Fire consists of three core components:
- Web Browser for defining end-to-end workflows for building data products and applications
- Users interact with the web based drag and drop user interface for creating Datasets and Workflows
- Workflows leverage the exhaustive set of functional and operational nodes such as Data Profiling, Data Cleaning, ETL, NLP, OCR, Machine Learning etc. displayed in the user interface.
- Web Server running on an Edge node in a Apache Spark Cluster
- For running the workflows, they are submitted to the web server. The web server submits the workflow to the Apache Spark cluster as a spark job using spark-submit. The results of the workflow execution are streamed back and displayed in the Browser.
- Web Server provides a host of other features likes interactive execution, schema inference and propagation, user permissions and roles, LDP integration etc.
- Apache Spark cluster on which the workflows are executed as Spark jobs
- Workflows are saved in a JSON string.
- Workflows can also be submitted on the spark cluster through spark-submit via a command line interface