Process & Analyze RSS Feeds in Databricks (AWS)

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RSS JDBC Driver

Easy-to-use RSS client driver enables developers to build Java applications that easily consume RSS feeds.



Host the CData JDBC Driver for RSS in AWS and use Databricks to perform data engineering and data science on live RSS feeds.

Databricks is a cloud-based service that provides data processing capabilities through Apache Spark. When paired with the CData JDBC Driver, customers can use Databricks to perform data engineering and data science on live RSS feeds. This article walks through hosting the CData JDBC Driver in AWS, as well as connecting to and processing live RSS feeds in Databricks.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live RSS feeds. 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 client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze RSS feeds using native data types.

Install the CData JDBC Driver in Databricks

To work with live RSS feeds in Databricks, install the driver on your Databricks cluster.

  1. Navigate to your Databricks administration screen and select the target cluster.
  2. On the Libraries tab, click "Install New."
  3. Select "Upload" as the Library Source and "Jar" as the Library Type.
  4. Upload the JDBC JAR file (cdata.jdbc.rss.jar) from the installation location (typically C:\Program Files\CData\CData JDBC Driver for RSS\lib).

Access RSS Feeds in your Notebook: Python

With the JAR file installed, we are ready to work with live RSS feeds in Databricks. Start by creating a new notebook in your workspace. Name the notebook, select Python as the language (though Scala is available as well), and choose the cluster where you installed the JDBC driver. When the notebook launches, we can configure the connection, query RSS, and create a basic report.

Configure the Connection to RSS

Connect to RSS by referencing the JDBC Driver class and constructing a connection string to use in the JDBC URL.

Step 1: Connection Information

driver = "cdata.jdbc.rss.RSSDriver"
url = "jdbc:rss:URI=http://broadcastCorp/rss/;"

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.

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.

Load RSS Feeds

Once you configure the connection, you can load RSS feeds as a dataframe using the CData JDBC Driver and the connection information.

Step 2: Reading the data

remote_table = spark.read.format ( "jdbc" ) \
	.option ( "driver" , driver) \
	.option ( "url" , url) \
	.option ( "dbtable" , "Latest News") \
	.load ()

Display RSS Feeds

Check the loaded RSS feeds by calling the display function.

Step 3: Checking the result

display (remote_table.select ("Author"))

Analyze RSS Feeds in Databricks

If you want to process data with Databricks SparkSQL, register the loaded data as a Temp View.

Step 4: Create a view or table

remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )

With the Temp View created, you can use SparkSQL to retrieve the RSS feeds for reporting, visualization, and analysis.

% sql

SELECT Author, Pubdate FROM SAMPLE_VIEW ORDER BY Pubdate DESC LIMIT 5

The data from RSS is only available in the target notebook. If you want to use it with other users, save it as a table.

remote_table.write.format ( "parquet" ) .saveAsTable ( "SAMPLE_TABLE" )

Download a free, 30-day trial of the CData JDBC Driver for RSS and start working with your live RSS feeds in Databricks. Reach out to our Support Team if you have any questions.