2015

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Geselllschaft für Informatik e.V.

Zusammenfassung

Big data applications with their high-volume and dynamically changing data streams impose new challenges to application performance management. Efficient and effective solutions must balance performance versus result precision and cope with dramatic changes in real-time load and needs without overprovisioning resources. Moreover, a developer should not be burdened too much with addressing performance management issues, so he can focus on the functional perspective of the system For addressing these challenges, we present a novel comprehensive approach, which combines software configuration, model-based development, application performance management and runtime adaptation.

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Eichelberger, Holger; Qin, Cui; Schmid, Klaus; Niederée, Claudia (2015): Adaptive Application Performance Management for Big Data Stream Processing. Softwaretechnik-Trends Band 35, Heft 3. Bonn: Geselllschaft für Informatik e.V.. PISSN: 0720-8928. Sonderteil: Proceedings of the Symposium on Software Performance (SSP) 2015, 4. - 6. November 2015, Munich, Germany

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