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

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

Install the CData JDBC Driver for Superchat

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

Start a Spark Shell and Connect to Superchat Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for Superchat/lib/cdata.jdbc.api.jar
   

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

   Superchat uses API Key authentication. The API key is passed via the X-API-KEY request header on every call.

   Authentication

   To authenticate to Superchat, you need to obtain your API key from the Superchat workspace settings.

   Using API Key Authentication

   You can obtain your API key from Settings > Integrations > API Key in your Superchat workspace.

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

   • AuthScheme: Set this to APIKey.
   • APIKey: Set this to your Superchat API key.

   Example connection string:

   Profile=C:\profiles\Superchat.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key';
   

   Built-in Connection String Designer

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

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\Superchat.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key';").option("dbtable","Channels").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 Superchat data as a temporary table:

   scala> api_df.registerTable("channels")

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

   scala> api_df.sqlContext.sql("SELECT ,  FROM Channels WHERE  = ").collect.foreach(println)

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

   

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