Analyze PhantomBuster Data in R via JDBC

Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Use standard R functions and the development environment of your choice to analyze PhantomBuster data with the CData JDBC Driver for PhantomBuster.

Access PhantomBuster data with pure R script and standard SQL on any machine where R and Java can be installed. You can use the CData JDBC Driver for PhantomBuster and the RJDBC package to work with remote PhantomBuster data in R. By using the CData Driver, you are leveraging a driver written for industry-proven standards to access your data in the popular, open-source R language. This article shows how to use the driver to execute SQL queries to PhantomBuster and visualize PhantomBuster data by calling standard R functions.

Install R

You can match the driver's performance gains from multi-threading and managed code by running the multithreaded Microsoft R Open or by running open R linked with the BLAS/LAPACK libraries. This article uses Microsoft R Open 3.2.3, which is preconfigured to install packages from the Jan. 1, 2016 snapshot of the CRAN repository. This snapshot ensures reproducibility.

Load the RJDBC Package

To use the driver, download the RJDBC package. After installing the RJDBC package, the following line loads the package:

library(RJDBC)

Connect to PhantomBuster as a JDBC Data Source

You will need the following information to connect to PhantomBuster as a JDBC data source:

  • Driver Class: Set this to cdata.jdbc.api.APIDriver
  • Classpath: Set this to the location of the driver JAR. By default this is the lib subfolder of the installation folder.

The DBI functions, such as dbConnect and dbSendQuery, provide a unified interface for writing data access code in R. Use the following line to initialize a DBI driver that can make JDBC requests to the CData JDBC Driver for PhantomBuster:

driver <- JDBC(driverClass = "cdata.jdbc.api.APIDriver", classPath = "MyInstallationDir\lib\cdata.jdbc.api.jar", identifier.quote = "'") 

You can now use DBI functions to connect to PhantomBuster and execute SQL queries. Initialize the JDBC connection with the dbConnect function.

Using API Key Authentication

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:

  • AuthScheme: Set this to APIKey.
  • APIKey: Set this to your Phantombuster API key from the account settings page.

Multi-Organization Accounts

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.

Example connection string:

Profile=C:\profiles\Phantombuster.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key_here"

Built-in Connection String Designer

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.

Below is a sample dbConnect call, including a typical JDBC connection string:

conn <- dbConnect(driver,"jdbc:api:Profile=C:\profiles\Phantombuster.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key_here"")

Schema Discovery

The driver models PhantomBuster APIs as relational tables, views, and stored procedures. Use the following line to retrieve the list of tables:

dbListTables(conn)

Execute SQL Queries

You can use the dbGetQuery function to execute any SQL query supported by the PhantomBuster API:

agents <- dbGetQuery(conn,"SELECT ,  FROM Agents WHERE  = ''")

You can view the results in a data viewer window with the following command:

View(agents)

Plot PhantomBuster Data

You can now analyze PhantomBuster data with any of the data visualization packages available in the CRAN repository. You can create simple bar plots with the built-in bar plot function:

par(las=2,ps=10,mar=c(5,15,4,2))
barplot(agents$, main="PhantomBuster Agents", names.arg = agents$, horiz=TRUE)

Ready to get started?

Connect to live data from PhantomBuster with the API Driver

Connect to PhantomBuster