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

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

Install the CData JDBC Driver in Databricks

To work with live ConstantContact 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 ConstantContact Data in your Notebook: Python

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

Configure the Connection to ConstantContact

Connect to ConstantContact 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\ConstantContact.apip;Authscheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;"

Built-in Connection String Designer

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

Start by setting the Profile connection property to the location of the ConstantContact Profile on disk (e.g. C:\profiles\ConstantContact.apip). Next, set the ProfileSettings connection property to the connection string for Profile (see below).

ConstantContact API Profile Settings

ConstantContact uses OAuth-based authentication.

First, you will need to register an OAuth application with ConstantContact. You can do so from the ConstantContact API Guide (https://v3.developer.constantcontact.com/api_guide/index.html), under "MyApplications" > "New Application". Your Oauth application will be assigned a client id (API Key) and you can generate a client secret (Secret).

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

• AuthScheme: Set this to OAuth.
• InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage the process to obtain the OAuthAccessToken.
• OAuthClientId: Set this to the client_id that is specified in you app settings.
• OAuthClientSecret: Set this to the client_secret that is specified in you app settings.
• CallbackURL: Set this to the Redirect URI you specified in your app settings.

Load ConstantContact Data

Once you configure the connection, you can load ConstantContact 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" , "Contacts") \
	.load ()

Display ConstantContact Data

Check the loaded ConstantContact data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("Id"))

Analyze ConstantContact 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 ConstantContact data for reporting, visualization, and analysis.

% sql

SELECT Id, EmailAddress FROM SAMPLE_VIEW ORDER BY EmailAddress DESC LIMIT 5

The data from ConstantContact 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 ConstantContact data in Databricks. Reach out to our Support Team if you have any questions.