Window aggregate sharing for out-of-order stream processing
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- Año de publicación 2016
- Idioma Inglés
- Descripción
- This thesis proposes a novel window aggregate sharing approach for out-of-order stream processing. We combined together the best of two worlds: the Google dataflow model for out-of-order stream processing and the Cutty aggregate sharing strategy. To our knowledge, our solution is the only aggregate sharing strategy for out-of-order stream processing that supports sliding, tumbling and session windows.Based on the experiments with the real world dataset DEBS12 [28] and a 3% out-of-order level, our solution has 1.24 higher throughput than the current implementation in Flink. Moreover, we show that the throughput of our solution becomes higher, as the out-of-order level increases.
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Citación recomendada (normas APA)
- Alejandro Rodríguez Cuéllar, "Window aggregate sharing for out-of-order stream processing", -:-, 2016. Consultado en línea en la Biblioteca Digital de Bogotá (https://www.bibliotecadigitaldebogota.gov.co/resources/2084786/), el día 2024-04-25.
