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

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

Install the CData JDBC Driver for Cvent

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

Start a Spark Shell and Connect to Cvent Data

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

   Before you can authenticate to Cvent, you must create a workspace and an OAuth application.

   Creating a Workspace

   To create a workspace:

   1. Sign into Cvent and navigate to App Switcher (the blue button in the upper right corner of the page) >> Admin.
   2. In the Admin menu, navigate to Integrations >> REST API.
   3. A new tab launches for Developer Management. Click on Manage API Access in the new tab.
   4. Create a Workspace and name it. Select the scopes you would like your developers to have access to. Scopes control what data domains the developer can access.
      • Choose All to allow developers to choose any scope, and any future scopes added to the REST API.
      • Choose Custom to limit the scopes developers can choose for their OAuth apps to selected scopes. To access all tables exposed by the driver, you need to set the following scopes:

        event/attendees:read	event/attendees:write	event/contacts:read
        event/contacts:write	event/custom-fields:read	event/custom-fields:write
        event/events:read	event/events:write	event/sessions:delete
        event/sessions:read	event/sessions:write	event/speakers:delete
        event/speakers:read	event/speakers:write	budget/budget-items:read
        budget/budget-items:write	exhibitor/exhibitors:read	exhibitor/exhibitors:write
        survey/surveys:read	survey/surveys:write

   Creating an OAuth Application

   After you have set up a Workspace and invited them, developers can sign up and create a custom OAuth app. See the Creating a Custom OAuth Application section in the Help documentation for more information.

   Connecting to Cvent

   After creating an OAuth application, set the following connection properties to connect to Cvent:

   • InitiateOAuth: GETANDREFRESH. Used to automatically get and refresh the OAuthAccessToken.
   • OAuthClientId: The Client ID associated with the OAuth application. You can find this on the Applications page in the Cvent Developer Portal.
   • OAuthClientSecret: The Client secret associated with the OAuth application. You can find this on the Applications page in the Cvent Developer Portal.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.cvent.jar

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

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

   scala> val cvent_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:cvent:OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;").option("dbtable","Events").option("driver","cdata.jdbc.cvent.CventDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Cvent data as a temporary table:

   scala> cvent_df.registerTable("events")

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

   scala> cvent_df.sqlContext.sql("SELECT Id, Title FROM Events WHERE Virtual = true").collect.foreach(println)

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

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