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Analyze Kintone Data in R



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

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

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

  • Driver Class: Set this to cdata.jdbc.kintone.KintoneDriver
  • 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 Kintone:

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

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

In addition to the authentication values, set the following parameters to connect to and retrieve data from Kintone:

  • Url: The URL of your account.
  • GuestSpaceId: Optional. Set this when using a guest space.

Authenticating with Kintone

Kintone supports the following authentication methods.

Using Password Authentication

You must set the following to authenticate:

  • User: The username of your account.
  • Password: The password of your account.

Using Basic Authentication

If the basic authentication security feature is set on the domain, supply the additional login credentials with BasicAuthUser and BasicAuthPassword. Basic authentication requires these credentials in addition to User and Password.

Using Client SSL

Instead of basic authentication, you can specify a client certificate to authenticate. Set SSLClientCert, SSLClientCertType, SSLClientCertSubject, and SSLClientCertPassword. Additionally, set User and Password to your login credentials.

Built-in Connection String Designer

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

java -jar cdata.jdbc.kintone.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:kintone:User=myuseraccount;Password=mypassword;Url=http://subdomain.domain.com;GuestSpaceId=myspaceid")

Schema Discovery

The driver models Kintone 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 Kintone API:

comments <- dbGetQuery(conn,"SELECT CreatorName, Text FROM Comments WHERE AppId = '1354841'")

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

View(comments)

Plot Kintone Data

You can now analyze Kintone 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(comments$Text, main="Kintone Comments", names.arg = comments$CreatorName, horiz=TRUE)