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

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

Install the CData JDBC Driver for Salesforce Marketing

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

Start a Spark Shell and Connect to Salesforce Marketing Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for Salesforce Marketing/lib/cdata.jdbc.sfmarketingcloud.jar
   

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

   Authenticating to the Salesforce Marketing Cloud APIs

   Set the and to your login credentials, or to the credentials for a sandbox user if you are connecting to a sandbox account.

   Connecting to the Salesforce Marketing Cloud APIs

   By default, the data provider connects to production environments. Set to true to use a Salesforce Marketing Cloud sandbox account.

   The default Instance is s7 of the Web Services API; however, if you use a different instance, you can set .

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.sfmarketingcloud.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 Salesforce Marketing, using the connection string generated above.

   scala> val sfmarketingcloud_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:sfmarketingcloud:User=myUser;Password=myPassword;InitiateOAuth=GETANDREFRESH;").option("dbtable","Subscriber").option("driver","cdata.jdbc.sfmarketingcloud.SFMarketingCloudDriver").load()
   

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

4. Register the Salesforce Marketing data as a temporary table:

   scala> sfmarketingcloud_df.registerTable("subscriber")

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

   scala> sfmarketingcloud_df.sqlContext.sql("SELECT Id, Status FROM Subscriber WHERE EmailAddress = [email protected]").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 Salesforce Marketing in Apache Spark, you are able to perform fast and complex analytics on Salesforce Marketing 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.