Analyze SAS Data Sets Data in R via JDBC

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

You will need the following information to connect to SAS Data Sets as a JDBC data source:

• Driver Class: Set this to cdata.jdbc.sasdatasets.SASDataSetsDriver
• 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 SAS Data Sets:

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

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

Set the following connection properties to connect to your SAS DataSet files:

Connecting to Local Files

• Set the Connection Type to "Local." Local files support SELECT, INSERT, and DELETE commands.
• Set the URI to a folder containing SAS files, e.g. C:\PATH\TO\FOLDER\.

Connecting to Cloud-Hosted SAS DataSet Files

While the driver is capable of pulling data from SAS DataSet files hosted on a variety of cloud data stores, INSERT, UPDATE, and DELETE are not supported outside of local files in this driver.

Set the Connection Type to the service hosting your SAS DataSet files. A unique prefix at the beginning of the URI connection property is used to identify the cloud data store and the remainder of the path is a relative path to the desired folder (one table per file) or single file (a single table). For more information, refer to the Getting Started section of the Help documentation.

Built-in Connection String Designer

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

java -jar cdata.jdbc.sasdatasets.jar

Fill in the connection properties and copy the connection string to the clipboard.

👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)

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

conn <- dbConnect(driver,"jdbc:sasdatasets:URI=C:/myfolder;")

Schema Discovery

The driver models SAS Data Sets 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 SAS Data Sets API:

restaurants <- dbGetQuery(conn,"SELECT name, borough FROM restaurants WHERE cuisine = 'American'")

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

View(restaurants)

Plot SAS Data Sets Data

You can now analyze SAS Data Sets 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(restaurants$borough, main="SAS Data Sets restaurants", names.arg = restaurants$name, horiz=TRUE)

👁 A basic bar plot. (Salesforce is shown.)