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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 PhantomBuster data. This article explains how to host the CData JDBC Driver in Azure, as well as connect to and process live PhantomBuster data in Databricks.
With built-in optimized data processing, the CData JDBC driver offers unmatched performance for interacting with live PhantomBuster data. When you issue complex SQL queries to PhantomBuster, the driver pushes supported SQL operations, like filters and aggregations, directly to PhantomBuster 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 PhantomBuster data using native data types.
To work with live PhantomBuster data in Databricks, install the driver through Azure Data Lake Storage (ADLS). (Please note that the method of connecting through DBFS, which previous versions of this article described, has been deprecated, but has not published an end-of-life.)
https://databrickslibraries.blob.core.windows.net/jdbcjars/cdata.jdbc.salesforce.jarπ Get JAR URL
abfss://[email protected]/cdata.jdbc.salesforce.jarπ Install ADLS Library
With the JAR file installed, we are ready to work with live PhantomBuster data in Databricks. Start by creating a new notebook in your workspace. Name the workbook, make sure Python is selected as the language (which should be by default), click on Connect and under General Compute select the cluster where you installed the JDBC driver (should be selected by default).
π Attaching to an existing compute resourceConnect to PhantomBuster by referencing the class for the JDBC Driver 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.api.APIDriver" url = "jdbc:api:RTK=5246...;Profile=C:\profiles\Phantombuster.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key_here""
For assistance in constructing the JDBC URL, use the connection string designer built into the PhantomBuster 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.
To use the Phantombuster API, you need to obtain an API key from your Phantombuster account settings. Navigate to phantombuster.com, click your profile icon, select Settings, and copy the API key from the API section.
After setting the following connection properties, you are ready to connect:
If your API key is associated with multiple organizations, you can target a specific organization by setting the OrganizationId connection property to the desired organization identifier. When set, it is sent as the X-Phantombuster-Org request header.
Profile=C:\profiles\Phantombuster.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key_here"π Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
Once the connection is configured, you can load PhantomBuster 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" , "Agents") \ .load ()
Check the loaded PhantomBuster data by calling the display function.
display (remote_table.select (""))
π Displaying PhantomBuster DataIf 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 PhantomBuster data for analysis.
result = spark.sql("SELECT , FROM SAMPLE_VIEW WHERE = ''")
The data from PhantomBuster 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" )π Displaying PhantomBuster Data
Download a free, 30-day trial of the CData API Driver for JDBC and start working with your live PhantomBuster data in Azure Databricks. Reach out to our Support Team if you have any questions.
Connect to live data from PhantomBuster with the API Driver
Connect to PhantomBuster