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

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

Install the CData JDBC Driver for Unbounce

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

Start a Spark Shell and Connect to Unbounce Data

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

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

2. With the shell running, you can connect to Unbounce 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 Unbounce Profile on disk (e.g. C:\profiles\Unbounce.apip).

   Next, set the ProfileSettings connection property to the connection string for Unbounce (see below).

   Unbounce API Profile Settings

   Unbounce uses OAuth to authenticate to your data.

   In order to authenticate to Unbounce, you will first need to register an OAuth application. To do so, go to https://developer.unbounce.com/getting_started/ and complete the Register OAuth Application form.

   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 your app settings.
   • OAuthClientSecret: Set this to Client Secret that is specified in your app settings.
   • CallbackURL: Set this to the Redirect URI you specified in your app settings.

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the Unbounce 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 the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
   

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

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\Unbounce.apip;Authscheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;").option("dbtable","Tags").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 Unbounce data as a temporary table:

   scala> api_df.registerTable("tags")

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

   scala> api_df.sqlContext.sql("SELECT Id, Name FROM Tags WHERE State = active").collect.foreach(println)

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

   👁 Data in Apache Spark (Salesforce is shown)
   

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