HyperStream: a Workflow Engine for Streaming Data
This provides a general-purpose tool for designing, developing, and deploying machine learning algorithms in sequential predictive problems, but it appears incremental as it builds on existing workflow and streaming data concepts.
The paper introduces HyperStream, a Python-based workflow engine for processing streaming data, designed to overcome limitations of other computational engines and execute complex operations like nesting, fusion, and prediction in both online and offline forms.
This paper describes HyperStream, a large-scale, flexible and robust software package, written in the Python language, for processing streaming data with workflow creation capabilities. HyperStream overcomes the limitations of other computational engines and provides high-level interfaces to execute complex nesting, fusion, and prediction both in online and offline forms in streaming environments. HyperStream is a general purpose tool that is well-suited for the design, development, and deployment of Machine Learning algorithms and predictive models in a wide space of sequential predictive problems. Source code, installation instructions, examples, and documentation can be found at: https://github.com/IRC-SPHERE/HyperStream.