In this section we will show how to control the various schemes that the connector offers to bridge the gap with relational SQL and nested Avro services. The CData Python Connector for Avro provides a managed way for you to use the two prevailing techniques for dealing with nested Avro data:

• Parsing the data structure and building a relational model based on the existing hierarchy.
• Drilling down into the nested arrays and objects using horizontal flattening.

Parsing Hierarchical Data

By default, the connector automatically detects the rows in a document, so that you do not need to know the structure of the underlying data to query it with SQL. Set the DataModel property to choose a basic configuration of how the connector models object arrays into tables. Set the FlattenObjects and FlattenArrays properties to configure how nested data is flattened into columns. See Parsing Hierarchical Data for a guide.