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Handling Iterations in Distributed Dataflow Systems
Zitatschlüssel GevaySM22
Autor Gábor E. Gévay, Juan Soto, Volker Markl
Seiten 1-38
Jahr 2022
DOI 10.1145/3477602
Journal ACM Comput. Surv.
Jahrgang 54
Nummer 9
Zusammenfassung 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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