For models that contain nested repeating groups, Intelligent Structure Discovery uses primary and foreign keys to identify the relationships between repeating groups and their child nodes.
When a model that is based on a JSON, XML, or XSD file contains nested repeating groups, Intelligent Structure Discovery can normalize the output data and assign each nested repeating group to its own output group. For models that are based on other input types, you can manually assign nested repeating groups to their output groups.
When a nested repeating group is assigned to its output group, Intelligent Structure Discovery adds a primary key to the parent group and a foreign key to the child group.
The following image shows the structure that Intelligent Structure Discovery discovered from a CSV input file:
In this model, the list group is part of the element output group. The data normalization mode is denormalized, and the list nested repeating group isn't assigned to a separate output group.
The following image shows the same model after you change the data normalization mode to normalized:
Intelligent Structure Discovery generates two separate output groups, the element output group, and the list output group. You can view a group name by hovering over the tip icon to the left of the group.
Intelligent Structure Discovery added the primary key element_PK to the parent element output group, and the foreign key element_FK to the nested list output group.
You can select a different node as the primary key by defining it as a record ID. When you change the record ID, Intelligent Structure Discovery creates a corresponding foreign key in the nested group.
