Access Live Azure Data Lake Storage Data in TIBCO Data Virtualization

TIBCO Data Virtualization (TDV) is an enterprise data virtualization solution that orchestrates access to multiple and varied data sources. When paired with the Azure Data Lake Storage Tibco DV Adapter, you get federated access to live Azure Data Lake Storage data directly within TIBCO Data Virtualization. This article explains how to deploy an adapter and create a new data source based on Azure Data Lake Storage.

With built-in optimized data processing, the CData TIBCO DV Adapter offers unmatched performance for interacting with live Azure Data Lake Storage data. When you issue complex SQL queries to Azure Data Lake Storage, the adapter pushes supported SQL operations, like filters and aggregations, directly to Azure Data Lake Storage. Its built-in dynamic metadata querying allows you to work with and analyze Azure Data Lake Storage data using native data types.

Deploy the Azure Data Lake Storage TIBCO DV Adapter

1. In a console, navigate to the bin folder in the TDV Server installation directory. If there is a current version of the adapter installed, you will need to undeploy it.

   .\server_util.bat -server localhost -user admin -password ******** -undeploy -version 1 -name ADLS
   

2. Extract the CData TIBCO DV Adapter to a local folder and deploy the JAR file (tdv.adls.jar) to the server from the extract location.

   .\server_util.bat -server localhost -user admin -password ******** -deploy -package /PATH/TO/tdv.adls.jar
   

You may need to restart the server to ensure the new JAR file is loaded properly, which can be accomplished by running the composite.bat script located at: C:\Program Files\TIBCO\TDV Server <version>\bin. Note that reauthenticating to the TDV Studio is required after restarting the server.

Sample Restart Call

.\composite.bat monitor restart

Authenticate with Azure Data Lake Storage Using OAuth

Since Azure Data Lake Storage authenticates using the OAuth protocol and TDV Studio does not support browser-based authentication internally, you will need to create and run a simple Java application to retrieve the OAuth tokens. Once retrieved, the tokens are used to connect to Azure Data Lake Storage directly from the adapter.

Create the Java Application

1. Create a new Java file with preferred name for example GenOAuthSettings.java. This Java file leverages the ADLSOAuth class contained within the TDV Adapter JAR to initiate a test connection and perform the required OAuth authentication flow
2. Copy and insert the following code into the .java file:

public class GenOAuthSettings {
 public static void main(String[] args) {
 try {
 	 if (args.length != 2) {
 			throw new Exception("Input must have two arguments: 'data source', 'connection string'");
 		}
 
 		String source = args[0].replace(" ", "").toLowerCase();
 		String connectionString = args[1];
 		String prefix;
 
 		if (source.equals("adls")) {
 			prefix = "jdbc:adls:";
 
 			com.cdata.cis.adls.ADLSOAuth oauth = new com.cdata.cis.adls.ADLSOAuth();
 
 			if (!connectionString.startsWith(prefix)) connectionString = prefix + connectionString;
 			oauth.generateOAuthSettingsFile(connectionString);
 		}
 		// More sources can be added below using the same format. You must add the import statement and ensure the jar file resides in the classpath
			// else if (source.equals("googlebigquery") || source.equals("bigquery")) {
			// prefix = "jdbc:googlebigquery:";
			//
			// com.cdata.cis.googlebigquery.GoogleBigQueryOAuth oauth = new com.cdata.cis.googlebigquery.GoogleBigQueryOAuth();
			//
			// if (!connectionString.startsWith(prefix)) connectionString = prefix + connectionString;
			// oauth.generateOAuthSettingsFile(connectionString);
			// }
 		else {
				throw new Exception("Data Source not supported. Available Data Sources: Azure Data Lake Storage");
			}
			
			System.out.println("Test Connection Successful!");
		} catch (Exception e) {
			e.printStackTrace();
		}
	}
}

3. Place the .java file in the same directory as the tdv.adls.jar file. This is required to prevent classpath resolution errors during compilation and execution

Build and run the Java Application

1. Open Console and navigate to the directory containing the .java file and adapter jar
2. Compile the Java file using the following command:

javac -cp .;tdv.adls.jar GenOAuthSettings.java

3. Execute the application using one of the following commands:

java -cp .;tdv.adls.jar GenOAuthSettings "ADLS" "connection string"

This command initiates the OAuth authentication flow and generates the OAuth settings file at the location specified in the OAuthSettingsLocation parameter. Once you deploy the adapter and authenticate, you can create a new data source for Azure Data Lake Storage in TDV Studio.

Create a Azure Data Lake Storage Data Source in TDV Studio

With the Azure Data Lake Storage Tibco DV Adapter, you can easily create a data source for Azure Data Lake Storage and introspect the data source to add resources to TDV.

Create the Data Source

1. Right-click on the folder you wish to add the data source to and select New -> New Data Source
2. Scroll until you find the adapter (e.g. Azure Data Lake Storage) and click Next
3. Name the data source (e.g. CData Azure Data Lake Storage Source)
4. Fill in the required connection properties

Authenticating to a Gen 1 DataLakeStore Account

Gen 1 uses OAuth 2.0 in Entra ID (formerly Azure AD) for authentication.

For this, an Active Directory web application is required. You can create one as follows:

1. Sign in to your Azure Account through the
2. Select "Entra ID" (formerly Azure AD).
3. Select "App registrations".
4. Select "New application registration".
5. Provide a name and URL for the application. Select Web app for the type of application you want to create.
6. Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
7. Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

To authenticate against a Gen 1 DataLakeStore account, the following properties are required:

• Schema: Set this to ADLSGen1.
• Account: Set this to the name of the account.
• OAuthClientId: Set this to the application Id of the app you created.
• OAuthClientSecret: Set this to the key generated for the app you created.
• TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
• Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

Authenticating to a Gen 2 DataLakeStore Account

To authenticate against a Gen 2 DataLakeStore account, the following properties are required:

• Schema: Set this to ADLSGen2.
• Account: Set this to the name of the account.
• FileSystem: Set this to the file system which will be used for this account.
• AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
• Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

NOTE: Ensure that the OAuthSettingsLocation property in the DV Adapter is set to the same file path used during the OAuth authentication process. Additionally, set the InitiateOAuth property to REFRESH so that the adapter can automatically handle OAuth access-token refreshes in the background without requiring any user action.

👁 Filling in Connection Information (Salesforce is shown.)

5. Click Create & Close.

Introspect the Data Source

Once the data source is created, you can introspect the data source by right-clicking and selecting Open. In the dashboard, click Add/Remove Resources and select the Tables, Views, and Stored Procedures to include as part of the data source. Click Next and Finish to add the selected Azure Data Lake Storage tables, views, and stored procedures as resources.

After creating and introspecting the data source, you are ready to work with Azure Data Lake Storage data in TIBCO Data Virtualization just like you would any other relational data source. You can create views, query using SQL, publish the data source, and more.