Statistical Algorithms Importer: Java Project

This page explains how to create a Java project using the Statistical Algorithms Importer (SAI) portlet with two approaches.

Two approaches are possible: Black-box and White-box integration. The next sections explain how they work and which cases these two ways address.

Black Box Integration

Java Project, SAI

This is the preferred way for developers who want their processes distributed based on the load of requests. Each process request will run on one dedicated machine. Black box processed usually do not use the e-Infrastructure resources but live on their own.

Project Configuration

Define project's metadata

Java Info, SAI

Add input and output parameters and click on "Set Code" to indicate the main file to execute (i.e. the .jar file)

Java I/O, SAI

Add information about the running environment (e.g. Java version etc.)

Java Interpreter, SAI

After the software creation phase a Main.R file and a Taget folder are created

Java Create, SAI

Example Code

Java code in sample:

/**
 * 
 * @author Giancarlo Panichi
 * 
 *
 */
import java.io.File;
import java.io.FileWriter;
 
public class SimpleProducer
{
  public static void main(String[] args)
  {
    try
    {
      FileWriter fw = new FileWriter(new File("program.txt"));
      fw.write("Check: " + args[0]);
      fw.close();
    }
    catch (Exception e)
    {
      e.printStackTrace();
    }
  }
}

Example Download

File:JavaBlackBox.zip

White Box Integration

This is the preferred way for developers who want their processes to fully exploit the e-Infrastructure resources, for example to implement Cloud computing using the e-Infrastructure computational resources. This integration modality allows also to fully reuse the Java data mining frameworks integrated by DataMiner, i.e. Knime, RapidMiner, Weka, gCube EcologicalEngine.

Step-by-step guide to integrate Java processes as white boxes