A design proto‐pattern for continuously evaluated forecasting in IBM^® InfoSphere^® Streams

Abstract

SUMMARYDesign patterns relieve much of the difficulty of developing software solutions. As sources and volumes of generated data have increased in recent times, stream computing has emerged as a new paradigm for acquiring and harnessing the data's rich potential to provide insight in near real time. One prominent platform for processing streaming data is IBM® InfoSphere® Streams, but design patterns for the platform are relatively scarce. This article proposes a prototypical application design pattern for continuously evaluated forecasting on the IBM InfoSphere Streams platform. Towards demonstrating the prototypical pattern, the application was implemented in three real-world scenarios: wind power, sentiment analysis, and stock market data. The purpose of this article is to specify the design proto-pattern and describe its variants in each different implementation. We believe that the proto-pattern will be applicable in IBM InfoSphere Streams to any data stream where forecasts over multiple forecast horizons are required.