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I2: Interactive Real-Time Visualization for Streaming Data

Developing scalable real-time data analysis programs is a challenging task. Developers need insights from the data to define meaningful analysis flows, which often makes the development a trial and error process. Data visualization techniques can provide insights to aid the development, but the sheer amount of available data frequently makes it impossible to visualize all data points at the same time. We present I, an interactive development environment that coordinates running cluster applications and corresponding visualizations such that only the currently depicted data points are processed and transferred. To this end, we present an algorithm for the real-time visualization of time series, which is proven to be correct and minimal in terms of transferred data. Moreover, we show how cluster programs can adapt to changed visualization properties at runtime to allow interactive data exploration on data streams.