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

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

Install the CData JDBC Driver for Ontraport

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

Start a Spark Shell and Connect to Ontraport Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for Ontraport/lib/cdata.jdbc.api.jar
   

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

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

   Ontraport API Profile Settings

   In your Ontraport account, navigate to Administration > Integrations > ONTRAPORT API Instructions and Key Manager to obtain both your API Key and App ID.

   Built-in Connection String Designer

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

   

   Configure the connection to Ontraport, using the connection string generated above.

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\Ontraport.apip;ProfileSettings='APIKey=your_api_key;AppId=your_app_id';").option("dbtable","Campaigns").option("driver","cdata.jdbc.api.APIDriver").load()
   

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

4. Register the Ontraport data as a temporary table:

   scala> api_df.registerTable("campaigns")

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

   scala> api_df.sqlContext.sql("SELECT Id, Name FROM Campaigns WHERE Deleted = false").collect.foreach(println)

   You will see the results displayed in the console, similar to the following:

   

Using the CData JDBC Driver for Ontraport in Apache Spark, you are able to perform fast and complex analytics on Ontraport 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.