--- toc_max_heading_level: 4 sidebar_label: R title: R Language Connector --- import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; import Rdemo from "../../07-develop/01-connect/_connect_r.mdx" By using the RJDBC library in R, you can enable R programs to access TDengine data. Here are the installation process, configuration steps, and an example code in R. ## Installation Process Before getting started, make sure you have installed the R language environment. Then, follow these steps to install and configure the RJDBC library: 1. Install Java Development Kit (JDK): RJDBC library requires Java environment. Download the appropriate JDK for your operating system from the official Oracle website and follow the installation guide. 2. Install the RJDBC library: Execute the following command in the R console to install the RJDBC library. ```r install.packages("RJDBC", repos='http://cran.us.r-project.org') ``` :::note 1. The default R language package version 4.2 which shipped with Ubuntu might lead unresponsive bug. Please install latest version of R language package from the [official website](https://www.r-project.org/). 2. On Linux systems, installing the RJDBC package may require installing the necessary components for compilation. For example, on Ubuntu, you can execute the command ``apt install -y libbz2-dev libpcre2-dev libicu-dev`` to install the required components. 3. On Windows systems, you need to set the **JAVA_HOME** environment variable. ::: 3. Download the TDengine JDBC driver: Visit the Maven website and download the TDengine JDBC driver (taos-jdbcdriver-X.X.X-dist.jar) to your local machine. ## Configuration Process Once you have completed the installation steps, you need to do some configuration to enable the RJDBC library to connect and access the TDengine time-series database. 1. Load the RJDBC library and other necessary libraries in your R script: ```r library(DBI) library(rJava) library(RJDBC) ``` 2. Set the JDBC driver and JDBC URL: ```r # Set the JDBC driver path (specify the location on your local machine) driverPath <- "/path/to/taos-jdbcdriver-X.X.X-dist.jar" # Set the JDBC URL (specify the FQDN and credentials of your TDengine cluster) url <- "jdbc:TAOS://localhost:6030/?user=root&password=taosdata" ``` 3. Load the JDBC driver: ```r # Load the JDBC driver drv <- JDBC("com.taosdata.jdbc.TSDBDriver", driverPath) ``` 4. Create a TDengine database connection: ```r # Create a database connection conn <- dbConnect(drv, url) ``` 5. Once the connection is established, you can use the ``conn`` object for various database operations such as querying data and inserting data. 6. Finally, don't forget to close the database connection after you are done: ```r # Close the database connection dbDisconnect(conn) ``` ## Example Code Using RJDBC in R Here's an example code that uses the RJDBC library to connect to a TDengine time-series database and perform a query operation: Please modify the JDBC driver, JDBC URL, username, password, and SQL query statement according to your specific TDengine time-series database environment and requirements. By following the steps and using the provided example code, you can use the RJDBC library in the R language to access the TDengine time-series database and perform tasks such as data querying and analysis.