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

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

Getting Started

---

Install the CData JDBC Driver for Dynamics CRM

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

Start a Spark Shell and Connect to Dynamics CRM Data

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

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

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

   The connection string options meet the authentication and connection requirements of different Dynamics CRM instances. To connect to your instance, set the User and Password properties, under the Authentication section, to valid Dynamics CRM user credentials and set the Url to a valid Dynamics CRM server organization root. Additionally, set the CRMVersion property to 'CRM2011+' or 'CRMOnline'. IFD configurations are supported as well; set InternetFacingDeployment to true.

   Additionally, you can provide the security token service (STS) or AD FS endpoint in the STSURL property. This value can be retrieved with the GetSTSUrl stored procedure. Office 365 users can connect to the default STS URL by simply setting CRMVersion.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.dynamicscrm.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 Dynamics CRM, using the connection string generated above.

   scala> val dynamicscrm_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:dynamicscrm:User=myuseraccount;Password=mypassword;URL=https://myOrg.crm.dynamics.com/;CRM Version=CRM Online;").option("dbtable","Account").option("driver","cdata.jdbc.dynamicscrm.DynamicsCRMDriver").load()
   

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

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

   scala> dynamicscrm_df.registerTable("account")

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

   scala> dynamicscrm_df.sqlContext.sql("SELECT FirstName, NumberOfEmployees FROM Account WHERE FirstName = Bob").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 Dynamics CRM in Apache Spark, you are able to perform fast and complex analytics on Dynamics 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.