Build Bitbucket-Connected ETL Processes in Google Data Fusion

Google Data Fusion allows users to perform self-service data integration to consolidate disparate data. Uploading the CData JDBC Driver for Bitbucket enables users to access live Bitbucket data from within their Google Data Fusion pipelines. While the CData JDBC Driver enables piping Bitbucket data to any data source natively supported in Google Data Fusion, this article walks through piping data from Bitbucket to Google BigQuery,

Upload the CData JDBC Driver for Bitbucket to Google Data Fusion

Upload the CData JDBC Driver for Bitbucket to your Google Data Fusion instance to work with live Bitbucket data. Due to the naming restrictions for JDBC drivers in Google Data Fusion, create a copy or rename the JAR file to match the following format driver-version.jar. For example: cdatabitbucket-2020.jar

1. Open your Google Data Fusion instance
2. Click the to add an entity and upload a driver
3. On the "Upload driver" tab, drag or browse to the renamed JAR file.
4. On the "Driver configuration" tab:
   • Name: Create a name for the driver (cdata.jdbc.bitbucket) and make note of the name
   • Class name: Set the JDBC class name: (cdata.jdbc.bitbucket.BitbucketDriver)
5. Click "Finish"

Connect to Bitbucket Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Bitbucket data in Google Data Fusion Pipelines.

1. Navigate to the Pipeline Studio to create a new Pipeline
2. From the "Source" options, click "Database" to add a source for the JDBC Driver
3. Click "Properties" on the Database source to edit the properties

   NOTE: To use the JDBC Driver in Google Data Fusion, you will need a license (full or trial) and a Runtime Key (RTK). For more information on obtaining this license (or a trial), contact our sales team.

   • Set the Label
   • Set Reference Name to a value for any future references (i.e.: cdata-bitbucket)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for Bitbucket. For example:
     
     jdbc:bitbucket:RTK=5246...;Workspace=myworkspaceslug;Schema=InformationInitiateOAuth=GETANDREFRESH;

     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.

     Built-in Connection String Designer

     For assistance in constructing the JDBC URL, use the connection string designer built into the Bitbucket JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

     java -jar cdata.jdbc.bitbucket.jar

     Fill in the connection properties and copy the connection string to the clipboard.

   • Set Import Query to a SQL query that will extract the data you want from Bitbucket, i.e.:
     SELECT * FROM Issues
4. From the "Sink" tab, click to add a destination sink (we use Google BigQuery in this example)
5. Click "Properties" on the BigQuery sink to edit the properties
   • Set the Label
   • Set Reference Name to a value like bitbucket-bigquery
   • Set Project ID to a specific Google BigQuery Project ID (or leave as the default, "auto-detect")
   • Set Dataset to a specific Google BigQuery dataset
   • Set Table to the name of the table you wish to insert Bitbucket data into

With the Source and Sink configured, you are ready to pipe Bitbucket data into Google BigQuery. Save and deploy the pipeline. When you run the pipeline, Google Data Fusion will request live data from Bitbucket and import it into Google BigQuery.

While this is a simple pipeline, you can create more complex Bitbucket pipelines with transforms, analytics, conditions, and more. Download a free, 30-day trial of the CData JDBC Driver for Bitbucket and start working with your live Bitbucket data in Google Data Fusion today.