Azure Databricks Notebooks Modulization and Interaction

Azure Databricks is the most common and popular platform and engine for data engineering and machine learning in Azure cloud. Notebook is the most used tool and application to do the data processing and data analysis, it not only inherits Jupyter Notebook powerful functionalities in Python but integrates Scala, R, Java even markdown to be able to create storyboard for data process. One common use case for a large data process development is notebooks need to call each. Main notebook calls sub-notebooks to retrieve classes, functions or properties, sub-notebooks call to parameter notebook to retrieve values for parameters. Notebook can be modularized and imported by other notebooks, this post is about the methods on notebook modulization and reference.