Using IVML to model the topology of big data processing pipelines

Holger Eichelberger, Cui Qin, R. Sizonenko, Klaus Schmid
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引用次数: 16

Abstract

Creating product lines of Big Data stream processing applications introduces a number of novel challenges to variability modeling. In this paper, we discuss these challenges and demonstrate how advanced variability modeling capabilities can be used to directly model the topology of processing pipelines as well as their variability. We also show how such processing pipelines can be modeled, configured and validated using the Integrated Variability Modeling Language (IVML).
利用IVML对大数据处理管道拓扑进行建模
创建大数据流处理应用的产品线给可变性建模带来了许多新的挑战。在本文中,我们讨论了这些挑战,并演示了如何使用先进的可变性建模功能来直接对处理管道的拓扑结构及其可变性进行建模。我们还展示了如何使用集成可变性建模语言(Integrated Variability Modeling Language, IVML)对这些处理管道进行建模、配置和验证。
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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