Research on Parallel Computing Model and Classification Algorithm Based on Data Mining Process

Abstract

In the big data era, with the parallel evolution of computer architecture, computing changes and modifications of industrial application mode resource expansion capability, we need to explore a new parallel computing model, to reflect the properties and large data applications form the current parallel machines, and a variety of mainstream big data processing system for unified theoretical analysis to guide large data applications tuning. Currently, despite the large data programming model study made many achievements, and is widely used in the TB level or even PB-class data processing and analysis, but the corresponding computational model study has just begun. From traditional parallel computing model, research big data programming model and large data computation model, summed up the three basic problems of large data model, in theory, need to be addressed: the three elements of the problem model, scalability and fault tolerance issues and performance optimization. Around these three questions, on the one hand and performance optimization model to calculate the theoretical study of data from a large, on the other hand these performance optimization methods in case of an actual big data.