How to work with RSS Feeds 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 RSS, Spark can work with live RSS feeds. This article describes how to connect to and query RSS feeds from a Spark shell.

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

Install the CData JDBC Driver for RSS

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

Start a Spark Shell and Connect to RSS Feeds

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

   $ spark-shell --jars /CData/CData JDBC Driver for RSS/lib/cdata.jdbc.rss.jar
   

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

   You can connect to RSS and Atom feeds, as well as feeds with custom extensions. To connect to a feed, set the URL property. You can also access secure feeds. A variety of authentication mechanisms are supported. See the help documentation for details.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.rss.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 RSS, using the connection string generated above.

   scala> val rss_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:rss:URI=http://broadcastCorp/rss/;").option("dbtable","Latest News").option("driver","cdata.jdbc.rss.RSSDriver").load()
   

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

4. Register the RSS feeds as a temporary table:

   scala> rss_df.registerTable("latest news")

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

   scala> rss_df.sqlContext.sql("SELECT Author, Pubdate FROM Latest News WHERE Category = US").collect.foreach(println)

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

   👁 Feeds in Apache Spark (Salesforce is shown)
   

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