Process & Analyze ServiceDesk Plus 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 ServiceDesk Plus data. This article explains how to host the CData JDBC Driver in AWS, as well as connect to and process live ServiceDesk Plus data in Databricks.

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

Install the CData JDBC Driver in Databricks

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

Access ServiceDesk Plus Data in your Notebook: Python

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

Configure the Connection to ServiceDesk Plus

Connect to ServiceDesk Plus 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.api.APIDriver"
url = "jdbc:api:RTK=5246...;Profile=C:\profiles\ServiceDeskPlus.apip;ProfileSettings="Portal=itdesk;Domain=.in;Scope=SDPOnDemand.requests.READ SDPOnDemand.problems.READ SDPOnDemand.assets.READ SDPOnDemand.projects.READ";AuthScheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;"

Built-in Connection String Designer

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

java -jar cdata.jdbc.api.jar

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

Using OAuth Authentication

ServiceDeskPlus uses Zoho OAuth 2.0 for secure authentication. To set up OAuth access:

1. Register your application in the Zoho Developer Console at https://api-console.zoho.com
2. Configure your redirect URI to match your application setup
3. Note your Client ID and Client Secret from the application settings

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to OAuth.
• OAuthClientId: Set this to your Zoho application Client ID.
• OAuthClientSecret: Set this to your Zoho application Client Secret.
• Scope: Set this to the required ServiceDeskPlus permissions (default includes read access to requests, problems, assets, and projects).
• Domain: Set this to your ServiceDeskPlus domain
• Portal: Set this to your ServiceDeskPlus portal

Example Connection String

Profile=C:\profiles\ServiceDeskPlus.apip;ProfileSettings="Portal=itdesk;Domain=.in;Scope=SDPOnDemand.requests.READ SDPOnDemand.problems.READ SDPOnDemand.assets.READ SDPOnDemand.projects.READ";AuthScheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;

Load ServiceDesk Plus Data

Once you configure the connection, you can load ServiceDesk Plus 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" , "AnnouncementComments") \
	.load ()

Display ServiceDesk Plus Data

Check the loaded ServiceDesk Plus data by calling the display function.

Step 3: Checking the result

display (remote_table.select (""))

Analyze ServiceDesk Plus 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 ServiceDesk Plus data for reporting, visualization, and analysis.

% sql

SELECT ,  FROM SAMPLE_VIEW ORDER BY  DESC LIMIT 5

The data from ServiceDesk Plus 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 API Driver for JDBC and start working with your live ServiceDesk Plus data in Databricks. Reach out to our Support Team if you have any questions.