The CData Python Connector for REST can be configured to create a relational model of the data, treating each XPath as an individual table containing a primary key and a foreign key that links to the parent document. This is particularly useful if you need to work with your data in existing BI, reporting, and ETL tools that expect a relational data model.

Joining Nested Arrays as Tables

With DataModel set to "Relational", any JOINs are controlled by the query. Any time you perform a JOIN query, the file or source will be queried once for each table included in the query.

Example

Below is a sample query against the sample document in Raw Data, using a relational model based on the XPaths "/root/people", "/root/people/vehicles", and "/root/people/vehicles/maintenance".

Connecting String

Set the DataModel connection property to "Relational" and set the XPath connection property to "/root/people;/root/people/vehicles;/root/people/vehicles/maintenance;" to perform the following query and see the example result set.

URI=C:\people.txt;Format=XML;DataModel=Relational;XPath='/root/people;/root/people/vehicles;/root/people/vehicles/maintenance;'

Query

The following query explicitly JOINs the people, vehicles, and maintenance tables.

SELECT 
  [people].[personal.age] AS age, 
  [people].[personal.gender] AS gender, 
  [people].[personal.name.first] AS first_name, 
  [people].[personal.name.last] AS last_name, 
  [people].[source], 
  [vehicles].[type], 
  [vehicles].[model], 
  [vehicles].[insurance.company] AS ins_company, 
  [vehicles].[insurance.policy_num] AS ins_policy_num, 
  [maintenance].[date] AS maint_date, 
  [maintenance].[desc] AS maint_desc
FROM 
  [people]
JOIN 
  [vehicles] 
ON 
  [people].[_id] = [vehicles].[people_id]
JOIN 
  [maintenance] 
ON 
  [vehicles].[_id] = [maintenance].[vehicles_id]

Results

In the example query, each maintenance element is JOINed to its parent vehicle element, which is JOINed to its parent people element to produce a table with 8 rows (2 maintenance entries for each of 2 vehicles each for 2 people).

See Also

• Automatic Schema Discovery: Configure the columns reported in the table schemas.
• Free-Form Queries: Use dot notation to select nested data.
• Vertical Flattening: Query nested data as separate tables.
• XML Functions and JSON Functions: Manipulate the data returned to perform client-side aggregation and transformations.