How to work with PingOne Data in Apache Spark using SQL

Apache Spark is a fast and general engine for large-scale data processing. When paired with the CData JDBC Driver for PingOne, Spark can work with live PingOne data. This article describes how to connect to and query PingOne data from a Spark shell.

The CData JDBC Driver offers unmatched performance for interacting with live PingOne data due to optimized data processing built into the driver. When you issue complex SQL queries to PingOne, the driver pushes supported SQL operations, like filters and aggregations, directly to PingOne and utilizes the embedded SQL engine to process unsupported operations (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can work with and analyze PingOne data using native data types.

Install the CData JDBC Driver for PingOne

Download the CData JDBC Driver for PingOne installer, unzip the package, and run the JAR file to install the driver.

Start a Spark Shell and Connect to PingOne Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for PingOne JAR file as the jars parameter:

   $ spark-shell --jars /CData/CData JDBC Driver for PingOne/lib/cdata.jdbc.pingone.jar
   

2. With the shell running, you can connect to PingOne with a JDBC URL and use the SQL Context load() function to read a table.

   To connect to PingOne, configure these properties:

   • : The region where the data for your PingOne organization is being hosted.
   • : The type of authentication to use when connecting to PingOne.
   • Either (required when using the default PingOne domain) or , configured as described below.

   Configuring WorkerAppEnvironmentId

   is the ID of the PingOne environment in which your Worker application resides. This parameter is used only when the environment is using the default PingOne domain (auth.pingone). It is configured after you have created the custom OAuth application you will use to authenticate to PingOne, as described in Creating a Custom OAuth Application in the Help documentation.

   First, find the value for this property:

   1. From the home page of your PingOne organization, move to the navigation sidebar and click Environments.
   2. Find the environment in which you have created your custom OAuth/Worker application (usually Administrators), and click Manage Environment. The environment's home page displays.
   3. In the environment's home page navigation sidebar, click Applications.
   4. Find your OAuth or Worker application details in the list.
   5. Copy the value in the Environment ID field. It should look similar to:
      

      WorkerAppEnvironmentId='11e96fc7-aa4d-4a60-8196-9acf91424eca'

   Now set to the value of the Environment ID field.

   Configuring AuthorizationServerURL

   is the base URL of the PingOne authorization server for the environment where your application is located. This property is only used when you have set up a custom domain for the environment, as described in the PingOne platform API documentation. See Custom Domains.

   Authenticating to PingOne with OAuth

   PingOne supports both OAuth and OAuthClient authentication. In addition to performing the configuration steps described above, there are two more steps to complete to support OAuth or OAuthCliet authentication:

   • Create and configure a custom OAuth application, as described in Creating a Custom OAuth Application in the Help documentation.
   • To ensure that the driver can access the entities in Data Model, confirm that you have configured the correct roles for the admin user/worker application you will be using, as described in Administrator Roles in the Help documentation.
   • Set the appropriate properties for the authscheme and authflow of your choice, as described in the following subsections.

   OAuth (Authorization Code grant)

   Set to OAuth.

   Desktop Applications

   Get and Refresh the OAuth Access Token

   After setting the following, you are ready to connect:

   • : GETANDREFRESH. To avoid the need to repeat the OAuth exchange and manually setting the each time you connect, use .
   • : The Client ID you obtained when you created your custom OAuth application.
   • : The Client Secret you obtained when you created your custom OAuth application.
   • : The redirect URI you defined when you registered your custom OAuth application. For example: https://localhost:3333

   When you connect, the driver opens PingOne's OAuth endpoint in your default browser. Log in and grant permissions to the application. The driver then completes the OAuth process:

   1. The driver obtains an access token from PingOne and uses it to request data.
   2. The OAuth values are saved in the location specified in , to be persisted across connections.

   The driver refreshes the access token automatically when it expires.

   For other OAuth methods, including Web Applications, Headless Machines, or Client Credentials Grant, refer to the Help documentation.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.pingone.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.)
   

   Configure the connection to PingOne, using the connection string generated above.

   scala> val pingone_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:pingone:AuthScheme=OAuth;WorkerAppEnvironmentId=eebc33a8-xxxx-4f3a-yyyy-d3e5262fd49e;Region=NA;OAuthClientId=client_id;OAuthClientSecret=client_secret;InitiateOAuth=GETANDREFRESH;").option("dbtable","[CData].[Administrators].Users").option("driver","cdata.jdbc.pingone.PingOneDriver").load()
   

3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the PingOne data as a temporary table:

   scala> pingone_df.registerTable("[cdata].[administrators].users")

5. Perform custom SQL queries against the Data using commands like the one below:

   scala> pingone_df.sqlContext.sql("SELECT Id, Username FROM [CData].[Administrators].Users WHERE EmployeeType = Contractor").collect.foreach(println)

   You will see the results displayed in the console, similar to the following:

   👁 Data in Apache Spark (Salesforce is shown)
   

Using the CData JDBC Driver for PingOne in Apache Spark, you are able to perform fast and complex analytics on PingOne data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the hundreds of CData JDBC Drivers and get started today.