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

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

Install the CData JDBC Driver for MailChimp

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

Start a Spark Shell and Connect to MailChimp Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for MailChimp JAR file as the jars parameter: $ spark-shell --jars /CData/CData JDBC Driver for MailChimp/lib/cdata.jdbc.mailchimp.jar
2. With the shell running, you can connect to MailChimp with a JDBC URL and use the SQL Context load() function to read a table.

   You can set the APIKey to the key you generate in your account settings, or, instead of providing your APIKey, you can use the OAuth standard to authenticate the application. OAuth can be used to enable other users to access their own data. To authenticate using OAuth, you will need to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL by registering an app with MailChimp.

   See the "Getting Started" chapter in the help documentation for a guide to using OAuth.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.mailchimp.jar

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

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

   scala> val mailchimp_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:mailchimp:APIKey=myAPIKey;").option("dbtable","Lists").option("driver","cdata.jdbc.mailchimp.MailChimpDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the MailChimp data as a temporary table:

   scala> mailchimp_df.registerTable("lists")

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

   scala> mailchimp_df.sqlContext.sql("SELECT Name, Stats_AvgSubRate FROM Lists WHERE Contact_Country = US").collect.foreach(println)

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

Using the CData JDBC Driver for MailChimp in Apache Spark, you are able to perform fast and complex analytics on MailChimp data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 200+ CData JDBC Drivers and get started today.