dmn4spark is a library which enables developers to use the Camunda Decision Model and Notation (DMN) in Big Data environments with Apache Spark. Thanks to this tools, users can perform decision making tasks on large amounts of data in a user-friendly and efficient way. This tool is the cortnerstone of our methodology DMN4DQ, which aims at facilitating data quality tasks in a context-aware basis.

Camunda DMN is an industry standard for modeling and executing decisions. Decisions are modeled in DMN tables, a user-friendly way of modeling business rules and decision rules. The rules in the DMN table are modeled with the Friendly Enough Expression Language (FEEL). feel-scala is the version which is currently supported in this library. It provides a set of data types and built-in function for making easier the construction of decision rules. Please refer to its documentation for

Try it yourself!

You can find a tutorial and the source code in our GitHub repository.