Examples

Building DataFlow Applications > Building DataFlow Applications > Building DataFlow Applications in Java > Composing an Application > Examples

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Examples

The following example provides a fully functional DataFlow application in Java. The application uses a random data generator as a data source. The random data is streamed to a LogRows operator that uses logging to store the input data.

Note: This example is used through the steps of composing a DataFlow application.

Simple DataFlow application in Java

package com.pervasive.datarush.training;

import com.pervasive.datarush.graphs.LogicalGraph; import com.pervasive.datarush.graphs.LogicalGraphFact ory;

import com.pervasive.datarush.operators.sink.LogRows; import com.pervasive.datarush.operators.source.Genera teRandom;

import com.pervasive.datarush.types.RecordTokenType; import com.pervasive.datarush.types.TokenTypeConstant

;

/**

* Create a simple application graph consisting of a random row generator and

* a row logger. Execute the graph with the default engine properties.

public class SimpleApp {

public static void main(String[] args) {

// Create an empty logical graph

LogicalGraph graph = LogicalGraphFactory.newLogicalGraph("SimpleApp ");

// Create a random row generator setting the row count and type wanted

GenerateRandom generator = graph.add(new GenerateRandom(), "generator");

generator.setRowCount(1000); RecordTokenType type =

TokenTypeConstant.record( TokenTypeConstant.DOUBLE("dblField"),

TokenTypeConstant.STRING("stringFld"));

generator.setOutputType(type);

// Create a row logger

LogRows logger = graph.add(newLogRows(0), "logger");

// Connect the output of the generator to the input of the logger

graph.connect(generator.getOutput(), logger.getInput());

// Compile and run the graph

graph.run();

}

The following is the same example written in JavaScript. For detailed conceptual information about building a DataFlow application, see Building DataFlow Applications Using RushScript.

Simple DataFlow application in JavaScript

// Define the schema wanted from the data generator

var schema = dr.schema().DOUBLE('dblField').STRING('stringF ield');

// Create a dataset of randomly generated data var data = dr.generateRandom({rowCount:1000, outputType:schema});

// Log the dataset

dr.logRows(data, {logFrequency:0});

// Execute the created application dr.execute();

The following provides the output of the application. This application was run on an 8-core system and the LogRows operator logs the type of its input data and the final row count.

INFO com.pervasive.datarush.graphs.internal.Logical Graph

InstanceImpl execute Executing phase 0 graph:

{[generateRandom, logRows]}

INFO SimpleApp.logRows execute Input type is