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

Upload the CData JDBC Driver for Oracle to Google Data Fusion

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

Connect to Oracle Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Oracle 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-oracleoci)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for Oracle. For example:
     
     jdbc:oracleoci:RTK=5246...;User=myuser;Password=mypassword;Server=localhost;Port=1521;

     To connect to Oracle, you'll first need to update your PATH variable and ensure it contains a folder location that includes the native DLLs. The native DLLs can be found in the lib folder inside the installation directory. Once you've done this, set the following to connect:

     • Port: The port used to connect to the server hosting the Oracle database.
     • User: The user Id provided for authentication with the Oracle database.
     • Password: The password provided for authentication with the Oracle database.
     • Service Name: The service name of the Oracle database.

     Built-in Connection String Designer

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

     java -jar cdata.jdbc.oracleoci.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 Oracle, i.e.:
     SELECT * FROM Customers
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 oracleoci-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 Oracle data into

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

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