Optimizing joins in a map-reduce environment

By Foto N. Afrati, Jeffrey D. Ullman. International Conference on Extending Database Technology, 2010

390 citations recorded by the source corpus.

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Hadoop++ (2010, methodology): “Afrate and Ullman [4] proposed techniques to perform multiway joins in a single MapReduce job.”
Parallel data processing with MapReduce: a survey (2012, background): “Afrati et al focus on how to minimize the sum of the communication cost of data that are transferred to Reducers for multi-way join [2].”
EmptyHeaded: A Relational Engine for Graph Processing (2015, background): “city of a single node. We are optimistic that our results can be applied within a single execution node. Additionally, new theory has been proposed for such scale-out systems that we plan to leverage [7,9]. Life Cycle of Data. We consider only a fraction, albeit an important one, of the complete lif”