Data Streaming Processing Window Joined With Graphics Processing Units (GPUs)

Abstract

Big data is large-scale data and can be either discrete or continuous. This article entails research that discusses the continuous case of big data often called “data streaming.” More and more businesses will depend on being able to process and make decisions on streams of data. This article utilizes the algorithmic side of data stream processing often called “stream analytics” or “stream mining.” Data streaming Windows Join can be improved by using graphics processing unit (GPU) for higher performance computing. Data streams are generated by two independent threads: one thread can be used to generate Data Stream A, and the other thread can be used to generate Data Stream B. One would use a Windows Join thread to merge the two data streams, which is also the process of “Data Stream Window Join.” The Window Join process can be implemented in parallel that can efficiently improve the computing speed. Experiments are provided for Data Stream Window Joins using both static and dynamic data.