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arXiv:1708.06423cs.DC

Practical Evaluation of the Lasp Programming Model at Large Scale - An Experience Report

Christopher S. Meiklejohn, Vitor Enes, Junghun Yoo, Carlos Baquero, Peter Van Roy, Annette Bieniusa

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.

arXiv comments
Journal reference
DOI
doi:10.1145/3131851.3131862
Subjects
cs.DCDistributed, Parallel, and Cluster Computing

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    • Not just aggregating writes, but merging them. It seems that high load high scale solutions [1] [2] start to converge on this idea of merging updates and eventual consistency. [1] https://arxiv.org/pdf/1708.06423.pdf [2] https://databeta.wordpress.com/2018/03/09/anna-kvs/

      zzzcpanView on HNParent context

    • The Lasp programming system also has an eventually consistent key-value store built-in (and, we've scaled it to 1,024+ nodes). Project home: https://lasp-lang.readme.io/docs Results on scaling: https://arxiv.org/abs/1708.06423

      cmeiklejohnView on HNParent context

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