Azure Data Factory (ADF) JSON Connector In this article you will learn how to integrate JSON data to Azure Data Factory (ADF) without coding in just a few clicks (live / bi-directional connection to JSON). JSON Connector can be used to extract and output JSON data coming from REST API web service calls (Web URL) or direct JSON String (variables or DB columns) or local JSON files data. JSON Connector also supports JSONPath to filter data from nested array/sub-documents. This Connector is optimized to work with very large JSON string.. Using JSON Connector you will be able to connect, read, and write data from within Azure Data Factory (ADF). Follow the steps below to see how we would accomplish that. Download  Help File  Buy  Driver mentioned in this article is part of ODBC PowerPack which is a collection of high-performance Drivers for various API data source (i.e. REST API, JSON, XML, CSV, Amazon S3 and many more). Using familiar SQL query language you can make live connections and read/write data from API sources or JSON / XML / CSV Files inside SQL Server (T-SQL) or your favorite Reporting (i.e. Power BI, Tableau, Qlik, SSRS, MicroStrategy, Excel, MS Access), ETL Tools (i.e. Informatica, Talend, Pentaho, SSIS). You can also call our drivers from programming languages such as JAVA, C#, Python, PowerShell etc. If you are new to ODBC and ZappySys ODBC PowerPack then check the following links to get started. ODBC PowerPack - System Requirements and Installation Getting Started - Using ODBC PowerPack ODBC API Driver Help File

See also Connect JSON in SSIS Connect JSON in SQL Server Connect JSON in Power BI Connect JSON in SSRS Connect JSON in Informatica Connect JSON in MS Access Connect JSON in MS Excel Connect JSON in SSAS Connect JSON in C# Connect JSON in Python Connect JSON in JAVA Connect JSON in Tableau Connect JSON in SAP Crystal Reports Connect JSON in ODBC

Create ODBC Data Source (DSN) based on ZappySys JSON Driver

To get data from Json using Azure Data Factory (ADF) we first need to create a DSN (Data Source) which will access data from Json. We will later be able to read data using Azure Data Factory (ADF). Perform these steps:

1. Install ZappySys ODBC PowerPack.

2. Open ODBC Data Sources (x64):
   

3. Create a System Data Source (System DSN) based on ZappySys JSON Driver

   ZappySys JSON Driver

   
   You should create a System DSN (instead of a User DSN) if the client application is launched under a Windows System Account, e.g. as a Windows Service. If the client application is 32-bit (x86) running with a System DSN, use ODBC Data Sources (32-bit) instead of the 64-bit version. Furthermore, a User DSN may be created instead, but then you will not be able to use the connection from Windows Services (or any application running under a Windows System Account).

4. Select Url or File and paste the following Url for this example.
   NOTE: Here for demo, We are using odata API, but you need to refer your own API documentation and based on that you need to use your own API URL and need to configure connection based on API Authentication type

   https://services.odata.org/V3/Northwind/Northwind.svc/Customers?$format=json

5. Now enter JSONPath expression in Array Filter textbox to extract only specific part of JSON file as below ($.value[*] will get content of value attribute from JSON document. Value attribute is array of JSON documents so we have to use [*] to indicate we want all records of that array)
   NOTE: Here, We are using our desired filter, but you need to select your desired filter based on your requirement.
   Click on Test Connection button to view whether the Test Connection is SUCCESSFUL or Not.

   $.value[*]
   

6. Once you configured a data source, you can preview data. Hit Preview tab, and use similar settings to preview data:
   

7. Click OK to finish creating the data source

8. That's it; we are done. In a few clicks we configured the call to JSON API using ZappySys JSON Connector.

Read data in Azure Data Factory (ADF) from ODBC datasource (JSON)

1. To start press New button:

   

2. Select "Azure, Self-Hosted" option:

   

3. Select "Self-Hosted" option:

   

4. Set a name, we will use "OnPremisesRuntime":

   

5. Download and install Microsoft Integration Runtime.

6. Launch Integration Runtime and copy/paste Authentication Key from Integration Runtime configuration in Azure Portal:

   

7. After finishing registering the Integration Runtime node, you should see a similar view:

   

8. Go back to Azure Portal and finish adding new Integration Runtime. You should see it was successfully added:

   

9. Go to Linked services section and create a new Linked service based on ODBC:

   

10. Select "ODBC" service:

    

11. Configure new ODBC service. Use the same DSN name we used in the previous step and copy it to Connection string box:

    JsonDSN

    DSN=JsonDSN

    

12. For created ODBC service create ODBC-based dataset:

    

13. Go to your pipeline and add Copy data connector into the flow. In Source section use OdbcDataset we created as a source dataset:

    

14. Then go to Sink section and select a destination/sink dataset. In this example we use precreated AzureBlobStorageDataset which saves data into an Azure Blob:

    

15. Finally, run the pipeline and see data being transferred from OdbcDataset to your destination dataset:

    

Create Custom Store Procedure in ZappySys Driver

You can create procedures to encapsulate custom logic and then only pass handful parameters rather than long SQL to execute your API call.

Steps to create Custom Store Procedure in ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here

1. Go to Custom Objects Tab and Click on Add button and Select Add Procedure:
   

2. Enter the desired Procedure name and click on OK:
   

3. Select the created Store Procedure and write the your desired store procedure and Save it and it will create the custom store procedure in the ZappySys Driver:
   Here is an example stored procedure for ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here
   

   CREATE PROCEDURE [usp_get_orders]
       @fromdate = '<<yyyy-MM-dd,FUN_TODAY>>'
    AS
       SELECT * FROM Orders where OrderDate >= '<@fromdate>';
   

   
   

4. That's it now go to Preview Tab and Execute your Store Procedure using Exec Command. In this example it will extract the orders from the date 1996-01-01:
   

   Exec usp_get_orders '1996-01-01';

   
   

Create Custom Virtual Table in ZappySys Driver

ZappySys API Drivers support flexible Query language so you can override Default Properties you configured on Data Source such as URL, Body. This way you don't have to create multiple Data Sources if you like to read data from multiple EndPoints. However not every application support supplying custom SQL to driver so you can only select Table from list returned from driver.

Many applications like MS Access, Informatica Designer wont give you option to specify custom SQL when you import Objects. In such case Virtual Table is very useful. You can create many Virtual Tables on the same Data Source (e.g. If you have 50 URLs with slight variations you can create virtual tables with just URL as Parameter setting.

1. Go to Custom Objects Tab and Click on Add button and Select Add Table:
   

2. Enter the desired Table name and click on OK:
   

3. And it will open the New Query Window Click on Cancel to close that window and go to Custom Objects Tab.

4. Select the created table, Select Text Type AS SQL and write the your desired SQL Query and Save it and it will create the custom table in the ZappySys Driver:
   Here is an example SQL query for ZappySys Driver. You can insert Placeholders also. Read more about placeholders here
   

   SELECT
     "ShipCountry",
     "OrderID",
     "CustomerID",
     "EmployeeID",
     "OrderDate",
     "RequiredDate",
     "ShippedDate",
     "ShipVia",
     "Freight",
     "ShipName",
     "ShipAddress",
     "ShipCity",
     "ShipRegion",
     "ShipPostalCode"
   FROM "Orders"
   Where "ShipCountry"='USA'

   
   

5. That's it now go to Preview Tab and Execute your custom virtual table query. In this example it will extract the orders for the USA Shipping Country only:
   

   SELECT * FROM "vt__usa_orders_only"

   
   

Conclusion

In this article we discussed how to connect to JSON in Azure Data Factory (ADF) and integrate data without any coding. Click here to Download JSON Connector for Azure Data Factory (ADF) and try yourself see how easy it is. If you still have any question(s) then ask here or simply click on live chat icon below and ask our expert (see bottom-right corner of this page).

Download JSON Connector for Azure Data Factory (ADF) Documentation 

Other App Integration scenarios for JSON

Other Connectors for Azure Data Factory (ADF)

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