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

Upload the CData JDBC Driver for CSV to Google Data Fusion

Upload the CData JDBC Driver for CSV to your Google Data Fusion instance to work with live CSV 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: cdatacsv-2020.jar

1. Open your Google Data Fusion instance
2. Click the to add an entity and upload a driver 👁 Image
   
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.csv) and make note of the name
   • Class name: Set the JDBC class name: (cdata.jdbc.csv.CSVDriver)
   👁 Configuring the driver (Salesforce is shown.)
   
5. Click "Finish"

Connect to CSV Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live CSV 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 👁 Adding a database source
   
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-csv)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for CSV. For example:
     
     jdbc:csv:RTK=5246...;URI=/PATH/TO/MyCSVFilesFolder;

     Connecting to Local or Cloud-Stored (Box, Google Drive, Amazon S3, SharePoint) CSV Files

     CData Drivers let you work with CSV files stored locally and stored in cloud storage services like Box, Amazon S3, Google Drive, or SharePoint, right where they are.

     Setting connection properties for local files

     Set the URI property to local folder path.

     Setting connection properties for files stored in Amazon S3

     To connect to CSV file(s) within Amazon S3, set the URI property to the URI of the Bucket and Folder where the intended CSV files exist. In addition, at least set these properties:

     • AWSAccessKey: AWS Access Key (username)
     • AWSSecretKey: AWS Secret Key

     Setting connection properties for files stored in Box

     To connect to CSV file(s) within Box, set the URI property to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect to Box.

     Dropbox

     To connect to CSV file(s) within Dropbox, set the URI proprerty to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect to Dropbox. Either User Account or Service Account can be used to authenticate.

     SharePoint Online (SOAP)

     To connect to CSV file(s) within SharePoint with SOAP Schema, set the URI proprerty to the URI of the document library that includes the intended CSV file. Set User, Password, and StorageBaseURL.

     SharePoint Online REST

     To connect to CSV file(s) within SharePoint with REST Schema, set the URI proprerty to the URI of the document library that includes the intended CSV file. StorageBaseURL is optional. If not set, the driver will use the root drive. OAuth is used to authenticate.

     Google Drive

     To connect to CSV file(s) within Google Drive, set the URI property to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect and set InitiateOAuth to GETANDREFRESH.

     Built-in Connection String Designer

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

      java -jar cdata.jdbc.csv.jar
      

     Fill in the connection properties and copy the connection string to the clipboard.

     👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
     
   • Set Import Query to a SQL query that will extract the data you want from CSV, i.e.:
     SELECT * FROM Customer
   👁 Configuring the database source
   
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 csv-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 CSV data into
   👁 Configuring the BigQuery sink
   

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

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