YouTube Connector for Azure Data Factory (Pipeline) In this article you will learn how to integrate YouTube data in Azure Data Factory (Pipeline) without coding in just a few clicks (live / bi-directional connection to YouTube). Read / write YouTube data inside your app, perform many Youtube operations without coding using easy to use high performance API Connector for YouTube. Using YouTube 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 YouTube in other apps Connect to YouTube in SSIS Connect to YouTube in SQL Server Connect to YouTube in Power BI Connect to YouTube in SSRS Connect to YouTube in Informatica Connect to YouTube in MS Access Connect to YouTube in MS Excel Connect to YouTube in SSAS Connect to YouTube in C# Connect to YouTube in Python Connect to YouTube in JAVA Connect to YouTube in Tableau Connect to YouTube in SAP Crystal Reports Connect to YouTube in Azure Data Factory (SSIS) Connect to YouTube in Talend Studio Connect to YouTube in UiPath Connect to YouTube in PowerShell Connect to YouTube in ODBC

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

Step-by-step instructions

To get data from YouTube using Azure Data Factory (Pipeline) we first need to create a DSN (Data Source) which will access data from YouTube. 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 API Driver

   ZappySys API 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. When the Configuration window appears give your data source a name if you haven't done that already, then select "YouTube" from the list of Popular Connectors. If "YouTube" is not present in the list, then click "Search Online" and download it. Then set the path to the location where you downloaded it. Finally, click Continue >> to proceed with configuring the DSN:

   YouTubeDSN

   YouTube

   

5. Now it's time to configure the Connection Manager. Select Authentication Type, e.g. Token Authentication. Then select API Base URL (in most cases, the default one is the right one). More info is available in the Authentication section.

    API Key [Http]

   Steps to get YouTube Credentials
   This walkthrough will help you create an API Key which you will be able to use in all requests and authenticate accordingly.

   1. Go to Google API Console
   2. From the Project Dropdown (usually found at the top bar) click Select Project
   3. On Project Popup click CREATE PROJECT
   4. Once project is created you can click Select Project to switch the context (You can click on Notification link or Choose from Top Dropdown)
   5. Click ENABLE APIs AND SERVICES
   6. Now we need to Enable three APIs one by one (YouTube Data API, YouTube Analytics API, YouTube Reporting API).
   7. Search YouTube Data API. Select and click ENABLE
   8. Search YouTube Analytics API. Select and click ENABLE
   9. Search YouTube Reporting API. Select and click ENABLE
   10. Go to back to main screen of Google API Console
   11. Click OAuth Consent Screen Tab. Enter necessary details and Save.
   12. Click Credentials Tab
   13. Click CREATE CREDENTIALS (some where in topbar) and select API key option.
   14. In the popup, copy API Key from the field "Your API key", close this window, and use it in the UI configuration, "key" field

   Fill in all required parameters and set optional parameters if needed:

   YouTubeDSN

   YouTube

   API Key [Http]

   https://youtube.googleapis.com/youtube/v3

   Required Parameters
   key	Fill in the parameter...
   Optional Parameters
   RetryMode	Fill in the parameter...
   RetryStatusCodeList	Fill in the parameter...
   RetryCountMax	Fill in the parameter...
   RetryMultiplyWaitTime	Fill in the parameter...

   

    User Account [OAuth]

   Steps to get YouTube Credentials
   To register a custom app, perform the following steps (detailed steps found in the help link at the end)

   1. Go to Google API Console
   2. From the Project Dropdown (usually found at the top bar) click Select Project
   3. On Project Popup click CREATE PROJECT
   4. Once project is created you can click Select Project to switch the context (You can click on Notification link or Choose from Top Dropdown)
   5. Click ENABLE APIs AND SERVICES
   6. Now we need to Enable three APIs one by one (YouTube Data API, YouTube Analytics API, YouTube Reporting API).
   7. Search YouTube Data API. Select and click ENABLE
   8. Search YouTube Analytics API. Select and click ENABLE
   9. Search YouTube Reporting API. Select and click ENABLE
   10. Go to back to main screen of Google API Console
   11. Click OAuth Consent Screen Tab. Enter necessary details and Save.
   12. Click Credentials Tab
   13. Click CREATE CREDENTIALS (some where in topbar) and select OAuth Client ID option.
   14. When prompted Select Application Type as Desktop App and click Create to receive your ClientID and Secret. Later on you can use this information now to configure Connection.
   15. Go to OAuth Consent Screen tab. Under Publishing Status click PUBLISH APP to ensure your refresh token doesnt expire often. If you planning to use App for Private use then do not have to worry about Verification Status after Publish.

   Fill in all required parameters and set optional parameters if needed:

   YouTubeDSN

   YouTube

   User Account [OAuth]

   https://youtube.googleapis.com/youtube/v3

   Required Parameters
   Optional Parameters
   ClientId	Fill in the parameter...
   ClientSecret	Fill in the parameter...
   Scope	Fill in the parameter...
   RetryMode	Fill in the parameter...
   RetryStatusCodeList	Fill in the parameter...
   RetryCountMax	Fill in the parameter...
   RetryMultiplyWaitTime	Fill in the parameter...
   Redirect URL (Only for Web App)	Fill in the parameter...

   

    Service Account (Using Private Key File) [OAuth]

   Steps to get YouTube Credentials
   Use these steps to authenticate as service account rather than Google / GSuite User. Learn more about service account here

   Basically to call Google API as Service account we need to perform following steps listed in 3 sections (Detailed steps found in the help link at the end)

   Create Project

   First thing is create a Project so we can call Google API. Skip this section if you already have Project (Go to next section)

   1. Go to Google API Console
   2. From the Project Dropdown (usually found at the top bar) click Select Project
   3. On Project Popup click CREATE PROJECT
   4. Once project is created you can click Select Project to switch the context (You can click on Notification link or Choose from Top Dropdown)
   5. Click ENABLE APIs AND SERVICES
   6. Now we need to Enable three APIs one by one (YouTube Data API, YouTube Analytics API, YouTube Reporting API)
   7. Search YouTube Data API. Select and click ENABLE
   8. Search YouTube Analytics API. Select and click ENABLE
   9. Search YouTube Reporting API. Select and click ENABLE

   Create Service Account

   Once Project is created and APIs are enabled we can now create a service account under that project. Service account has its ID which looks like some email ID (not to confuse with Google /Gmail email ID)

   1. Go to Create Service Account
   2. From the Project Dropdown (usually found at the top bar) click Select Project
   3. Enter Service account name and Service account description
   4. For Role, do not select anything for now and Click Continue and then click Done. Next we will create Key.

   Create Key

   Once service account is created we need to create key file (i.e. credentials).

   1. In the Cloud Console, click the email address for the service account that you created.
   2. Click Keys.
   3. Click Add key, then click Create new key.
   4. Click Create and select P12 format. A P12 key file is downloaded to your computer. We will use this file in our API connection.
   5. Click Close.
   6. Now you may use downloaded *.p12 key file as secret file and Service Account Email as Client ID (e.g. some-service-account-name@your-project-id.iam.gserviceaccount.com ).

   Add Permission

   Now last thing is give read/write permission to Service Account. Basically you can create or open Google Sheet and add the Service Account as an editor to it as below.

   1. Copy the email address of your service account we created in previous step (its usually like this some-service-account-name@your-project-id.iam.gserviceaccount.com).
   2. Create or select an existing Google Sheet.
   3. Navigate to Sheet for which you like to give read/write access to Service Account.
   4. Click on the Share button in the top right, and add the email address of the service account as an editor. Here is how to share file(s) with specific people. Juse share with Service Account (use Service Account Email found on previous section)

   Fill in all required parameters and set optional parameters if needed:

   YouTubeDSN

   YouTube

   Service Account (Using Private Key File) [OAuth]

   https://youtube.googleapis.com/youtube/v3

   Required Parameters
   Service Account Email	Fill in the parameter...
   Service Account Private Key Path (i.e. *.p12)	Fill in the parameter...
   Optional Parameters
   Scope	Fill in the parameter...
   RetryMode	Fill in the parameter...
   RetryStatusCodeList	Fill in the parameter...
   RetryCountMax	Fill in the parameter...
   RetryMultiplyWaitTime	Fill in the parameter...

   

6. Once the data source has been configured, you can preview data. Select the Preview tab and use settings similar to the following to preview data:
   

7. Click OK to finish creating the data source.

Video instructions

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

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:

    YouTubeDSN

    DSN=YouTubeDSN

    

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.
   

Actions supported by YouTube Connector

YouTube Connector Examples for Azure Data Factory (Pipeline) Connection

This page offers a collection of SQL examples designed for seamless integration with the ZappySys API ODBC Driver under ODBC Data Source (36/64) or ZappySys Data Gateway, enhancing your ability to connect and interact with Prebuilt Connectors effectively.

SELECT * FROM MyVideos

SELECT * FROM MyChannels

SELECT * FROM MyPlaylists

SELECT * FROM get_comments WITH (videoId='INPUT_YOUR_VIDEO_ID')

SELECT * FROM get_comments WITH (channelId='INPUT_YOUR_CHANNEL_ID')

SELECT * FROM MyPlaylists

SELECT * FROM get_playlists WITH (channelId='UCVGOyzms_XJNk_DHqrffXCw')

SELECT * FROM search WITH (q='ZappySys Tutorials', maxResults='50')

SELECT * FROM search WITH (q='GPU', maxResults='50', channelId='UCXuqSBlHAE6Xw-yeJA0Tunw')

SELECT *
FROM get_channels
WITH(
	  id='UC2d5diIOoCEa47p4PjpIHya,AC2d5diIOoCEa47p4PjpIHyQ,TC2d5diIOoCEa47p4PjpIHyI'
)

SELECT *
FROM get_report
WITH(
	  ids='channel==ENTER_CHANNEL_ID'
	, metrics='likes~shares~views'
	, startDate='2022-08-01'
	, endDate='2022-08-30'
)

SELECT *
FROM get_report
WITH(
      ids='channel==MINE'
    , metrics='likes~shares~views'
    , startDate='yearstart' --OR put date like '2022-08-01'
    , endDate='today' --OR put date like '2022-08-01'
    , dimensions='country'
)

Conclusion

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

More integrations

Other application integration scenarios for YouTube

SSIS

SQL Server

Power BI

SSRS

Informatica

MS Access

MS Excel

SSAS

C#

Python

JAVA

Tableau

SAP Crystal Reports

Azure Data Factory (SSIS)

Talend Studio

UiPath

PowerShell

ODBC

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Google BigQuery

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Google Drive

Google Sheets

Hubspot

Jira

Mailchimp

ManagedEngine ServiceDesk Plus (Zoho)

Nativo

OData

OneDrive

Outlook Mail (Office 365)

Power BI

ServiceNow

SharePoint Online

Shopify

Smartsheet

Stripe

YouTube

Zendesk

Zoho CRM

Zoho SalesIQ

Zoom

REST API

JSON

JSON File

XML

SOAP

XML File

JDBC-ODBC Bridge

Salesforce

CSV

Amazon S3 JSON File

Amazon S3 XML File

Amazon S3 CSV File

Azure Blob JSON File

Azure Blob XML File

Azure Blob CSV File

FTP/SFTP JSON File

FTP/SFTP XML File

FTP/SFTP CSV File

Build your own Custom API Connector

Download YouTube Connector for Azure Data Factory (Pipeline) Documentation

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