Process & Analyze Dynamics CRM Data in Databricks (AWS)

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 Dynamics CRM data. This article explains how to host the CData JDBC Driver in AWS, as well as connect to and process live Dynamics CRM data in Databricks.

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

Getting Started

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Install the CData JDBC Driver in Databricks

To work with live Dynamics CRM data in Databricks, install the driver on your Databricks 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.dynamicscrm.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).

👁 Loading the JDBC JAR File into AWS

Access Dynamics CRM Data in your Notebook: Python

With the JAR file installed, we are ready to work with live Dynamics CRM 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 Dynamics CRM, and create a basic report.

Configure the Connection to Dynamics CRM

Connect to Dynamics CRM by referencing the JDBC Driver class and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the 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.

Step 1: Connection Information

driver = "cdata.jdbc.dynamicscrm.DynamicsCRMDriver"
url = "jdbc:dynamicscrm:RTK=5246...;User=myuseraccount;Password=mypassword;URL=https://myOrg.crm.dynamics.com/;CRM Version=CRM Online;"

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.

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.

👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)

Load Dynamics CRM Data

Once you configure the connection, you can load Dynamics CRM data as a dataframe using the CData JDBC Driver and the connection information.

Step 2: Reading the data

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

Display Dynamics CRM Data

Check the loaded Dynamics CRM data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("FirstName"))

👁 Displaying Dynamics CRM Data

Analyze Dynamics CRM Data in Databricks

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

Step 4: Create a view or table

remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )

With the Temp View created, you can use SparkSQL to retrieve the Dynamics CRM data for reporting, visualization, and analysis.

% sql

SELECT FirstName, NumberOfEmployees FROM SAMPLE_VIEW ORDER BY NumberOfEmployees DESC LIMIT 5

👁 Displaying Dynamics CRM Data

The data from Dynamics CRM 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 Dynamics CRM and start working with your live Dynamics CRM data in Databricks. Reach out to our Support Team if you have any questions.