homework-jianmu/docs/en/14-reference/05-connector/43-r-lang.mdx

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---
sidebar_label: R
title: R Client Library
slug: /tdengine-reference/client-libraries/r-lang
---
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
import Rdemo from "../../07-develop/_connect_r.mdx"
By using the RJDBC library in R, R programs can access data from TDengine. Below are the installation process, configuration steps, and R code examples.
## Installation Process
Before you start, ensure that you have the R language environment installed. Then follow these steps to install and configure the RJDBC library:
1. Install the Java Development Kit (JDK): The RJDBC library requires a Java environment. Please download the appropriate JDK for your operating system from the Oracle official 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 R language software version 4.2 that comes with Ubuntu may produce a non-responsive bug when calling the RJDBC library. Please install the R language package from the [official R website](https://www.r-project.org/).
2. Installing the RJDBC package on Linux may require installing additional components. For example, on Ubuntu, execute the command `apt install -y libbz2-dev libpcre2-dev libicu-dev` to install.
3. On Windows systems, you need to set the JAVA_HOME environment variable.
:::
3. Download the TDengine JDBC driver: Visit maven.org to download the TDengine JDBC driver (taos-jdbcdriver-X.X.X-dist.jar).
4. Place the TDengine JDBC driver in an appropriate location: Choose a suitable location on your computer to save the TDengine JDBC driver file (taos-jdbcdriver-X.X.X-dist.jar).
## Configuration Process
After completing the installation steps, you need to configure some settings so that the RJDBC library can correctly connect to and access the TDengine time-series database.
1. Load the RJDBC 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 path to the JDBC driver (modify based on your actual storage location)
driverPath <- "/path/to/taos-jdbcdriver-X.X.X-dist.jar"
# Set the JDBC URL (modify based on your specific environment)
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 the database connection
conn <- dbConnect(drv, url)
```
5. Once connected successfully, you can perform various database operations with the `conn` object, such as querying data, inserting data, etc.
6. Finally, don't forget to close the database connection when you're done using it:
```r
# Close the database connection
dbDisconnect(conn)
```
## R Language Example Code Using RJDBC
Here is an example code snippet that connects to the TDengine time-series database using the RJDBC library and executes a query:
<Rdemo/>
Please modify the JDBC driver, JDBC URL, username, password, and SQL query statement according to your actual TDengine time-series database environment and requirements.
By following the above steps and example code, you can access the TDengine time-series database using the RJDBC library in the R language environment for data querying and analysis operations.