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Process & Analyze Cloudant Data in Azure Databricks

Host the CData JDBC Driver for Cloudant in Azure and use Databricks to perform data engineering and data science on live Cloudant data.

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 Cloudant data. This article walks through hosting the CData JDBC Driver in Azure, as well as connecting to and processing live Cloudant data in Databricks.

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

Install the CData JDBC Driver in Azure

To work with live Cloudant data in Databricks, install the driver on your Azure 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.cloudant.jar) from the installation location (typically C:\Program Files\CData\CData JDBC Driver for Cloudant\lib).

Connect to Salesforce from Databricks

With the JAR file installed, we are ready to work with live Cloudant data 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 Cloudant, and create a basic report.

Configure the Connection to Cloudant

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

driver = "cdata.jdbc.cloudant.CloudantDriver"
url = "jdbc:cloudant:User=abc123; Password=abcdef;"

Built-in Connection String Designer

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

java -jar cdata.jdbc.cloudant.jar

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

Set the following connection properties to connect to Cloudant:

  • User: Set this to your username.
  • Password: Set this to your password.

Load Cloudant Data

Once the connection is configured, you can load Cloudant data as a dataframe using the CData JDBC Driver and the connection information.

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

Display Cloudant Data

Check the loaded Cloudant data by calling the display function.

display (remote_table.select ("MovieRuntime"))

Analyze Cloudant Data in Azure Databricks

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

remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )

The SparkSQL below retrieves the Cloudant data for analysis.

% sql

SELECT MovieRuntime, MovieRating FROM Movies

The data from Cloudant 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 Cloudant and start working with your live Cloudant data in Apache NiFi. Reach out to our Support Team if you have any questions.