package org.surus.pig;
import static org.junit.Assert.*;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import javax.xml.bind.JAXBException;
import org.apache.pig.data.DataType;
import org.apache.pig.data.Tuple;
import org.apache.pig.data.TupleFactory;
import org.apache.pig.impl.logicalLayer.FrontendException;
import org.apache.pig.impl.logicalLayer.schema.Schema;
import org.apache.pig.impl.logicalLayer.schema.Schema.FieldSchema;
import org.junit.*;
import org.surus.pig.ScorePMML;
import org.xml.sax.SAXException;
public class ScorePMML_AuditTest {
// Audit Models
private String ensembleAuditModelPath = "./resources/examples/models/ensemble_audit_dectree.xml";
// Tuple Factory
private TupleFactory tf = TupleFactory.getInstance();
// --------------------------
// Audit Test Functions
// --------------------------
@Test
public void ensembleScoringTest_Audit_1() throws IOException, SAXException, JAXBException {
Schema inputSchema = buildAuditInputSchema();
// Input/Output Bag
Tuple inputTuple = tf.newTuple();
Tuple expected = tf.newTuple();
{
// Visit 1, Input: Implicit Signout
inputTuple = this.buildAuditInputEvent(1038288L,45,"Private","Bachelor","Married","Repair",27743.82,"Male",0,55,"UnitedStates",7298,1);
// Visit 1, Output
expected = this.buildAuditOutputEvent(1038288L,45,"Private","Bachelor","Married","Repair",27743.82,"Male",0,55,"UnitedStates",7298,1,"0");
}
// Initialize Class
ScorePMML evalPMML = new ScorePMML(this.ensembleAuditModelPath);
Schema outputScheam = evalPMML.outputSchema(inputSchema);
Tuple observed = evalPMML.exec(inputTuple);
// Test
if (expected.equals(observed)) {
System.out.println("ensembleScoringTest_Audit_1: PASS");
} else {
System.out.println("---------- EPIC FAIL: ensembleScoringTest_Audit_1 ----------");
System.out.println("Expected: " + expected.toString());
System.out.println("Observed: " + observed.toString());
System.out.println("-------- END EPIC FAIL --------");
}
assertEquals(expected,observed);
}
// --------------------------
// Audit Helper Functions
// --------------------------
private Schema buildAuditInputSchema() throws FrontendException {
// Build Field Schema
List<FieldSchema> fieldSchemas = new ArrayList<FieldSchema>();
fieldSchemas.add(new Schema.FieldSchema("id" , DataType.LONG));
fieldSchemas.add(new Schema.FieldSchema("age" , DataType.INTEGER));
fieldSchemas.add(new Schema.FieldSchema("employment" , DataType.CHARARRAY));
fieldSchemas.add(new Schema.FieldSchema("education" , DataType.CHARARRAY));
fieldSchemas.add(new Schema.FieldSchema("marital" , DataType.CHARARRAY));
fieldSchemas.add(new Schema.FieldSchema("occupation" , DataType.CHARARRAY));
fieldSchemas.add(new Schema.FieldSchema("income" , DataType.DOUBLE));
fieldSchemas.add(new Schema.FieldSchema("gender" , DataType.CHARARRAY));
fieldSchemas.add(new Schema.FieldSchema("deductions" , DataType.DOUBLE));
fieldSchemas.add(new Schema.FieldSchema("hours" , DataType.INTEGER));
fieldSchemas.add(new Schema.FieldSchema("ignore_accounts", DataType.CHARARRAY));
fieldSchemas.add(new Schema.FieldSchema("risk_adjustment", DataType.INTEGER));
fieldSchemas.add(new Schema.FieldSchema("target_adjusted", DataType.INTEGER));
return new Schema(fieldSchemas);
}
private Tuple buildAuditInputEvent( Long ID
, Integer Age
, String Employment
, String Education
, String Marital
, String Occupation
, Double Income
, String Gender
, Integer Deductions
, Integer Hours
, String IGNORE_Accounts
, Integer RISK_Adjustment
, Integer TARGET_Adjusted) {
Tuple newTuple = tf.newTuple();
newTuple.append(ID );
newTuple.append(Age );
newTuple.append(Employment );
newTuple.append(Education );
newTuple.append(Marital );
newTuple.append(Occupation );
newTuple.append(Income );
newTuple.append(Gender );
newTuple.append(Deductions );
newTuple.append(Hours );
newTuple.append(IGNORE_Accounts);
newTuple.append(RISK_Adjustment);
newTuple.append(TARGET_Adjusted);
return newTuple;
}
private Tuple buildAuditOutputEvent( Long ID
, Integer Age
, String Employment
, String Education
, String Marital
, String Occupation
, Double Income
, String Gender
, Integer Deductions
, Integer Hours
, String IGNORE_Accounts
, Integer RISK_Adjustment
, Integer TARGET_Adjusted
, String TARGET_Adjusted_predicted) {
Tuple newTuple = tf.newTuple();
newTuple.append(TARGET_Adjusted_predicted);
return newTuple;
}
}
