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

Upload the CData JDBC Driver for Email to Google Data Fusion

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

Connect to Email Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Email 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-email)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for Email. For example:
     
     jdbc:email:RTK=5246...;User=username@gmail.com;Password=password;Server=imap.gmail.com;Port=993;SMTP Server=smtp.gmail.com;SMTP Port=465;SSL Mode=EXPLICIT;Protocol=IMAP;Mailbox=Inbox;

     The User and Password properties, under the Authentication section, must be set to valid credentials. The Server must be specified to retrieve emails and the SMTPServer must be specified to send emails.

     Built-in Connection String Designer

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

     java -jar cdata.jdbc.email.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 Email, i.e.:
     SELECT * FROM Mailboxes
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 email-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 Email data into

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

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