第四届MapReduce及Beyond算法与系统研讨会报告(BeyondMR’17)

F. Afrati, J. Hidders, Paraschos Koutris, J. Sroka, J. Ullman
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引用次数: 0

摘要

本报告总结了第四届MapReduce和Beyond算法和系统研讨会(BeyondMR '17)的演讲和讨论。BeyondMR研讨会于2017年5月19日星期五在美国伊利诺伊州芝加哥市与2017 SIGMOD/PODS会议一起举行。研讨会的目标是将研究人员和实践者聚集在一起,探索提供大规模并行化和容错的系统的算法、计算模型、语言和接口。其中包括基于MapReduce及其扩展的专门编程和数据管理系统、图形处理系统和数据密集型工作流系统。会议邀请了两场演讲,第一场由Databricks和斯坦福大学的Matei Zaharia主讲大数据处理的当前和未来发展,第二场由香港科技大学的柯毅主讲大数据处理算法的分析和开发计算模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Report from the Fourth Workshop on Algorithms andSystems for MapReduce and Beyond (BeyondMR '17)
This report summarizes the presentations and discussions of the fourth workshop on Algorithms and Systems for MapReduce and Beyond (BeyondMR '17). The BeyondMR workshop was held in conjunction with the 2017 SIGMOD/PODS conference in Chicago, Illinois, USA on Friday May 19, 2017. The goal of the workshop was to bring together researchers and practitioners to explore algorithms, computational models, languages and interfaces for systems that provide large-scale parallelization and fault tolerance. These include specialized programming and data-management systems based on MapReduce and extensions thereof, graph processing systems and data-intensive workflow systems. The program featured two well-attended invited talks, the first on current and future development in big data processing by Matei Zaharia from Databricks and the University of Stanford, and the second on computational models for the analysis and development of big data processing algorithms by Ke Yi from the Hong Kong University of Science and Technology.
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