Build Google Translate-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 API Driver for JDBC enables users to access live Google Translate data from within their Google Data Fusion pipelines. While the CData JDBC Driver enables piping Google Translate data to any data source natively supported in Google Data Fusion, this article explains how to pipe data from Google Translate to Google BigQuery,

Upload the CData API Driver for JDBC to Google Data Fusion

Upload the CData API Driver for JDBC to your Google Data Fusion instance to work with live Google Translate 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: cdataapi-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.api) and make note of the name
   • Class name: Set the JDBC class name: (cdata.jdbc.api.APIDriver)
   
5. Click "Finish"

Connect to Google Translate Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Google Translate 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-api)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for Google Translate. For example:
     
     jdbc:api:RTK=5246...;Profile=C:\profiles\GoogleTranslate.apip;AuthScheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;

     Authentication

     Google Cloud Translation API requires OAuth 2.0 authentication to ensure secure access to translation services, datasets, glossaries, and adaptive MT resources. This authentication method allows you to securely connect to your Google Cloud project and manage translation resources with proper authorization.

     OAuth 2.0 Setup and Configuration

     Step 1: Create Google Cloud Project and Enable API

     To set up OAuth authentication:

     1. Visit the Google Cloud Console
     2. Create a new project or select an existing project
     3. Note down your Project ID (required for all API calls)
     4. Navigate to "APIs & Services" > "Library"
     5. Search for and enable the "Cloud Translation API"
     6. Go to "APIs & Services" > "Credentials"
     7. Click "Create Credentials" and select "OAuth Client ID"
     8. Configure the OAuth consent screen if prompted
     9. Select "Desktop application" or "Web application" as appropriate
     10. Set the authorized redirect URI (CallbackURL)
     11. Copy the Client ID and Client Secret for use in your connection

     Required Connection Properties

     • AuthScheme: Set this to OAuth (required)
     • OAuthClientId: Client ID from Google Cloud Console (required)
     • OAuthClientSecret: Client secret from Google Cloud Console (required)
     • CallbackURL: Redirect URI specified in your OAuth application (required)
     • InitiateOAuth: Set to GETANDREFRESH for automatic token management (recommended)
     • ProjectId: Your Google Cloud project ID or project number (required for queries)

     Required OAuth Scopes

     The Google Cloud Translation API Profile requires the following OAuth scope:

     • https://www.googleapis.com/auth/cloud-translation - Full access to Cloud Translation API resources including translation, datasets, glossaries, and adaptive MT

     Built-in Connection String Designer

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

           java -jar cdata.jdbc.api.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 Translate, i.e.:
     SELECT * FROM SupportedLanguages
   
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 api-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 Translate data into
   

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

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