Computational Models for Big Data Processing

MapReduce framework has emerged as one of the most widely used parallel computing platforms for processing Big Data on tera- and peta-byte scale. In this note, we introduce several theoretical computational models for MapReduce from a standpoint of parallel algorithmic power by comparing MapReduce computation with standard parallel computational models such as PRAMs and/or combinational Boolean circuits.