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Chemistry-Inspired Adaptive Stream Processing

机译:化学启发自适应流处理

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Stream processing engines have appeared as the next generation of data processing systems, facing the needs for low-delay processing. While these systems have been widely studied recently, their ability to adapt their processing logics at run time upon the detection of some events calling for adaptation is still an open issue. Chemistry-inspired models of computation have been shown to ease the specification of adaptive systems. In this paper, we argue that a higher-order chemical model can be used to specify such an adaptive SPE in a natural way. We also show how such programming abstractions can get enacted in a decentralised environment.
机译:流处理引擎已出现作为下一代数据处理系统,面对低延延迟处理的需求。虽然最近这些系统已被广泛研究,但它们在检测到调用适应某些事件时在运行时调整其处理逻辑的能力仍然是一个开放的问题。已经显示化学灵感的计算模型来缓解自适应系统的规格。在本文中,我们认为高阶化学模型可用于以自然的方式指定这种自适应SPE。我们还展示了这些编程抽象如何在分散的环境中颁布。

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