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

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

Install the CData JDBC Driver for Zoom

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

Start a Spark Shell and Connect to Zoom Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for Zoom JAR file as the jars parameter: $ spark-shell --jars /CData/CData JDBC Driver for Zoom/lib/cdata.jdbc.api.jar
2. With the shell running, you can connect to Zoom 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 Zoom Profile on disk (e.g. C:\profiles\Zoom.apip). Next, set the ProfileSettings connection property to the connection string for Zoom (see below).

   Zoom API Profile Settings

   To authenticate to Zoom, you can use the OAuth standard to connect to your own data or to allow other users to connect to their data.

   First you will need to create an OAuth app. To do so, navigate to https://marketplace.zoom.us/develop/create and click Create under the OAuth section. Select whether or not the app will be for individual users or for the entire account, and uncheck the box to publish the app. Give the app a name and click Create. You will then be given your Client Secret and Client ID

   After setting the following connection properties, you are ready to connect:

   • AuthScheme: Set this to OAuth.
   • InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage the process to obtain the OAuthAccessToken.
   • OAuthClientID: Set this to the OAuth Client ID that is specified in your app settings.
   • OAuthClientSecret: Set this to the OAuth Client Secret that is specified in your app settings.
   • CallbackURL: Set this to the Redirect URI you specified in your app settings.

   Built-in Connection String Designer

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

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

   scala> api_df.registerTable("meetingregistrants")

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

   scala> api_df.sqlContext.sql("SELECT Id, JobTitle FROM MeetingRegistrants WHERE State = NC").collect.foreach(println)

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

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