Build SAS Data Sets-Connected ETL Processes in Google Data Fusion

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SAS Data Sets JDBC Driver

Rapidly create and deploy powerful Java applications that integrate with SAS Data Sets.



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

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

Upload the CData JDBC Driver for SAS Data Sets to Google Data Fusion

Upload the CData JDBC Driver for SAS Data Sets to your Google Data Fusion instance to work with live SAS Data Sets 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: cdatasasdatasets-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.sasdatasets) and make note of the name
    • Class name: Set the JDBC class name: (cdata.jdbc.sasdatasets.SASDataSetsDriver)
  5. Click "Finish"

Connect to SAS Data Sets Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live SAS Data Sets 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-sasdatasets)
    • Set Plugin Type to "jdbc"
    • Set Connection String to the JDBC URL for SAS Data Sets. For example:

      jdbc:sasdatasets:RTK=5246...;URI=C:/myfolder;

      Set the following connection properties to connect to your SAS DataSets files:

      • URI: Set this to the folder containing your .sas7bdat resources. Currently we only support local files.

      Built-in Connection String Designer

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

      java -jar cdata.jdbc.sasdatasets.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 SAS Data Sets, i.e.:
      SELECT * FROM restaurants
  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 sasdatasets-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 SAS Data Sets data into

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

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