In today’s data-driven world, combining the power of different programming languages is essential for tackling complex analytical tasks. Integrating R, a popular language for statistical computing and graphics, with Java, a universal language for building applications, can unlock new possibilities. One effective way to bridge the gap between R and Java is by utilizing Rserve—a server-based interface for R.
Rserve is a package in R that allows other programs to communicate with an R session over a network. It provides a flexible and efficient means for leveraging R’s capabilities from external languages like Java.
Here’s an example demonstrating how to call R from Java using the Rserve package.
import org.rosuda.REngine.Rserve.RConnection;
import org.rosuda.REngine.Rserve.RserveException;
import org.rosuda.REngine.REXPMismatchException;
public class RserveInJava {
public static void main(String[] args) throws RserveException,
REXPMismatchException {
// Establish a connection to the Rserve server
RConnection connection = new RConnection();
System.out.println("The connection has been established with Rserve.");
// Execute the R code
String rCode = "X <- c(2, 4, 6, 8, 10); mean(X)"; // R code to calculate the mean of a vector
double result = connection.eval(rCode).asDouble();
System.out.println("Result from R: " + result);
// Close the connection
connection.close();
System.out.println("Disconnected from Rserve.");
}
}Let’s look at the code explanation below:
Lines 1–3: We use the org.rosuda.REngine.Rserve.RConnection class from the Rserve package to establish a connection to the Rserve server.
Line 9: The RConnection object represents the connection to the Rserve server. We create an instance of RConnection and establish a connection.
Line 12: We define the R code we want to execute. In this case, we calculate the mean of a vector X using the mean() function.
Lines 13–14: We use the eval() method of the RConnection object to execute the R code. The result is returned as an asDouble() to retrieve the result as a double value.
Line 16: Finally, we close the connection using the close() method of the RConnection object to release the resources.
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