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

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

Install the CData JDBC Driver for Bullhorn CRM

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

Start a Spark Shell and Connect to Bullhorn CRM Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for Bullhorn CRM/lib/cdata.jdbc.bullhorncrm.jar
   

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

   Begin by providing your Bullhorn CRM account credentials in the following:

   • DataCenterCode: Set this to the data center code which responds to your data center. Refer to the list of data-center-specific Bullhorn API URLs: https://bullhorn.github.io/Data-Center-URLs/

   If you are uncertain about your data center code, codes like CLS2, CLS21, etc. are cluster IDs that are contained in a user's browser URL (address bar) once they are logged in.

   Example: https://cls21.bullhornstaffing.com/BullhornSTAFFING/MainFrame.jsp?#no-ba... indicates that the logged in user is on CLS21.

   Authenticating with OAuth

   Bullhorn CRM uses the OAuth 2.0 authentication standard. To authenticate using OAuth, create and configure a custom OAuth app. See the Help documentation for more information.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.bullhorncrm.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 Bullhorn CRM, using the connection string generated above.

   scala> val bullhorncrm_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:bullhorncrm:DataCenterCode=CLS33;OAuthClientId=myoauthclientid;OAuthClientSecret=myoauthclientsecret;InitiateOAuth=GETANDREFRESH;").option("dbtable","Candidate").option("driver","cdata.jdbc.bullhorncrm.BullhornCRMDriver").load()
   

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

4. Register the Bullhorn CRM data as a temporary table:

   scala> bullhorncrm_df.registerTable("candidate")

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

   scala> bullhorncrm_df.sqlContext.sql("SELECT Id, CandidateName FROM Candidate WHERE CandidateName = Jane Doe").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 Bullhorn CRM in Apache Spark, you are able to perform fast and complex analytics on Bullhorn CRM 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.