JSON File Connector for Azure Data Factory (Pipeline) In this article you will learn how to integrate JSON File data in Azure Data Factory (Pipeline) without coding in just a few clicks (live / bi-directional connection to JSON File). JSON File Connector can be used to extract and output JSON data stored in local files or direct JSON String (variables or DB columns). JSON Connector also supports JSONPath to filter data from nested array/sub-documents. This Connector is optimized to work with very large files.. Using JSON File Connector you will be able to connect, read, and write data from within Azure Data Factory (Pipeline). Follow the steps below to see how we would accomplish that. Download Documentation The driver mentioned above 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

Connect to JSON File in other apps Connect to JSON File in SSIS Connect to JSON File in SQL Server Connect to JSON File in Power BI Connect to JSON File in SSRS Connect to JSON File in Informatica Connect to JSON File in MS Access Connect to JSON File in MS Excel Connect to JSON File in SSAS Connect to JSON File in C# Connect to JSON File in Python Connect to JSON File in JAVA Connect to JSON File in Tableau Connect to JSON File in SAP Crystal Reports Connect to JSON File in Azure Data Factory (SSIS) Connect to JSON File in Talend Studio Connect to JSON File in UiPath Connect to JSON File in PowerShell Connect to JSON File in ODBC

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

Step-by-step instructions

To get data from JSON File using Azure Data Factory (Pipeline) we first need to create a DSN (Data Source) which will access data from JSON File. We will later be able to read data using Azure Data Factory (Pipeline). 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. You can use pass single file or multiple file path using wildcard pattern in path and you can use select single file by clicking [...] path button or multiple file using wildcard pattern in path.
   

   Note: If you want to operation with multiple files then use wild card pattern as below 
   (when you use wild card pattern in source path then system will treat target path as folder regardless you end with slash)
   
   C:\SSIS\Test\reponse.json (will read only single reponse.json file)
   C:\SSIS\Test\j*.json (all files starting with file name)
   C:\SSIS\Test\*.json (all files with .json Extension and located under folder subfolder)
   

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 File using ZappySys JSON File Connector

Video instructions

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

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:

    JsonFileDSN

    DSN=JsonFileDSN

    

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:

    

Advanced topics

Create Custom Stored 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 Stored 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 Stored Procedure and write the your desired stored procedure and Save it and it will create the custom stored 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 Stored 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';

   
   

5. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC usp_get_orders @fromdate=''1996-07-30''')

   
   

6. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

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.

If you're dealing with Microsoft Access and need to import data from an SQL query, it's important to note that Access doesn't allow direct import of SQL queries. Instead, you can create custom objects (Virtual Tables) to handle the import process.

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"

   
   

6. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC [usp_get_orders] ''1996-01-01''')

   
   

7. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

Conclusion

In this article we discussed how to connect to JSON File in Azure Data Factory (Pipeline) and integrate data without any coding. Click here to Download JSON File Connector for Azure Data Factory (Pipeline) 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 File Connector for Azure Data Factory (Pipeline) Documentation 

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Download JSON File Connector for Azure Data Factory (Pipeline) Documentation

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