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Work with Workday Data in Apache Spark Using SQL

Access and process Workday Data in Apache Spark using the CData JDBC Driver.

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

The CData JDBC Driver offers unmatched performance for interacting with live Workday data due to optimized data processing built into the driver. 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 (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can work with and analyze Workday data using native data types.

Install the CData JDBC Driver for Workday

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

Start a Spark Shell and Connect to Workday Data

  1. Open a terminal and start the Spark shell with the CData JDBC Driver for Workday JAR file as the jars parameter: $ spark-shell --jars /CData/CData JDBC Driver for Workday/lib/cdata.jdbc.workday.jar
  2. With the shell running, you can connect to Workday with a JDBC URL and use the SQL Context load() function to read a table.

    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

    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.

    java -jar cdata.jdbc.workday.jar

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

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

    scala> val workday_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:workday:User=myuser;Password=mypassword;Tenant=mycompany_gm1;Host=https://wd3-impl-services1.workday.com").option("dbtable","Workers").option("driver","cdata.jdbc.workday.WorkdayDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the Workday data as a temporary table:

    scala> workday_df.registerTable("workers")
  5. Perform custom SQL queries against the Data using commands like the one below:

    scala> workday_df.sqlContext.sql("SELECT Worker_Reference_WID, Legal_Name_Last_Name FROM Workers WHERE Legal_Name_Last_Name = Morgan").collect.foreach(println)

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

Using the CData JDBC Driver for Workday in Apache Spark, you are able to perform fast and complex analytics on Workday data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 200+ CData JDBC Drivers and get started today.