Analyze Postmark Data in R via JDBC

Access Postmark 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 Postmark and the RJDBC package to work with remote Postmark 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 Postmark and visualize Postmark 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 Postmark as a JDBC Data Source

You will need the following information to connect to Postmark 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 Postmark:

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 Postmark and execute SQL queries. Initialize the JDBC connection with the dbConnect function.

Using API Key Authentication

Postmark uses server API tokens to authenticate requests. Each Postmark server has its own API token, which controls access to messages, bounces, templates, and statistics associated with that server.

To obtain your Server API Token, log in to your Postmark account and navigate to the server you want to connect to. Go to API Tokens under the server settings and copy the token labeled Server API token.

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Postmark Server API Token. This value is sent as the X-Postmark-Server-Token header on every request.

Example connection string:

Profile=C:\profiles\Postmark.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your-server-api-token"

Connecting to Postmark

Once the authentication is configured, you can connect to Postmark and query data from any of the available tables such as OutboundMessages, Bounces, and Templates.

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Postmark 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\Postmark.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your-server-api-token"")

Schema Discovery

The driver models Postmark 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 Postmark API:

bounces <- dbGetQuery(conn,"SELECT ,  FROM Bounces WHERE  = ''")

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

View(bounces)

Plot Postmark Data

You can now analyze Postmark 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(bounces$, main="Postmark Bounces", names.arg = bounces$, horiz=TRUE)