Analyze SharePoint Data in R

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SharePoint JDBC Driver

Provides Java developers with the power to easily connect their Web, Desktop, and Mobile applications to data in SharePoint Server Lists, Contacts, Calendar, Links, Tasks, and more!



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

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

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

  • Driver Class: Set this to cdata.jdbc.sharepoint.SharePointDriver
  • 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 SharePoint:

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

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

Set the URL property to the base SharePoint site or to a sub-site. This allows you to query any lists and other SharePoint entities defined for the site or sub-site.

The User and Password properties, under the Authentication section, must be set to valid SharePoint user credentials when using SharePoint On-Premise.

If you are connecting to SharePoint Online, set the SharePointEdition to SHAREPOINTONLINE along with the User and Password connection string properties. For more details on connecting to SharePoint Online, see the "Getting Started" chapter of the help documentation

Built-in Connection String Designer

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

java -jar cdata.jdbc.sharepoint.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:sharepoint:User=myuseraccount;Password=mypassword;Auth Scheme=NTLM;URL=http://sharepointserver/mysite;SharePointEdition=SharePointOnPremise;")

Schema Discovery

The driver models SharePoint 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 SharePoint API:

mycustomlist <- dbGetQuery(conn,"SELECT Name, Revenue FROM MyCustomList")

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

View(mycustomlist)

Plot SharePoint Data

You can now analyze SharePoint 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(mycustomlist$Revenue, main="SharePoint MyCustomList", names.arg = mycustomlist$Name, horiz=TRUE)