Relational Model
The CData Cmdlets PowerShell Module for JSON can be configured to create a relational model of the data, treating nested object arrays as individual tables 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 JSON 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 JSON file or source will be queried once for each table (nested array) included in the query.
Example
Below is a sample query against the sample document in Raw Data, using a relational model based on the JSON paths "$.people", "$.people.vehicles", and "$.people.vehicles.maintenance".
Connecting String
Set the DataModel connection property to "Relational" and set the JSONPath connection property to "$.people;$.people.vehicles;$.people.vehicles.maintenance;" to perform the following query and see the example result set.
URI=C:\people.txt;DataModel=Relational;JSONPath='$.people;$.people.vehicles;$.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 object is JOINed to its parent vehicle object, which is JOINed to its parent people object to produce a table with 8 rows (2 maintenance entries for each of 2 vehicles each for 2 people).
age | gender | first_name | last_name | source | type | model | ins_company | ins_policy_num | maint_date | maint_desc | ||
20 | M | John | Doe | internet | car | Honda Civic | ABC Insurance | 12345 | 2017-07-17 | oil change | ||
20 | M | John | Doe | internet | car | Honda Civic | ABC Insurance | 12345 | 2018-01-03 | new tires | ||
20 | M | John | Doe | internet | truck | Dodge Ram | ABC Insurance | 12345 | 2017-08-27 | new tires | ||
20 | M | John | Doe | internet | truck | Dodge Ram | ABC Insurance | 12345 | 2018-01-08 | oil change | ||
24 | F | Jane | Roberts | phone | car | Toyota Camry | Car Insurance | 98765 | 2017-05-11 | tires rotated | ||
24 | F | Jane | Roberts | phone | car | Toyota Camry | Car Insurance | 98765 | 2017-11-03 | oil change | ||
24 | F | Jane | Roberts | phone | car | Honda Accord | Car Insurance | 98765 | 2017-10-07 | new air filter | ||
24 | F | Jane | Roberts | phone | car | Honda Accord | Car Insurance | 98765 | 2018-01-13 | new brakes |
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: Access nested object arrays as separate tables.
- JSON Functions: Manipulate the data returned to perform client-side aggregation and transformations.