Practical evaluation of the Lasp programming model at large scale: an experience report

Christopher S. Meiklejohn, Vitor Enes, Junghun Yoo, Carlos Baquero, P. V. Roy, Annette Bieniusa
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引用次数: 10

Abstract

Programming models for building large-scale distributed applications assist the developer in reasoning about consistency and distribution. However, many of the programming models for weak consistency, which promise the largest scalability gains, have little in the way of evaluation to demonstrate the promised scalability. We present an experience report on the implementation and large-scale evaluation of one of these models, Lasp, originally presented at PPDP '15, which provides a declarative, functional programming style for distributed applications. We demonstrate the scalability of Lasp's prototype runtime implementation up to 1024 nodes in the Amazon cloud computing environment. It achieves high scalability by uniquely combining hybrid gossip with a programming model based on convergent computation. We report on the engineering challenges of this implementation and its evaluation, specifically related to operating research prototypes in a production cloud environment.
大规模Lasp编程模型的实际评估:经验报告
用于构建大规模分布式应用程序的编程模型帮助开发人员对一致性和分布进行推理。然而,许多承诺获得最大可伸缩性的弱一致性编程模型几乎没有评估的方式来证明所承诺的可伸缩性。我们提供了一份关于这些模型之一Lasp的实现和大规模评估的经验报告,Lasp最初在PPDP '15上提出,它为分布式应用程序提供了一种声明式、函数式编程风格。我们演示了Lasp的原型运行时实现在Amazon云计算环境中最多可达1024个节点的可伸缩性。该算法独特地将混合八卦与基于收敛计算的规划模型相结合,实现了高可扩展性。我们报告了这种实现及其评估的工程挑战,特别是与生产云环境中的运营研究原型相关的挑战。
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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