How to connect and process Workday Data from Azure Databricks

Databricks is a cloud-based service that provides data processing capabilities through Apache Spark. When paired with the CData JDBC Driver, customers can use Databricks to perform data engineering and data science on live Workday data. This article walks through hosting the CData JDBC Driver in Azure, as well as connecting to and processing live Workday data in Databricks.

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

Install the CData JDBC Driver in Azure

To work with live Workday data in Databricks, install the driver on your Azure cluster.

1. Navigate to your Databricks administration screen and select the target cluster.
2. On the Libraries tab, click "Install New."
3. Select "Upload" as the Library Source and "Jar" as the Library Type.
4. Upload the JDBC JAR file (cdata.jdbc.workday.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).

Connect to Workday from Databricks

With the JAR file installed, we are ready to work with live Workday data in Databricks. Start by creating a new notebook in your workspace. Name the notebook, select Python as the language (though Scala is available as well), and choose the cluster where you installed the JDBC driver. When the notebook launches, we can configure the connection, query Workday, and create a basic report.

Configure the Connection to Workday

Connect to Workday by referencing the class for the JDBC Driver and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the RTK property in the JDBC URL (unless you are using a Beta driver). You can view the licensing file included in the installation for information on how to set this property.

driver = "cdata.jdbc.workday.WorkdayDriver"
url = "jdbc:workday:RTK=5246...;User=myuser;Password=mypassword;Tenant=mycompany_gm1;Host=https://wd3-impl-services1.workday.com"

Built-in Connection String Designer

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

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

To connect, there are three pieces of information required: Authentication, API URL, and WSDL URL.

Authentication

To authenticate, specify your User and Password. Note that you must append your Tenant to your User separated by an '@' character. For instance, if you normally log in with 'geraldg' and your Tenant is 'mycompany_mc1', then your User should be specified as 'geraldg@mycompany_mc1'.

API URL

The API URL may be specified either directly via APIURL, or it may be constructed from the Tenant, Service, and Host. The APIURL is constructed in the following format: <Host>/ccx/service/<Tenant>/<Service>.

WSDL URL

The WSDLURL may be specified in its entirety, or may be constructed from the Service and WSDLVersion connection properties. The WSDLURL is constructed in the following format: https://community.workday.com/sites/default/files/file-hosting/productionapi/<Service>/<WSDLVersion>/<Service>.wsdl

Load Workday Data

Once the connection is configured, you can load Workday data as a dataframe using the CData JDBC Driver and the connection information.

remote_table = spark.read.format ( "jdbc" ) \
	.option ( "driver" , driver) \
	.option ( "url" , url) \
	.option ( "dbtable" , "Workers") \
	.load ()

Display Workday Data

Check the loaded Workday data by calling the display function.

display (remote_table.select ("Worker_Reference_WID"))

Analyze Workday Data in Azure Databricks

If you want to process data with Databricks SparkSQL, register the loaded data as a Temp View.

remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )

The SparkSQL below retrieves the Workday data for analysis.

% sql

SELECT Worker_Reference_WID, Legal_Name_Last_Name FROM Workers WHERE Legal_Name_Last_Name = 'Morgan'

The data from Workday is only available in the target notebook. If you want to use it with other users, save it as a table.

remote_table.write.format ( "parquet" ) .saveAsTable ( "SAMPLE_TABLE" )

Download a free, 30-day trial of the CData JDBC Driver for Workday and start working with your live Workday data in Azure Databricks. Reach out to our Support Team if you have any questions.