Towards Formalizing of MapReduce
Yuxin Jing, Hanpin Wang, Yu Huang, Lei Zhang, Yongzhi Cao · 2017
As a powerful distributed computing model, MapReduce has been widely used in many domains to process massive amounts of data. To ensure its correctness, one of the appropriate ways is formal methods. In this paper, we will propose a formal language to model MapReduce Programs based on our previous work. The language describes the MapReduce programming model from a view of files and blocks. So the details of data processing during a MapReduce computation can be clearly demonstrated. Certainly some parallel commands are introduced to reflect the parallelization of the computation. Based on this language, the correctness verification of the MapReduce programming model can be developed.