88 lines
3.3 KiB
Plaintext
88 lines
3.3 KiB
Plaintext
---
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toc_max_heading_level: 4
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sidebar_label: R
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title: R Language Connector
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---
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import Tabs from '@theme/Tabs';
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import TabItem from '@theme/TabItem';
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import Rdemo from "../../07-develop/01-connect/_connect_r.mdx"
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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.
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## Installation Process
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Before getting started, make sure you have installed the R language environment. Then, follow these steps to install and configure the RJDBC library:
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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.
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2. Install the RJDBC library: Execute the following command in the R console to install the RJDBC library.
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```r
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install.packages("RJDBC", repos='http://cran.us.r-project.org')
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```
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:::note
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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/).
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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.
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3. On Windows systems, you need to set the **JAVA_HOME** environment variable.
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:::
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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.
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## Configuration Process
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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.
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1. Load the RJDBC library and other necessary libraries in your R script:
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```r
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library(DBI)
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library(rJava)
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library(RJDBC)
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```
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2. Set the JDBC driver and JDBC URL:
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```r
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# Set the JDBC driver path (specify the location on your local machine)
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driverPath <- "/path/to/taos-jdbcdriver-X.X.X-dist.jar"
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# Set the JDBC URL (specify the FQDN and credentials of your TDengine cluster)
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url <- "jdbc:TAOS://localhost:6030/?user=root&password=taosdata"
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```
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3. Load the JDBC driver:
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```r
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# Load the JDBC driver
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drv <- JDBC("com.taosdata.jdbc.TSDBDriver", driverPath)
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```
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4. Create a TDengine database connection:
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```r
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# Create a database connection
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conn <- dbConnect(drv, url)
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```
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5. Once the connection is established, you can use the ``conn`` object for various database operations such as querying data and inserting data.
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6. Finally, don't forget to close the database connection after you are done:
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```r
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# Close the database connection
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dbDisconnect(conn)
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```
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## Example Code Using RJDBC in R
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Here's an example code that uses the RJDBC library to connect to a TDengine time-series database and perform a query operation:
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<Rdemo/>
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Please modify the JDBC driver, JDBC URL, username, password, and SQL query statement according to your specific TDengine time-series database environment and requirements.
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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.
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