Analyze Live Bitbucket Data in SAS Viya

SAS Viya is an analytics platform that enhances data management, machine learning, and analytics, fostering efficient decision-making and insights. When paired with CData Connect AI, you get instant, cloud-to-cloud access to Bitbucket data for building predictive models, crafting stunning insights to make data-driven decisions, and more. This article shows how to connect to Connect AI from the SAS Viya cloud platform and integrate live Bitbucket data into your self-service AI and analytics deployments.

CData Connect AI provides a pure SQL, cloud-to-cloud interface for Bitbucket, allowing you to easily integrate with live Bitbucket data in SAS Viya — without replicating the data. CData Connect AI looks exactly like a SQL Server database to SAS Viya and uses optimized data processing out of the box to push all supported SQL operations (filters, JOINs, etc.) directly to Bitbucket, leveraging server-side processing to return Bitbucket data quickly.

Configure Bitbucket Connectivity for SAS Viya

Connectivity to Bitbucket from SAS Viya is made possible through CData Connect AI. To work with Bitbucket data from SAS Viya, we start by creating and configuring a Bitbucket connection.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "Bitbucket" from the Add Connection panel

3. Enter the necessary authentication properties to connect to Bitbucket.

   For most queries, you must set the Workspace. The only exception to this is the Workspaces table, which does not require this property to be set, as querying it provides a list of workspace slugs that can be used to set Workspace. To query this table, you must set Schema to 'Information' and execute the query SELECT * FROM Workspaces>.

   Setting Schema to 'Information' displays general information. To connect to Bitbucket, set these parameters:

   • Schema: To show general information about a workspace, such as its users, repositories, and projects, set this to Information. Otherwise, set this to the schema of the repository or project you are querying. To get a full set of available schemas, query the sys_schemas table.
   • Workspace: Required if you are not querying the Workspaces table. This property is not required for querying the Workspaces table, as that query only returns a list of workspace slugs that can be used to set Workspace.

   Authenticating to Bitbucket

   Bitbucket supports OAuth authentication only. To enable this authentication from all OAuth flows, you must create a custom OAuth application, and set AuthScheme to OAuth.

   Be sure to review the Help documentation for the required connection properties for you specific authentication needs (desktop applications, web applications, and headless machines).

   Creating a custom OAuth application

   From your Bitbucket account:

   1. Go to Settings (the gear icon) and select Workspace Settings.
   2. In the Apps and Features section, select OAuth Consumers.
   3. Click Add Consumer.
   4. Enter a name and description for your custom application.
   5. Set the callback URL:
      • For desktop applications and headless machines, use http://localhost:33333 or another port number of your choice. The URI you set here becomes the CallbackURL property.
      • For web applications, set the callback URL to a trusted redirect URL. This URL is the web location the user returns to with the token that verifies that your application has been granted access.
   6. If you plan to use client credentials to authenticate, you must select This is a private consumer. In the driver, you must set AuthScheme to client.
   7. Select which permissions to give your OAuth application. These determine what data you can read and write with it.
   8. To save the new custom application, click Save.
   9. After the application has been saved, you can select it to view its settings. The application's Key and Secret are displayed. Record these for future use. You will use the Key to set the OAuthClientId and the Secret to set the OAuthClientSecret.
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Bitbucket Connection page and update the User-based permissions.

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to Bitbucket data from SAS Viya.

Connecting to CData Connect AI from SAS Viya

The following steps detail the process of loading data from Bitbucket into SAS Viya using the established connection in CData Connect AI.

1. Download and install the CData Connect AI JDBC driver.
   • Open the Integrations page of CData Connect AI.
   • Search for and select JDBC.
   • Download and run the setup file.
   • When the installation is complete, the JAR file can be found in the installation directory (inside the lib folder).
2. Now, log in to SAS Viya and navigate to the Applications Menu at the top-left corner.
3. Select Develop Code and Flows from the Analytics Life Cycle topic.
4. Navigate to the Explorer tab and click on SAS Server on the left panel.
5. Follow the steps to upload the JAR file of the CData Connect JDBC driver:
   • Right-click on the "Home" directory.
   • Click on Upload files.
   • Place the JAR file in the specified location and note its file path.
6. Once done, navigate to the Libraries tab and click on Create a new library connection (on the top left corner as shown below) for the CData Connect JDBC.
7. Enter the library connection settings:
   • Connection name: enter a name for your connection
   • Library name (libref): enter a reference for your library
   • Library type: choose "SAS/ACCESS to JDBC"
8. Click on the Properties tab and set Library attributes to READONLY.
9. Click the Connection Options tab and enter the following details:
   • Hive JDBC driver's class name: cdata.jdbc.connect.ConnectDriver
   • Java CLASSPATH: enter the file path to the JAR driver file (Refer to Step 5)
10. Click on Test connection. If it succeeds, click on Save and connect.
11. Click on to add a new tab and select SAS program.
12. Fill in the code block below with your setup parameters:
    • Libref: enter the library reference you defined in Step 9.
    • ClassPath: enter the file path to the JAR driver file.
    • Username: enter your CData Connect username. This is displayed in the top-right corner of the CData Connect interface. For example, [email protected].
    • DefaultCatalog: enter the connection configured in CData Connect AI that you want to query.
    • Password: enter the PAT you generated in the "Add a Personal Access Token" section.

    
    libname [Libref] JDBC   
    classpath=[ClassPath]  
    class="cdata.jdbc.connect.ConnectDriver"     
    URL="jdbc:Connect:AuthScheme=Basic;User=[Username];DefaultCatalog=[DefaultCatalog];DefaultSchema=dbo;Password=[PAT]"; 
     
    proc sql; 
    
    SELECT * FROM [Libref].MyTable; 
    
    quit; 
    

13. Click on Run. You can see the data load from CData Connect AI into SAS Viya.

Live Access to Bitbucket Data from Cloud Applications

At this point, you have a direct, cloud-to-cloud connection to Bitbucket data from SAS Viya. You can build predictive models, craft insights to make data-driven decisions, and more — all without replicating Bitbucket data.

Try Connect AI and get real-time data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications.