Analyze Pushover Data in R via JDBC

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

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

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

Start by setting the Profile connection property to the location of the Pushover Profile on disk (e.g. C:\profiles\Pushover.apip). Next, set the ProfileSettings connection property to the connection string for Pushover (see below).

Pushover API Profile Settings

Pushover uses API Key authentication. Your Pushover Application API Token is used to authenticate all requests. You can create and manage API tokens in the Pushover dashboard at pushover.net by registering an application under Settings > Your Applications.

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

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your 30-character Pushover Application API Token.

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Pushover 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\Pushover.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_application_token';")

Schema Discovery

The driver models Pushover 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 Pushover API:

groupmembers <- dbGetQuery(conn,"SELECT User, Memo FROM GroupMembers WHERE GroupKey = 'your_group_key'")

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

View(groupmembers)

Plot Pushover Data

You can now analyze Pushover 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(groupmembers$Memo, main="Pushover GroupMembers", names.arg = groupmembers$User, horiz=TRUE)