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Build Google Sheets-Connected ETL Processes in Google Data Fusion

Load the CData JDBC Driver into Google Data Fusion and create ETL processes with access live Google Sheets data.

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

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

Upload the CData JDBC Driver for Google Sheets to your Google Data Fusion instance to work with live Google Sheets 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 -.jar. For example: cdata.jdbc.googlesheets-2019.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.googlesheets) and make note of the name
    • Class name: Set the JDBC class name: (cdata.jdbc.googlesheets.GoogleSheetsDriver)
  5. Click "Finish"

Connect to Google Sheets Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Google Sheets 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
    • Set the Label
    • Set Reference Name to a value for any future references (i.e.: cdata-googlesheets)
    • Set Plugin Type to "jdbc"
    • Set Connection String to the JDBC URL for Google Sheets. For example:

      jdbc:googlesheets:RTK=5246...;Spreadsheet=MySheet;InitiateOAuth=GETANDREFRESH;

      You can connect to a spreadsheet by providing authentication to Google and then setting the Spreadsheet connection property to the name or feed link of the spreadsheet. If you want to view a list of information about the spreadsheets in your Google Drive, execute a query to the Spreadsheets view after you authenticate.

      ClientLogin (username/password authentication) has been officially deprecated since April 20, 2012 and is now no longer available. Instead, use the OAuth 2.0 authentication standard. To access Google APIs on behalf on individual users, you can use the embedded credentials or you can register your own OAuth app.

      OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, you will need to register an application to obtain the OAuth JWT values.

      See the Getting Started chapter in the help documentation to connect to Google Sheets from different types of accounts: Google accounts, Google Apps accounts, and accounts using two-step verification.

      To use the JDBC Driver in Google Data Fusion, you will need to set the RTK property in the JDBC URL. You can view the licensing file included in the installation for information on how to set this property.

      Built-in Connection String Designer

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

      java -jar cdata.jdbc.googlesheets.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 Sheets, i.e.:
      SELECT * FROM Orders
  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 googlesheets-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 Sheets data into

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

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