Analyze Linear Data in R via JDBC

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

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

• Driver Class: Set this to cdata.jdbc.linear.LinearDriver
• 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 Linear:

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

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

You can authenticate to Linear with a personal API key or with OAuth 2.0. The API key is the simplest option for connecting with your own Linear account.

Authenticating with an API Key

Set the following connection properties:

• AuthScheme: Set this to APIKey.
• APIKey: A Linear personal API key.

To create a personal API key, log in to Linear, open Settings > Security & access > Personal API keys, select New API key, and create it. Copy the key immediately, because Linear shows it only once.

Authenticating with OAuth

OAuth requires a custom OAuth application registered in Linear (Settings > API > OAuth applications), which provides the OAuthClientId and OAuthClientSecret. Two flows are supported:

• Authorization code: Set AuthScheme to OAuth, InitiateOAuth to GETANDREFRESH, and provide OAuthClientId, OAuthClientSecret, and the CallbackURL defined in your application (e.g., http://localhost:33333). The driver opens Linear in your browser so you can grant access.
• Client credentials: Set AuthScheme to OAuthClient and provide OAuthClientId and OAuthClientSecret. This authenticates the application itself, with no browser interaction, and suits machine-to-machine integrations.

By default, the driver requests the read,write scopes. The driver refreshes the access token automatically when it expires.

Built-in Connection String Designer

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

java -jar cdata.jdbc.linear.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:linear:AuthScheme=APIKey;APIKey=myAPIKey;")

Schema Discovery

The driver models Linear 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 Linear API:

team <- dbGetQuery(conn,"SELECT id, name FROM Team WHERE key = 'ENG'")

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

View(team)

Plot Linear Data

You can now analyze Linear 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(team$name, main="Linear Team", names.arg = team$id, horiz=TRUE)