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Analyze Authorize.Net Data in R

Use standard R functions and the development environment of your choice to analyze Authorize.Net data with the CData JDBC Driver for Authorize.Net.

Access Authorize.Net 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 Authorize.Net and the RJDBC package to work with remote Authorize.Net 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 Authorize.Net and visualize Authorize.Net 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 Authorize.Net as a JDBC Data Source

You will need the following information to connect to Authorize.Net as a JDBC data source:

  • Driver Class: Set this to cdata.jdbc.authorizenet.AuthorizeNetDriver
  • 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 Authorize.Net:

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

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

You can obtain the necessary connection properties on the Security Settings -> General Settings page after logging into your Merchant Account.

  • UseSandbox: The Authorize.Net API to be used to process transactions. If you are using a production account, this property can be left blank. If you are using a developer test account, set this to 'TRUE'.
  • LoginID: The API login Id associated with your payment gateway account. This property is used to authenticate that you are authorized to submit website transactions. Note that this value is not the same as the login Id that you use to log in to the Merchant Interface.
  • TransactionKey: The transaction key associated with your payment gateway account. This property is used to authenticate that you are authorized to submit website transactions.

Built-in Connection String Designer

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

java -jar cdata.jdbc.authorizenet.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:authorizenet:LoginId=MyLoginId;TransactionKey=MyTransactionKey;")

Schema Discovery

The driver models Authorize.Net 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 Authorize.Net API:

settledbatchlist <- dbGetQuery(conn,"SELECT MarketType, TotalCharge FROM SettledBatchList")

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

View(settledbatchlist)

Plot Authorize.Net Data

You can now analyze Authorize.Net 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(settledbatchlist$TotalCharge, main="Authorize.Net SettledBatchList", names.arg = settledbatchlist$MarketType, horiz=TRUE)