Cloud-based data stream processing

Thomas S. Heinze, Leonardo Aniello, Leonardo Querzoni, Zbigniew Jerzak
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引用次数: 59

Abstract

In this tutorial we present the results of recent research about the cloud enablement of data streaming systems. We illustrate, based on both industrial as well as academic prototypes, new emerging uses cases and research trends. Specifically, we focus on novel approaches for (1) scalability and (2) fault tolerance in large scale distributed streaming systems. In general, new fault tolerance mechanisms strive to be more robust and at the same time introduce less overhead. Novel load balancing approaches focus on elastic scaling over hundreds of instances based on the data and query workload. Finally, we present open challenges for the next generation of cloud-based data stream processing engines.
基于云的数据流处理
在本教程中,我们将介绍有关数据流系统的云支持的最新研究结果。我们以工业和学术原型为基础,阐述了新出现的用例和研究趋势。具体来说,我们专注于(1)大规模分布式流系统的可伸缩性和(2)容错的新方法。通常,新的容错机制力求更健壮,同时引入更少的开销。新的负载平衡方法侧重于根据数据和查询工作负载在数百个实例上进行弹性扩展。最后,我们提出了下一代基于云的数据流处理引擎的公开挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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