Window aggregate sharing for out-of-order stream processing
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Contenido de la obra
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- Título: Window aggregate sharing for out-of-order stream processing
- Autor: Rodríguez Cuéllar, Alejandro
- Publicación original: 2016
- Descripción física: PDF
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Nota general:
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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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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.
- Notas de reproducción original: Digitalización realizada por la Biblioteca Virtual del Banco de la República (Colombia)
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Notas:
- Resumen: Streaming; Aggregate sharing; Out-of-order stream processing; Windowing; Google dataflow; Cutty
- © Derechos reservados del autor
- Colfuturo
- Forma/género: tesis
- Idioma: inglés
- Institución origen: Biblioteca Virtual del Banco de la República
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Encabezamiento de materia:
