Process & Analyze Act 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 Act CRM data. This article walks through hosting the CData JDBC Driver in AWS, as well as connecting to and processing live Act CRM data in Databricks.

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

Install the CData JDBC Driver in Databricks

To work with live Act 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.actcrm.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).

Access Act CRM Data in your Notebook: Python

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

Configure the Connection to Act CRM

Connect to Act 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 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.

Step 1: Connection Information

driver = "cdata.jdbc.actcrm.ActCRMDriver"
url = "jdbc:actcrm:RTK=5246...;URL=https://myActCRMserver.com;User=myUser;Password=myPassword;ActDatabase=MyDB;"

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Act CRM 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.

The User and Password properties, under the Authentication section, must be set to valid Act! user credentials. In addition to the authentication values, see the following:

• Connecting to Act! Premium

  In addition to the authentication values, the URL to Act! is also required; for example https://eup1-iis-04.eu.hosted.act.com/.

  Additionally, you must specify the ActDatabase you will connect to. This is found by going to the About Act! Premium menu of your account, at the top right of the page, in the ? menu. Use the Database Name in the window that appears.

• Connecting to Act! Premium Cloud

  To connect to your Act! Premium Cloud account, you also need to specify the ActCloudName property. This property is found in the URL address of the Cloud account; for example https://eup1-iis-04.eu.hosted.act.com/ActCloudName/.

Note that retrieving ActCRM metadata can be expensive. It is advised that you set the CacheMetadata property to store the metadata locally.

Load Act CRM Data

Once you configure the connection, you can load Act 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" , "Activities") \
	.load ()

Display Act CRM Data

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

Step 3: Checking the result

display (remote_table.select ("ActivityDisplayName"))

Analyze Act 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 Act CRM data for reporting, visualization, and analysis.

% sql

SELECT ActivityDisplayName, Subject FROM SAMPLE_VIEW ORDER BY Subject DESC LIMIT 5

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