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

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

Install the CData JDBC Driver for AdRoll

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

Start a Spark Shell and Connect to AdRoll Data

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

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

2. With the shell running, you can connect to AdRoll 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 AdRoll Profile on disk (e.g. C:\profiles\AdRoll.apip). Next, set the ProfileSettings connection property to the connection string for AdRoll (see below).

   AdRoll API Profile Settings

   Register a developer account with AdRoll and create an OAuth application to receive a client ID and secret.

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the AdRoll 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 AdRoll, using the connection string generated above.

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

   scala> api_df.registerTable("accounts")

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

   scala> api_df.sqlContext.sql("SELECT Eid, Name FROM Accounts WHERE IsSuspended = false").collect.foreach(println)

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

   

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