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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 HubDB data. This article explains how to host the CData JDBC Driver in AWS, as well as connect to and process live HubDB data in Databricks.
With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live HubDB data. When you issue complex SQL queries to HubDB, the driver pushes supported SQL operations, like filters and aggregations, directly to HubDB 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 HubDB data using native data types.
To work with live HubDB data in Databricks, install the driver on your Databricks cluster.
With the JAR file installed, we are ready to work with live HubDB 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 HubDB, and create a basic report.
Connect to HubDB by referencing the JDBC Driver class and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the property in the JDBC URL (unless you are using a Beta driver). You can view the licensing file included in the installation for information on how to set this property.
driver = "cdata.jdbc.hubdb.HubDBDriver" url = "jdbc:hubdb:RTK=5246...;AuthScheme=OAuth;OAuthClientID=MyOAuthClientID;OAuthClientSecret=MyOAuthClientSecret;CallbackURL=http://localhost:33333;InitiateOAuth=GETANDREFRESH;"
For assistance in constructing the JDBC URL, use the connection string designer built into the HubDB JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.
java -jar cdata.jdbc.hubdb.jar
Fill in the connection properties and copy the connection string to the clipboard.
There are two authentication methods available for connecting to HubDB data source: OAuth Authentication with a public HubSpot application and authentication with a Private application token.
AuthScheme must be set to "OAuth" in all OAuth flows. Be sure to review the Help documentation for the required connection properties for you specific authentication needs (desktop applications, web applications, and headless machines).
Follow the steps below to register an application and obtain the OAuth client credentials:
Under Scopes, select any scopes you need for your application's intended functionality.
A minimum of the following scopes is required to access tables:
To connect using a HubSpot private application token, set the AuthScheme property to "PrivateApp."
You can generate a private application token by following the steps below:
To connect, set PrivateAppToken to the private application token you retrieved.
๐ Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)Once you configure the connection, you can load HubDB 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" , "NorthwindProducts") \ .load ()
Check the loaded HubDB data by calling the display function.
display (remote_table.select ("PartitionKey"))
๐ Displaying HubDB DataIf you want to process data with Databricks SparkSQL, register the loaded data as a Temp View.
remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )
With the Temp View created, you can use SparkSQL to retrieve the HubDB data for reporting, visualization, and analysis.
% sql SELECT PartitionKey, Name FROM SAMPLE_VIEW ORDER BY Name DESC LIMIT 5๐ Displaying HubDB Data
The data from HubDB 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 HubDB and start working with your live HubDB data in Databricks. Reach out to our Support Team if you have any questions.
Download a free trial of the HubDB Driver to get started:
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