Analyze SQL Server Data in R

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SQL Server Driver

Rapidly create and deploy powerful Java applications that integrate with Microsoft SQL Server.



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

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

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

  • Driver Class: Set this to cdata.jdbc.sql.SQLDriver
  • 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 SQL Server:

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

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

Connecting to Microsoft SQL Server

Connect to Microsoft SQL Server using the following properties:

  • Server: The name of the server running SQL Server.
  • User: The username provided for authentication with SQL Server.
  • Password: The password associated with the authenticating user.
  • Database: The name of the SQL Server database.

Connecting to Azure SQL Server and Azure Data Warehouse

You can authenticate to Azure SQL Server or Azure Data Warehouse by setting the following connection properties:

  • Server: The server running Azure. You can find this by logging into the Azure portal and navigating to "SQL databases" (or "SQL data warehouses") -> "Select your database" -> "Overview" -> "Server name."
  • User: The name of the user authenticating to Azure.
  • Password: The password associated with the authenticating user.
  • Database: The name of the database, as seen in the Azure portal on the SQL databases (or SQL warehouses) page.

Built-in Connection String Designer

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

java -jar cdata.jdbc.sql.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:sql:User=myUser;Password=myPassword;Database=NorthWind;Server=myServer;Port=1433;")

Schema Discovery

The driver models SQL Server 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 SQL Server API:

orders <- dbGetQuery(conn,"SELECT ShipName, Freight FROM Orders")

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

View(orders)

Plot SQL Server Data

You can now analyze SQL Server 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(orders$Freight, main="SQL Server Orders", names.arg = orders$ShipName, horiz=TRUE)