How to work with UKG Pro WFM 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 UKG Pro WFM, Spark can work with live UKG Pro WFM data. This article describes how to connect to and query UKG Pro WFM data from a Spark shell.

The CData JDBC Driver offers unmatched performance for interacting with live UKG Pro WFM data due to optimized data processing built into the driver. When you issue complex SQL queries to UKG Pro WFM, the driver pushes supported SQL operations, like filters and aggregations, directly to UKG Pro WFM 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 UKG Pro WFM data using native data types.

Install the CData JDBC Driver for UKG Pro WFM

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

Start a Spark Shell and Connect to UKG Pro WFM Data

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

   
   $ spark-shell --jars /CData/CData JDBC Driver for UKG Pro WFM/lib/cdata.jdbc.api.jar
   

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

   Start by setting the Profile connection property to the location of the UKGProWFM Profile on disk (e.g. C:\profiles\UKGProWFM.apip). Next, set the ProfileSettings connection property to the connection string for UKGProWFM (see below).

   UKGProWFM API Profile Settings

   UKG Pro Workforce Management uses OAuth 2.0 with the Resource Owner Password Credentials grant (grant_type=password) to authorize access to the API. Unlike most OAuth-based profiles, this does not use a browser redirect/authorization-code step: the driver exchanges your UKG Pro WFM username, password, client ID, and client secret directly for an access token.

   Set the following connection properties to authenticate:

   • AuthScheme: Set this to OAuthPassword.
   • Host: Set this to the hostname of your UKG Pro Workforce Management datacenter/tenant (for example, yourcompany.mykronos.com). Do not include the protocol (https://) or a trailing slash.
   • OAuthClientId: Set this to the client ID issued for your UKG Pro Workforce Management OAuth application.
   • OAuthClientSecret: Set this to the client secret issued for your UKG Pro Workforce Management OAuth application.
   • User: Set this to your UKG Pro Workforce Management username.
   • Password: Set this to your UKG Pro Workforce Management password.

   Access tokens are obtained from https://{Host}/api/authentication/access_token. Refresh tokens issued by UKG Pro Workforce Management expire after 7 days; if a refresh attempt fails because the refresh token itself has expired, the driver must re-authenticate with your User/Password credentials to obtain a new access token.

   Built-in Connection String Designer

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

   
   java -jar cdata.jdbc.api.jar
   

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

   

   Configure the connection to UKG Pro WFM, using the connection string generated above.

   
   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\UKGProWFM.apip;AuthScheme=OAuthPassword;ProfileSettings='Host=yourcompany.mykronos.com;User=your_username;Password=your_password;';OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;").option("dbtable","Employees").option("driver","cdata.jdbc.api.APIDriver").load()
   

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

4. Register the UKG Pro WFM data as a temporary table:

   scala> api_df.registerTable("employees")

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

   scala> api_df.sqlContext.sql("SELECT PersonNumber, UserName FROM Employees WHERE PersonId = 12345").collect.foreach(println)

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

   

Using the CData JDBC Driver for UKG Pro WFM in Apache Spark, you are able to perform fast and complex analytics on UKG Pro WFM 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.