Connect to SAS xpt Data in DBVisualizer

The CData JDBC Driver for SAS xpt implements JDBC standards to provide connectivity to SAS xpt data in applications ranging from business intelligence tools to IDEs. This article shows how to establish a connection to SAS xpt data in DBVisualizer and use the table editor to load SAS xpt data.

Create a New JDBC Data Source for SAS xpt Data

Follow the steps below to use the Driver Manager to provide connectivity to SAS xpt data from DBVisualizer tools.

1. In DBVisualizer, click Tools -> Driver Manager -> Create a New Driver.
2. Enter a name for the data source.
3. Enter the following in the URL Format box: jdbc:sasxpt:
   The DBVisualizer Driver Manager.
4. In the User Specified tab, click the Open File button and select the cdata.jdbc.sasxpt.jar file, located in the lib subfolder of the installation directory.
5. In the Driver Class menu, select the SASXptDriver class, cdata.jdbc.sasxpt.SASXptDriver.

Define the Connection to the JDBC Data Source

Follow the steps below to save connection properties in the JDBC URL.

1. In the Database tab, right-click the Database Connection node and click Create a Database Connection.

2. In the Connection section, set the following options:

   • Database Type: If you selected the wizard option, the database type is automatically detected. If you selected the "No Wizard" option, select the Generic or Auto Detect option in the Database Type menu.
   • Driver: Select the driver you just created.

   • Database URL: Enter the full JDBC URL. The syntax of the JDBC URL is jdbc:sasxpt: followed by the connection properties in a semicolon-separated list of name-value pairs.

     Connecting to Local SASXpt Files

     You can connect to local SASXpt file by setting the URI to a folder containing SASXpt files.

     Connecting to S3 data source

     You can connect to Amazon S3 source to read SASXpt files. Set the following properties to connect:

     • URI: Set this to the folder within your bucket that you would like to connect to.
     • AWSAccessKey: Set this to your AWS account access key.
     • AWSSecretKey: Set this to your AWS account secret key.
     • TemporaryLocalFolder: Set this to the path, or URI, to the folder that is used to temporarily download SASXpt file(s).

     Connecting to Azure Data Lake Storage Gen2

     You can connect to ADLS Gen2 to read SASXpt files. Set the following properties to connect:

     • URI: Set this to the name of the file system and the name of the folder which contacts your SASXpt files.
     • AzureAccount: Set this to the name of the Azure Data Lake storage account.
     • AzureAccessKey: Set this to our Azure DataLakeStore Gen 2 storage account access key.
     • TemporaryLocalFolder: Set this to the path, or URI, to the folder that is used to temporarily download SASXpt file(s).

     Built-in Connection String Designer

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

     java -jar cdata.jdbc.sasxpt.jar

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

     When you configure the JDBC URL, you may also want to set the Max Rows connection property. This will limit the number of rows returned, which is especially helpful for improving performance when designing reports and visualizations.

     A typical connection string is below:

     jdbc:sasxpt:URI=C:/folder;
   • Database UserId: The username to use to authenticate to SAS xpt.
   • Database Password: The password to use to authenticate to SAS xpt.

3. On the Connection tab, click Connect.

To browse through tables exposed by the SAS xpt JDBC Driver, right-click a table and click Open in New Tab.

To execute SQL queries, use the SQL Commander tool: Click SQL Commander -> New SQL Commander. Select the Database Connection, Database, and Schema from the available menus.

See the "Supported SQL" chapter in the help documentation for more information on the supported SQL. See the "Data Model" chapter for table-specific information.