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Handling Iterations in Distributed Dataflow Systems
Citation key GevaySM22
Author Gábor E. Gévay, Juan Soto, Volker Markl
Pages 1-38
Year 2022
DOI 10.1145/3477602
Journal ACM Comput. Surv.
Volume 54
Number 9
Abstract Over the past decade, distributed dataflow systems (DDS) have become a standard technology. In these systems, users write programs in restricted dataflow programming models, such as MapReduce, which enable them to scale out program execution to a shared-nothing cluster of machines. Yet, there is no established consensus that prescribes how to extend these programming models to support iterative algorithms. In this survey, we review the research literature and identify how DDS handle control flow, such as iteration, from both the programming model and execution level perspectives. This survey will be of interest for both users and designers of DDS.
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