Ready to get started?

Learn more about the CData JDBC Driver for Salesforce Chatter or download a free trial:

Download Now

Work with Salesforce Chatter Data in Apache Spark Using SQL

Access and process Salesforce Chatter Data in Apache Spark using the CData JDBC Driver.

Apache Spark is a fast and general engine for large-scale data processing. When paired with the CData JDBC Driver for Salesforce Chatter, Spark can work with live Salesforce Chatter data. This article describes how to connect to and query Salesforce Chatter data from a Spark shell.

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

Install the CData JDBC Driver for Salesforce Chatter

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

Start a Spark Shell and Connect to Salesforce Chatter Data

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

    Salesforce Chatter uses OAuth 2.0 authentication. To authenticate to Salesforce Chatter via OAuth 2.0, you will need to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL by registering an app with Salesforce Chatter.

    Built-in Connection String Designer

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

    java -jar cdata.jdbc.salesforcechatter.jar

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

    Configure the connection to Salesforce Chatter, using the connection string generated above.

    scala> val salesforcechatter_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:salesforcechatter:OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;CallbackURL=http://localhost:343343;").option("dbtable","Users").option("driver","cdata.jdbc.salesforcechatter.SalesforceChatterDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the Salesforce Chatter data as a temporary table:

    scala> salesforcechatter_df.registerTable("users")
  5. Perform custom SQL queries against the Data using commands like the one below:

    scala> salesforcechatter_df.sqlContext.sql("SELECT Name, PostCount FROM Users WHERE SearchTerms = Smoked*BBQ").collect.foreach(println)

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

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