Build Google Data Catalog-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 Google Data Catalog enables users to access live Google Data Catalog data from within their Google Data Fusion pipelines. While the CData JDBC Driver enables piping Google Data Catalog data to any data source natively supported in Google Data Fusion, this article walks through piping data from Google Data Catalog to Google BigQuery,

Upload the CData JDBC Driver for Google Data Catalog to Google Data Fusion

Upload the CData JDBC Driver for Google Data Catalog to your Google Data Fusion instance to work with live Google Data Catalog 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: cdatagoogledatacatalog-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.googledatacatalog) and make note of the name
   • Class name: Set the JDBC class name: (cdata.jdbc.googledatacatalog.GoogleDataCatalogDriver)
5. Click "Finish"

Connect to Google Data Catalog Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Google Data Catalog 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-googledatacatalog)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for Google Data Catalog. For example:
     
     jdbc:googledatacatalog:RTK=5246...;ProjectId=YourProjectId;InitiateOAuth=GETANDREFRESH;

     Google Data Catalog uses the OAuth authentication standard. Authorize access to Google APIs on behalf on individual users or on behalf of users in a domain.

     Before connecting, specify the following to identify the organization and project you would like to connect to:

     • OrganizationId: The ID associated with the Google Cloud Platform organization resource you would like to connect to. Find this by navigating to the cloud console.

       Click the project selection drop-down, and select your organization from the list. Then, click More -> Settings. The organization ID is displayed on this page.

     • ProjectId: The ID associated with the Google Cloud Platform project resource you would like to connect to.

       Find this by navigating to the cloud console dashboard and selecting your project from the Select from drop-down. The project ID will be present in the Project info card.

     When you connect, the OAuth endpoint opens in your default browser. Log in and grant permissions to the application to completes the OAuth process. For more information, refer to the OAuth section in the Help documentation.

     Built-in Connection String Designer

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

     java -jar cdata.jdbc.googledatacatalog.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 Google Data Catalog, i.e.:
     SELECT * FROM Schemas
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 googledatacatalog-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 Google Data Catalog data into

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

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