R Language Client Library

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.

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.
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:

library(DBI)
library(rJava)
library(RJDBC)

2. Set the JDBC driver and JDBC URL:

# 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:

# Load the JDBC driver
drv <- JDBC("com.taosdata.jdbc.TSDBDriver", driverPath)

4. Create a TDengine database connection:

# 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:

# 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:

Native Connection

library("DBI")
library("rJava")
library("RJDBC")

args<- commandArgs(trailingOnly = TRUE)
driver_path = args[1] # path to jdbc-driver for example: "/root/taos-jdbcdriver-3.2.4-dist.jar"
driver = JDBC("com.taosdata.jdbc.TSDBDriver", driver_path)
conn = dbConnect(driver, "jdbc:TAOS://127.0.0.1:6030/?user=root&password=taosdata")
dbGetQuery(conn, "SELECT server_version()")
dbSendUpdate(conn, "create database if not exists rtest")
dbSendUpdate(conn, "create table if not exists rtest.test (ts timestamp, current float, voltage int, devname varchar(20))")
dbSendUpdate(conn, "insert into rtest.test values (now, 1.2, 220, 'test')")
dbGetQuery(conn, "select * from rtest.test")
dbDisconnect(conn)

view source code

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.