Domino: an incremental computing framework in cloud with eventual synchronization

Dong Dai, Yong Chen, D. Kimpe, R. Ross, Xuehai Zhou
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引用次数: 5

Abstract

In recent years, more and more applications in cloud have needed to process large-scale on-line data sets that evolve over time as entries are added or modified. Several programming frameworks, such as Percolator and Oolong, are proposed for such incremental data processing and can achieve efficient updates with an event-driven abstraction. However, these frameworks are inherently asynchronous, leaving the heavy burden of managing synchronization to applications developers. Such a limitation significantly restricts their usability. In this paper, we introduce a trigger-based incremental computing framework, called Domino, with a flexible synchronization mechanism and runtime optimizations to coordinate parallel triggers efficiently. With this new framework, both synchronous and asynchronous applications can be seamlessly developed. Use cases and current evaluation results confirm that the new Domino programming model delivers sufficient performance and is easy to use in large-scale distributed computing.
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Domino:具有最终同步的云中的增量计算框架
近年来,越来越多的云应用程序需要处理大规模的在线数据集,这些数据集随着时间的推移而随着条目的添加或修改而演变。一些编程框架,如Percolator和odragon,被提出用于这种增量数据处理,并且可以通过事件驱动的抽象实现有效的更新。然而,这些框架本质上是异步的,将管理同步的繁重负担留给了应用程序开发人员。这种限制极大地限制了它们的可用性。在本文中,我们介绍了一个基于触发器的增量计算框架,称为Domino,它具有灵活的同步机制和运行时优化,可以有效地协调并行触发器。使用这个新框架,可以无缝地开发同步和异步应用程序。用例和当前的评估结果证实,新的Domino编程模型提供了足够的性能,并且易于在大规模分布式计算中使用。
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