git-svn-id: https://svn.d4science.research-infrastructures.eu/gcube/trunk/data-analysis/EcologicalEngine@58772 82a268e6-3cf1-43bd-a215-b396298e98cf

src/main/java/org/gcube/dataanalysis/ecoengine/clustering/DBScan.java

@@ -6,11 +6,11 @@ import java.util.List;
 import org.gcube.contentmanagement.lexicalmatcher.utils.AnalysisLogger;
 import org.gcube.dataanalysis.ecoengine.configuration.AlgorithmConfiguration;
 import org.gcube.dataanalysis.ecoengine.configuration.INFRASTRUCTURE;
+import org.gcube.dataanalysis.ecoengine.datatypes.ColumnTypesList;
 import org.gcube.dataanalysis.ecoengine.datatypes.DatabaseType;
 import org.gcube.dataanalysis.ecoengine.datatypes.InputTable;
 import org.gcube.dataanalysis.ecoengine.datatypes.OutputTable;
 import org.gcube.dataanalysis.ecoengine.datatypes.PrimitiveType;
-import org.gcube.dataanalysis.ecoengine.datatypes.PrimitiveTypesList;
 import org.gcube.dataanalysis.ecoengine.datatypes.ServiceType;
 import org.gcube.dataanalysis.ecoengine.datatypes.StatisticalType;
 import org.gcube.dataanalysis.ecoengine.datatypes.enumtypes.DatabaseParameters;
@@ -387,35 +387,19 @@ public class DBScan implements Clusterer{
 		List<StatisticalType> parameters = new ArrayList<StatisticalType>();
 		List<TableTemplates> templateOccs = new ArrayList<TableTemplates>();
 		templateOccs.add(TableTemplates.GENERIC);
-		
 		InputTable p1 = new InputTable(templateOccs,"OccurrencePointsTable","Occurrence Points Table","occurrences");
-//		PrimitiveType p2 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "FeaturesColumnNames","Column Names for the features comma separated","x,y");
+		ColumnTypesList p2 = new ColumnTypesList ("OccurrencePointsTable","FeaturesColumnNames", "Column Names for the features", false);
-		
-		PrimitiveTypesList p2 = new PrimitiveTypesList(PrimitiveTypes.STRING, "FeaturesColumnNames","Column Names for the features",false);
-		
 		ServiceType p3 = new ServiceType(ServiceParameters.RANDOMSTRING, "OccurrencePointsClusterTable","Table name of the distribution","occCluster_");
 		PrimitiveType p4 = new PrimitiveType(Integer.class.getName(), null, PrimitiveTypes.NUMBER, "epsilon","DBScan epsilon parameter","10");
 		PrimitiveType p5 = new PrimitiveType(Integer.class.getName(), null, PrimitiveTypes.NUMBER, "min_points","DBScan minimum points parameter (identifies outliers)","1");
-
-		
-		DatabaseType p6 = new DatabaseType(DatabaseParameters.DATABASEUSERNAME, "DatabaseUserName", "db user name");
-		DatabaseType p7 = new DatabaseType(DatabaseParameters.DATABASEPASSWORD, "DatabasePassword", "db password");
-		DatabaseType p8 = new DatabaseType(DatabaseParameters.DATABASEDRIVER, "DatabaseDriver", "db driver");
-		DatabaseType p9 = new DatabaseType(DatabaseParameters.DATABASEURL, "DatabaseURL", "db url");
-		DatabaseType p10 = new DatabaseType(DatabaseParameters.DATABASEDIALECT, "DatabaseDialect", "db dialect");
-		DatabaseType p11 = new DatabaseType(DatabaseParameters.DATABASETABLESPACE, "DatabaseTableSpace", "db dialect");
 		
 		parameters.add(p1);
 		parameters.add(p2);
 		parameters.add(p3);
 		parameters.add(p4);
 		parameters.add(p5);
-		parameters.add(p6);
+		
-		parameters.add(p7);
+		DatabaseType.addDefaultDBPars(parameters);
-		parameters.add(p8);
-		parameters.add(p9);
-		parameters.add(p10);
-		parameters.add(p11);
 		
 		return parameters;
 	}
@@ -436,7 +420,10 @@ public class DBScan implements Clusterer{
 
 	@Override
 	public String getResources() {
-		return ResourceFactory.getResources(100f);
+		if ((status>0)&&(status<100))
+			return ResourceFactory.getResources(100f);
+		else
+			return ResourceFactory.getResources(0f);
 	}
 
 

src/main/java/org/gcube/dataanalysis/ecoengine/clustering/KMeans.java

@@ -5,10 +5,10 @@ import java.util.List;
 
 import org.gcube.contentmanagement.lexicalmatcher.utils.AnalysisLogger;
 import org.gcube.dataanalysis.ecoengine.configuration.AlgorithmConfiguration;
+import org.gcube.dataanalysis.ecoengine.datatypes.ColumnTypesList;
 import org.gcube.dataanalysis.ecoengine.datatypes.DatabaseType;
 import org.gcube.dataanalysis.ecoengine.datatypes.InputTable;
 import org.gcube.dataanalysis.ecoengine.datatypes.PrimitiveType;
-import org.gcube.dataanalysis.ecoengine.datatypes.PrimitiveTypesList;
 import org.gcube.dataanalysis.ecoengine.datatypes.ServiceType;
 import org.gcube.dataanalysis.ecoengine.datatypes.StatisticalType;
 import org.gcube.dataanalysis.ecoengine.datatypes.enumtypes.DatabaseParameters;
@@ -114,17 +114,9 @@ public class KMeans extends DBScan{
 		List<TableTemplates> templateOccs = new ArrayList<TableTemplates>();
 		templateOccs.add(TableTemplates.GENERIC);
 		InputTable p1 = new InputTable(templateOccs,"OccurrencePointsTable","Occurrence Points Table","occurrences");
-		PrimitiveTypesList p2 = new PrimitiveTypesList(PrimitiveTypes.STRING, "FeaturesColumnNames","Column Names for the features",false);
+		ColumnTypesList p2 = new ColumnTypesList ("OccurrencePointsTable","FeaturesColumnNames", "Column Names for the features", false);
 		
 		ServiceType p3 = new ServiceType(ServiceParameters.RANDOMSTRING, "OccurrencePointsClusterTable","Table name of the distribution","occCluster_");
-
-		DatabaseType p6 = new DatabaseType(DatabaseParameters.DATABASEUSERNAME, "DatabaseUserName", "db user name");
-		DatabaseType p7 = new DatabaseType(DatabaseParameters.DATABASEPASSWORD, "DatabasePassword", "db password");
-		DatabaseType p8 = new DatabaseType(DatabaseParameters.DATABASEDRIVER, "DatabaseDriver", "db driver");
-		DatabaseType p9 = new DatabaseType(DatabaseParameters.DATABASEURL, "DatabaseURL", "db url");
-		DatabaseType p10 = new DatabaseType(DatabaseParameters.DATABASEDIALECT, "DatabaseDialect", "db dialect");
-		DatabaseType p11 = new DatabaseType(DatabaseParameters.DATABASETABLESPACE, "DatabaseTableSpace", "db dialect");
-		
 		PrimitiveType p4 = new PrimitiveType(Integer.class.getName(), null, PrimitiveTypes.NUMBER, "k","Expected Number of Clusters","3");
 		PrimitiveType p5 = new PrimitiveType(Integer.class.getName(), null, PrimitiveTypes.NUMBER, "max_runs","Max runs of the clustering procedure","10");
 		PrimitiveType p12 = new PrimitiveType(Integer.class.getName(), null, PrimitiveTypes.NUMBER, "max_optimization_steps","Max number of internal optimization steps","5");
@@ -135,15 +127,10 @@ public class KMeans extends DBScan{
 		parameters.add(p3);
 		parameters.add(p4);
 		parameters.add(p5);
-		parameters.add(p6);
-		parameters.add(p7);
-		parameters.add(p8);
-		parameters.add(p9);
-		parameters.add(p10);
-		parameters.add(p11);
 		parameters.add(p12);
 		parameters.add(p13);
 		
+		DatabaseType.addDefaultDBPars(parameters);
 		return parameters;
 	}
 

src/main/java/org/gcube/dataanalysis/ecoengine/clustering/XMeansWrapper.java

@@ -8,10 +8,10 @@ import java.util.List;
 
 import org.gcube.contentmanagement.lexicalmatcher.utils.AnalysisLogger;
 import org.gcube.dataanalysis.ecoengine.configuration.AlgorithmConfiguration;
+import org.gcube.dataanalysis.ecoengine.datatypes.ColumnTypesList;
 import org.gcube.dataanalysis.ecoengine.datatypes.DatabaseType;
 import org.gcube.dataanalysis.ecoengine.datatypes.InputTable;
 import org.gcube.dataanalysis.ecoengine.datatypes.PrimitiveType;
-import org.gcube.dataanalysis.ecoengine.datatypes.PrimitiveTypesList;
 import org.gcube.dataanalysis.ecoengine.datatypes.ServiceType;
 import org.gcube.dataanalysis.ecoengine.datatypes.StatisticalType;
 import org.gcube.dataanalysis.ecoengine.datatypes.enumtypes.DatabaseParameters;
@@ -120,7 +120,7 @@ public class XMeansWrapper extends DBScan {
 		templateOccs.add(TableTemplates.GENERIC);
 
 		InputTable p1 = new InputTable(templateOccs, "OccurrencePointsTable", "Occurrence Points Table", "occurrences");
-		PrimitiveTypesList p2 = new PrimitiveTypesList(PrimitiveTypes.STRING, "FeaturesColumnNames", "Column Names for the features", false);
+		ColumnTypesList p2 = new ColumnTypesList ("OccurrencePointsTable","FeaturesColumnNames", "Column Names for the features", false);
 		ServiceType p3 = new ServiceType(ServiceParameters.RANDOMSTRING, "OccurrencePointsClusterTable", "Table name of the distribution", "occCluster_");
 
 		PrimitiveType p4 = new PrimitiveType(Integer.class.getName(), null, PrimitiveTypes.NUMBER, "maxIterations", "XMeans max number of overall iterations of the clustering learning", "10");
@@ -128,27 +128,15 @@ public class XMeansWrapper extends DBScan {
 		PrimitiveType p12 = new PrimitiveType(Integer.class.getName(), null, PrimitiveTypes.NUMBER, "maxClusters", "Maximum number of clusters to produce", "50");
 		PrimitiveType p13 = new PrimitiveType(Integer.class.getName(), null, PrimitiveTypes.NUMBER, "min_points", "Number of points which define an outlier set", "2");
 
-		DatabaseType p6 = new DatabaseType(DatabaseParameters.DATABASEUSERNAME, "DatabaseUserName", "db user name");
-		DatabaseType p7 = new DatabaseType(DatabaseParameters.DATABASEPASSWORD, "DatabasePassword", "db password");
-		DatabaseType p8 = new DatabaseType(DatabaseParameters.DATABASEDRIVER, "DatabaseDriver", "db driver");
-		DatabaseType p9 = new DatabaseType(DatabaseParameters.DATABASEURL, "DatabaseURL", "db url");
-		DatabaseType p10 = new DatabaseType(DatabaseParameters.DATABASEDIALECT, "DatabaseDialect", "db dialect");
-		DatabaseType p11 = new DatabaseType(DatabaseParameters.DATABASETABLESPACE, "DatabaseTableSpace", "db dialect");
-
 		parameters.add(p1);
 		parameters.add(p2);
 		parameters.add(p3);
 		parameters.add(p4);
 		parameters.add(p5);
-		parameters.add(p6);
-		parameters.add(p7);
-		parameters.add(p8);
-		parameters.add(p9);
-		parameters.add(p10);
-		parameters.add(p11);
 		parameters.add(p12);
 		parameters.add(p13);
 
+		DatabaseType.addDefaultDBPars(parameters);
 		return parameters;
 	}
 

src/main/java/org/gcube/dataanalysis/ecoengine/datatypes/ColumnType.java

@@ -0,0 +1,24 @@
+package org.gcube.dataanalysis.ecoengine.datatypes;
+
+
+//name of columns
+public class ColumnType extends StatisticalType{
+	
+	private String tableName;
+	
+	public ColumnType(String tableName, String name, String description, String defaultValue, boolean optional) {
+		super(name, description, defaultValue, optional);
+		this.tableName=tableName;
+	}
+
+	public String getTableName() {
+		return tableName;
+	}
+
+	public void setTableName(String tableName) {
+		this.tableName = tableName;
+	}
+
+	
+		
+}

src/main/java/org/gcube/dataanalysis/ecoengine/datatypes/ColumnTypesList.java

@@ -0,0 +1,27 @@
+package org.gcube.dataanalysis.ecoengine.datatypes;
+
+import java.util.List;
+
+public class ColumnTypesList  extends StatisticalType {
+	
+	String tableName;
+	protected List<ColumnType> list;
+	
+	public ColumnTypesList(String tableName, String name, String description, boolean optional) {
+		super(name, description, optional);
+		this.tableName=tableName;
+	}
+	
+	public void add(ColumnType st){
+		list.add(st);
+	}
+
+	public List<ColumnType> getList(){
+		return list;
+	}
+	
+	public String getTabelName(){
+		return tableName;
+	}
+	
+}

src/main/java/org/gcube/dataanalysis/ecoengine/datatypes/DatabaseType.java

@@ -1,5 +1,7 @@
 package org.gcube.dataanalysis.ecoengine.datatypes;
 
+import java.util.List;
+
 import org.gcube.dataanalysis.ecoengine.datatypes.enumtypes.DatabaseParameters;
 
 public class DatabaseType extends StatisticalType{
@@ -29,4 +31,20 @@ public class DatabaseType extends StatisticalType{
 		this.databaseParameter = databaseParameters;
 	}
 	
+	public static void addDefaultDBPars(List<StatisticalType> parameters){
+		DatabaseType p1 = new DatabaseType(DatabaseParameters.DATABASEUSERNAME, "DatabaseUserName", "db user name");
+		DatabaseType p2 = new DatabaseType(DatabaseParameters.DATABASEPASSWORD, "DatabasePassword", "db password");
+		DatabaseType p3 = new DatabaseType(DatabaseParameters.DATABASEDRIVER, "DatabaseDriver", "db driver");
+		DatabaseType p4 = new DatabaseType(DatabaseParameters.DATABASEURL, "DatabaseURL", "db url");
+		DatabaseType p5 = new DatabaseType(DatabaseParameters.DATABASEDIALECT, "DatabaseDialect", "db dialect");
+		DatabaseType p6 = new DatabaseType(DatabaseParameters.DATABASETABLESPACE, "DatabaseTableSpace", "db dialect");
+
+		parameters.add(p1);
+		parameters.add(p2);
+		parameters.add(p3);
+		parameters.add(p4);
+		parameters.add(p5);
+		parameters.add(p6);
+	}
+	
 }

src/main/java/org/gcube/dataanalysis/ecoengine/datatypes/enumtypes/TableTemplates.java

@@ -5,10 +5,11 @@ public enum TableTemplates {
 	HSPEN,
 	HCAF,
 	HSPEC,
-	OCCURRENCE,
+	OCCURRENCE_AQUAMAPS,
 	MINMAXLAT,
 	TRAININGSET,
 	TESTSET,
 	GENERIC,
-	CLUSTER
+	CLUSTER,
+	OCCURRENCE_SPECIES
 }

src/main/java/org/gcube/dataanalysis/ecoengine/evaluation/DiscrepancyAnalysis.java

@@ -3,15 +3,14 @@ package org.gcube.dataanalysis.ecoengine.evaluation;
 import java.util.ArrayList;
 import java.util.HashMap;
 import java.util.List;
-import java.util.Map;
 
 import org.gcube.contentmanagement.graphtools.utils.MathFunctions;
 import org.gcube.contentmanagement.lexicalmatcher.utils.AnalysisLogger;
+import org.gcube.dataanalysis.ecoengine.datatypes.ColumnType;
 import org.gcube.dataanalysis.ecoengine.datatypes.DatabaseType;
 import org.gcube.dataanalysis.ecoengine.datatypes.InputTable;
 import org.gcube.dataanalysis.ecoengine.datatypes.PrimitiveType;
 import org.gcube.dataanalysis.ecoengine.datatypes.StatisticalType;
-import org.gcube.dataanalysis.ecoengine.datatypes.enumtypes.DatabaseParameters;
 import org.gcube.dataanalysis.ecoengine.datatypes.enumtypes.PrimitiveTypes;
 import org.gcube.dataanalysis.ecoengine.datatypes.enumtypes.TableTemplates;
 import org.gcube.dataanalysis.ecoengine.interfaces.DataAnalysis;
@@ -54,17 +53,12 @@ public class DiscrepancyAnalysis extends DataAnalysis {
 		templates.add(TableTemplates.TESTSET);
 		InputTable p1 = new InputTable(templates,"FirstTable","First Table");
 		InputTable p2 = new InputTable(templates,"SecondTable","Second Table");
-		PrimitiveType p3 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "FirstTableCsquareColumn","the csquares column name in the first table ","csquarecode");
+		ColumnType p3 = new ColumnType("FirstTable", "FirstTableCsquareColumn", "the csquares column name in the first table", "csquarecode", false);
-		PrimitiveType p4 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "SecondTableCsquareColumn","the csquares column name in the second table","csquarecode");
+		ColumnType p4 = new ColumnType("SecondTable", "SecondTableCsquareColumn", "the csquares column name in the second table", "csquarecode", false);
-		PrimitiveType p5 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "FirstTableProbabilityColumn","the probability column in the first table","probability");
+		ColumnType p5 = new ColumnType("FirstTable", "FirstTableProbabilityColumn", "the probability column in the first table", "probability", false);
-		PrimitiveType p13 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "SecondTableProbabilityColumn","the probability column in the second table","probability");
+		ColumnType p13 = new ColumnType("SecondTable", "SecondTableProbabilityColumn", "the probability column in the second table", "probability", false);
 		PrimitiveType p6 = new PrimitiveType(Float.class.getName(), null, PrimitiveTypes.NUMBER, "ComparisonThreshold","the comparison threshold","0.1");
 		PrimitiveType p7 = new PrimitiveType(Integer.class.getName(), null, PrimitiveTypes.NUMBER, "MaxSamples","the comparison threshold","10000");
-		DatabaseType p8 = new DatabaseType(DatabaseParameters.DATABASEUSERNAME, "DatabaseUserName", "db user name");
-		DatabaseType p9 = new DatabaseType(DatabaseParameters.DATABASEPASSWORD, "DatabasePassword", "db password");
-		DatabaseType p10 = new DatabaseType(DatabaseParameters.DATABASEDRIVER, "DatabaseDriver", "db driver");
-		DatabaseType p11 = new DatabaseType(DatabaseParameters.DATABASEURL, "DatabaseURL", "db url");
-		DatabaseType p12 = new DatabaseType(DatabaseParameters.DATABASEDIALECT, "DatabaseDialect", "db dialect");
 		
 		parameters.add(p1);
 		parameters.add(p2);
@@ -74,12 +68,8 @@ public class DiscrepancyAnalysis extends DataAnalysis {
 		parameters.add(p13);
 		parameters.add(p6);
 		parameters.add(p7);
-		parameters.add(p8);
-		parameters.add(p9);
-		parameters.add(p10);
-		parameters.add(p11);
-		parameters.add(p12);
 		
+		DatabaseType.addDefaultDBPars(parameters);
 		return parameters;
 	}
 

src/main/java/org/gcube/dataanalysis/ecoengine/evaluation/DistributionQualityAnalysis.java

@@ -8,6 +8,7 @@ import java.util.Map;
 
 import org.gcube.contentmanagement.lexicalmatcher.utils.AnalysisLogger;
 import org.gcube.dataanalysis.ecoengine.configuration.AlgorithmConfiguration;
+import org.gcube.dataanalysis.ecoengine.datatypes.ColumnType;
 import org.gcube.dataanalysis.ecoengine.datatypes.DatabaseType;
 import org.gcube.dataanalysis.ecoengine.datatypes.InputTable;
 import org.gcube.dataanalysis.ecoengine.datatypes.PrimitiveType;
@@ -50,25 +51,22 @@ public class DistributionQualityAnalysis extends DataAnalysis {
 		templates.add(TableTemplates.TESTSET);
 		
 		List<TableTemplates> templatesOccurrences = new ArrayList<TableTemplates>();
-		templatesOccurrences.add(TableTemplates.OCCURRENCE);
+		templatesOccurrences.add(TableTemplates.OCCURRENCE_AQUAMAPS);
 		templatesOccurrences.add(TableTemplates.TRAININGSET);
 		templatesOccurrences.add(TableTemplates.TESTSET);
 		
 		InputTable p1 = new InputTable(templatesOccurrences,"PositiveCasesTable","A Table containing positive cases");
 		InputTable p2 = new InputTable(templatesOccurrences,"NegativeCasesTable","A Table containing negative cases");
-		PrimitiveType p3 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "PositiveCasesTableKeyColumn","Positive Cases Table Key Column","csquarecode");
-		PrimitiveType p4 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "NegativeCasesTableKeyColumn","Negative Cases Table Key Column","csquarecode");
 		InputTable p5 = new InputTable(templates,"DistributionTable","A probability distribution table");
-		PrimitiveType p6 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "DistributionTableKeyColumn","Distribution Table Key Column","csquarecode");
+		
-		PrimitiveType p7 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "DistributionTableProbabilityColumn","Distribution Table Probability Column","csquarecode");
+		ColumnType p3 = new ColumnType("PositiveCasesTable", "PositiveCasesTableKeyColumn", "Positive Cases Table Key Column", "csquarecode", false);
+		ColumnType p4 = new ColumnType("NegativeCasesTable", "NegativeCasesTableKeyColumn", "Negative Cases Table Key Column", "csquarecode", false);
+		ColumnType p6 = new ColumnType("DistributionTable", "DistributionTableKeyColumn", "Distribution Table Key Column", "csquarecode", false);
+		ColumnType p7 = new ColumnType("DistributionTable", "DistributionTableProbabilityColumn", "Distribution Table Probability Column", "probability", false);
+		
 		PrimitiveType p8 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "PositiveThreshold","Positive acceptance threshold","0.8");
 		PrimitiveType p9 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "NegativeThreshold","Negative acceptance threshold","0.3");
-		DatabaseType p10 = new DatabaseType(DatabaseParameters.DATABASEUSERNAME, "DatabaseUserName", "db user name");
+		
-		DatabaseType p11 = new DatabaseType(DatabaseParameters.DATABASEPASSWORD, "DatabasePassword", "db password");
-		DatabaseType p12 = new DatabaseType(DatabaseParameters.DATABASEDRIVER, "DatabaseDriver", "db driver");
-		DatabaseType p13 = new DatabaseType(DatabaseParameters.DATABASEURL, "DatabaseURL", "db url");
-		DatabaseType p14 = new DatabaseType(DatabaseParameters.DATABASEDIALECT, "DatabaseDialect", "db dialect");
-
 		parameters.add(p1);
 		parameters.add(p2);
 		parameters.add(p3);
@@ -78,11 +76,8 @@ public class DistributionQualityAnalysis extends DataAnalysis {
 		parameters.add(p7);
 		parameters.add(p8);
 		parameters.add(p9);
-		parameters.add(p10);
+		
-		parameters.add(p11);
+		DatabaseType.addDefaultDBPars(parameters);
-		parameters.add(p12);
-		parameters.add(p13);
-		parameters.add(p14);
 		
 		return parameters;
 	}

src/main/java/org/gcube/dataanalysis/ecoengine/evaluation/HabitatRepresentativeness.java

@@ -8,6 +8,7 @@ import java.util.Map;
 import org.gcube.contentmanagement.lexicalmatcher.utils.AnalysisLogger;
 import org.gcube.contentmanagement.lexicalmatcher.utils.MathFunctions;
 import org.gcube.dataanalysis.ecoengine.configuration.AlgorithmConfiguration;
+import org.gcube.dataanalysis.ecoengine.datatypes.ColumnTypesList;
 import org.gcube.dataanalysis.ecoengine.datatypes.DatabaseType;
 import org.gcube.dataanalysis.ecoengine.datatypes.InputTable;
 import org.gcube.dataanalysis.ecoengine.datatypes.PrimitiveType;
@@ -20,7 +21,6 @@ import org.gcube.dataanalysis.ecoengine.models.cores.pca.PrincipalComponentAnaly
 import org.gcube.dataanalysis.ecoengine.utils.DatabaseFactory;
 import org.gcube.dataanalysis.ecoengine.utils.Operations;
 import org.gcube.dataanalysis.ecoengine.utils.Transformations;
-import org.hibernate.SessionFactory;
 
 public class HabitatRepresentativeness extends DataAnalysis {
 
@@ -45,7 +45,7 @@ public class HabitatRepresentativeness extends DataAnalysis {
 		templates.add(TableTemplates.TESTSET);
 
 		List<TableTemplates> templatesOccurrences = new ArrayList<TableTemplates>();
-		templatesOccurrences.add(TableTemplates.OCCURRENCE);
+		templatesOccurrences.add(TableTemplates.OCCURRENCE_AQUAMAPS);
 		templatesOccurrences.add(TableTemplates.TRAININGSET);
 		templatesOccurrences.add(TableTemplates.TESTSET);
 		
@@ -53,23 +53,17 @@ public class HabitatRepresentativeness extends DataAnalysis {
 		PrimitiveType p2 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "ProjectingAreaFeaturesOptionalCondition","optional filter for taking area rows","oceanarea>0",true);
 		InputTable p3 = new InputTable(templatesOccurrences,"PositiveCasesTable","A Table containing positive cases");
 		InputTable p4 = new InputTable(templatesOccurrences,"NegativeCasesTable","A Table containing negative cases");
-		PrimitiveType p5 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "FeaturesColumns","fetures columns names separated by comma","depthmean,depthmax,depthmin, sstanmean,sbtanmean,salinitymean,salinitybmean, primprodmean,iceconann,landdist,oceanarea");
+		
-		DatabaseType p6 = new DatabaseType(DatabaseParameters.DATABASEUSERNAME, "DatabaseUserName", "db user name");
+//		PrimitiveType p5 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "FeaturesColumns","fetures columns names separated by comma","depthmean,depthmax,depthmin, sstanmean,sbtanmean,salinitymean,salinitybmean, primprodmean,iceconann,landdist,oceanarea");
-		DatabaseType p7 = new DatabaseType(DatabaseParameters.DATABASEPASSWORD, "DatabasePassword", "db password");
+		ColumnTypesList p5 = new ColumnTypesList ("PositiveCasesTable","FeaturesColumns", "Features columns", false);
-		DatabaseType p8 = new DatabaseType(DatabaseParameters.DATABASEDRIVER, "DatabaseDriver", "db driver");
-		DatabaseType p9 = new DatabaseType(DatabaseParameters.DATABASEURL, "DatabaseURL", "db url");
-		DatabaseType p10 = new DatabaseType(DatabaseParameters.DATABASEDIALECT, "DatabaseDialect", "db dialect");
 
 		parameters.add(p1);
 		parameters.add(p2);
 		parameters.add(p3);
 		parameters.add(p4);
 		parameters.add(p5);
-		parameters.add(p6);
+		
-		parameters.add(p7);
+		DatabaseType.addDefaultDBPars(parameters);
-		parameters.add(p8);
-		parameters.add(p9);
-		parameters.add(p10);
 		return parameters;
 	}
 
@@ -203,7 +197,7 @@ public class HabitatRepresentativeness extends DataAnalysis {
 			status = 0;
 			String projectingAreaTable = config.getParam("ProjectingAreaTable");
 			String projectingAreaFeaturesOptionalCondition = config.getParam("ProjectingAreaFeaturesOptionalCondition");
-			String FeaturesColumns = config.getParam("FeaturesColumns");
+			String FeaturesColumns = config.getParam("FeaturesColumns").replace(AlgorithmConfiguration.getListSeparator(), ",");
 			String positiveCasesTable = config.getParam("PositiveCasesTable");
 			String negativeCasesTable = config.getParam("NegativeCasesTable");
 			connection = AlgorithmConfiguration.getConnectionFromConfig(config);

src/main/java/org/gcube/dataanalysis/ecoengine/models/ModelAquamapsNN.java

@@ -15,6 +15,7 @@ import org.gcube.dataanalysis.ecoengine.configuration.AlgorithmConfiguration;
 import org.gcube.dataanalysis.ecoengine.datatypes.DatabaseType;
 import org.gcube.dataanalysis.ecoengine.datatypes.InputTable;
 import org.gcube.dataanalysis.ecoengine.datatypes.PrimitiveType;
+import org.gcube.dataanalysis.ecoengine.datatypes.PrimitiveTypesList;
 import org.gcube.dataanalysis.ecoengine.datatypes.ServiceType;
 import org.gcube.dataanalysis.ecoengine.datatypes.StatisticalType;
 import org.gcube.dataanalysis.ecoengine.datatypes.enumtypes.DatabaseParameters;
@@ -48,12 +49,12 @@ public class ModelAquamapsNN implements Model {
 	public List<StatisticalType> getInputParameters() {
 		List<StatisticalType> parameters = new ArrayList<StatisticalType>();
 		List<TableTemplates> templatesOccurrences = new ArrayList<TableTemplates>();
-		templatesOccurrences.add(TableTemplates.OCCURRENCE);
+		templatesOccurrences.add(TableTemplates.OCCURRENCE_AQUAMAPS);
 		
 		InputTable p1 = new InputTable(templatesOccurrences,"AbsenceDataTable","A Table containing absence points");
 		InputTable p2 = new InputTable(templatesOccurrences,"PresenceDataTable","A Table containing positive occurrences");
 		PrimitiveType p3 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "SpeciesName","Species Code of the fish the NN will correspond to","Fis-10407");
-		PrimitiveType p4 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "LayersNeurons","a list of neurons number for each inner layer separated by comma","100,2");
+		PrimitiveTypesList p4 = new PrimitiveTypesList(PrimitiveTypes.NUMBER,"LayersNeurons","a list of neurons number for each inner layer separated by comma",false);
 
 		DatabaseType p5 = new DatabaseType(DatabaseParameters.DATABASEUSERNAME, "DatabaseUserName", "db user name");
 		DatabaseType p6 = new DatabaseType(DatabaseParameters.DATABASEPASSWORD, "DatabasePassword", "db password");
@@ -118,7 +119,7 @@ public class ModelAquamapsNN implements Model {
 		String layersNeurons$ = Input.getParam("LayersNeurons");
 		if ((layersNeurons$!=null)&&(layersNeurons$.length()>0))
 		{
-			String [] split = layersNeurons$.split(",");
+			String [] split = layersNeurons$.split(AlgorithmConfiguration.getListSeparator());
 			layersNeurons = new int[split.length];
 			for (int i = 0;i<split.length;i++){
 				layersNeurons[i] = Integer.parseInt(split[i]);

src/main/java/org/gcube/dataanalysis/ecoengine/models/ModelAquamapsNNNS.java

@@ -47,7 +47,7 @@ public class ModelAquamapsNNNS implements Model {
 	public List<StatisticalType> getInputParameters() {
 		List<StatisticalType> parameters = new ArrayList<StatisticalType>();
 		List<TableTemplates> templatesOccurrences = new ArrayList<TableTemplates>();
-		templatesOccurrences.add(TableTemplates.OCCURRENCE);
+		templatesOccurrences.add(TableTemplates.OCCURRENCE_AQUAMAPS);
 		
 		InputTable p1 = new InputTable(templatesOccurrences,"AbsenceDataTable","A Table containing absence points");
 		InputTable p2 = new InputTable(templatesOccurrences,"PresenceDataTable","A Table containing positive occurrences");

src/main/java/org/gcube/dataanalysis/ecoengine/models/ModelHSPEN.java

@@ -432,7 +432,7 @@ public class ModelHSPEN implements Model {
 	public List<StatisticalType> getInputParameters() {
 		List<StatisticalType> parameters = new ArrayList<StatisticalType>();
 		List<TableTemplates> templatesOccurrences = new ArrayList<TableTemplates>();
-		templatesOccurrences.add(TableTemplates.OCCURRENCE);
+		templatesOccurrences.add(TableTemplates.OCCURRENCE_AQUAMAPS);
 		List<TableTemplates> templateHspen = new ArrayList<TableTemplates>();
 		templateHspen.add(TableTemplates.HSPEN);
 		List<TableTemplates> templateHcaf = new ArrayList<TableTemplates>();

src/main/java/org/gcube/dataanalysis/ecoengine/spatialdistributions/AquamapsSuitable.java

@@ -251,7 +251,7 @@ public class AquamapsSuitable implements SpatialProbabilityDistributionTable{
 	public List<StatisticalType> getInputParameters() {
 		List<StatisticalType> parameters = new ArrayList<StatisticalType>();
 		List<TableTemplates> templatesOccurrence = new ArrayList<TableTemplates>();
-		templatesOccurrence.add(TableTemplates.OCCURRENCE);
+		templatesOccurrence.add(TableTemplates.OCCURRENCE_AQUAMAPS);
 		List<TableTemplates> templateHspen = new ArrayList<TableTemplates>();
 		templateHspen.add(TableTemplates.HSPEN);
 		List<TableTemplates> templateHcaf = new ArrayList<TableTemplates>();
@@ -263,13 +263,6 @@ public class AquamapsSuitable implements SpatialProbabilityDistributionTable{
 		PrimitiveType p4 = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.STRING, "DistributionTableLabel","Name of the HSPEC probability distribution","hspec");
 		InputTable p5 = new InputTable(templatesOccurrence,"OccurrencePointsTable","The Occurrence points table for calculating the bounding box","occurrencecells");
 		PrimitiveType p6  = new PrimitiveType(String.class.getName(), null, PrimitiveTypes.CONSTANT, "CreateTable","Create New Table for each computation","true");		
-
-		DatabaseType p7 = new DatabaseType(DatabaseParameters.DATABASEUSERNAME, "DatabaseUserName", "db user name");
-		DatabaseType p8 = new DatabaseType(DatabaseParameters.DATABASEPASSWORD, "DatabasePassword", "db password");
-		DatabaseType p9 = new DatabaseType(DatabaseParameters.DATABASEDRIVER, "DatabaseDriver", "db driver");
-		DatabaseType p10 = new DatabaseType(DatabaseParameters.DATABASEURL, "DatabaseURL", "db url");
-		DatabaseType p11 = new DatabaseType(DatabaseParameters.DATABASEDIALECT, "DatabaseDialect", "db dialect");
-		DatabaseType p12 = new DatabaseType(DatabaseParameters.DATABASETABLESPACE, "DatabaseTableSpace", "db tablespace");
 		
 		parameters.add(p1);
 		parameters.add(p2);
@@ -277,13 +270,8 @@ public class AquamapsSuitable implements SpatialProbabilityDistributionTable{
 		parameters.add(p4);
 		parameters.add(p5);
 		parameters.add(p6);
-		parameters.add(p7);
-		parameters.add(p8);
-		parameters.add(p9);
-		parameters.add(p10);
-		parameters.add(p11);
-		parameters.add(p12);
 		
+		DatabaseType.addDefaultDBPars(parameters);
 		return parameters;
 	}
 

src/main/java/org/gcube/dataanalysis/ecoengine/test/regression/RegressionTestTransducers.java

@@ -12,8 +12,9 @@ public class RegressionTestTransducers {
 public static void main(String[] args) throws Exception {
 		
 		System.out.println("TEST 1");
-
+		List<Transducerer> trans = null;
-		List<Transducerer> trans = TransducerersFactory.getTransducerers(testConfigLocal());
+		
+		trans = TransducerersFactory.getTransducerers(testConfigLocal());
 		trans.get(0).init();
 		Regressor.process(trans.get(0));
 		trans = null;
@@ -32,6 +33,11 @@ public static void main(String[] args) throws Exception {
 		trans.get(0).init();
 		Regressor.process(trans.get(0));
 		trans = null;
+		
+		trans = TransducerersFactory.getTransducerers(testConfigLocal5());
+		trans.get(0).init();
+		Regressor.process(trans.get(0));
+		trans = null;
 }
 
 	
@@ -81,5 +87,26 @@ public static void main(String[] args) throws Exception {
 		
 		return config;
 	}
+	
+	private static AlgorithmConfiguration testConfigLocal5() {
+		
+		AlgorithmConfiguration config = Regressor.getConfig();
+		config.setAgent("OCCURRENCES_MERGER");
+		
+		config.setParam("longitudeColumn", "decimallongitude");
+		config.setParam("latitudeColumn", "decimallatitude");
+		config.setParam("recordedByColumn", "recordedby");
+		config.setParam("scientificNameColumn", "scientificname");
+		config.setParam("eventDateColumn", "eventdate");
+		config.setParam("lastModificationColumn", "modified");
+		config.setParam("rightTableName", "whitesharkoccurrences2");
+		config.setParam("leftTableName", "whitesharkoccurrences1");
+		config.setParam("mergedTableName", "whitesharkoccurrencesmerged");
+		config.setParam("spatialTolerance", "0.5");
+		config.setParam("confidence", "0.8");
+		
+		
+		return config;
+	}
 
 }

src/main/java/org/gcube/dataanalysis/ecoengine/test/regression/Regressor.java

@@ -1,6 +1,5 @@
 package org.gcube.dataanalysis.ecoengine.test.regression;
 
-import org.gcube.contentmanagement.lexicalmatcher.utils.AnalysisLogger;
 import org.gcube.dataanalysis.ecoengine.configuration.AlgorithmConfiguration;
 import org.gcube.dataanalysis.ecoengine.interfaces.ComputationalAgent;
 
@@ -24,8 +23,9 @@ public class Regressor {
 				Thread.sleep(1000);
 			}
 		} else
-			AnalysisLogger.getLogger().trace("Generator Algorithm Not Supported");
+			System.out.println("Generator Algorithm Not Supported" );
 
+		System.out.println("-|"+agent.getStatus()); 
 	}
 
 	public class ThreadCalculator implements Runnable {

src/main/java/org/gcube/dataanalysis/ecoengine/transducers/BioClimateHCAFTransducer.java

@@ -35,28 +35,15 @@ public class BioClimateHCAFTransducer extends BioClimateHSPECTransducer{
 	@Override
 	public List<StatisticalType> getInputParameters() {
 		List<StatisticalType> parameters = new ArrayList<StatisticalType>();
-		
-		DatabaseType p1 = new DatabaseType(DatabaseParameters.DATABASEUSERNAME, "DatabaseUserName", "db user name");
-		DatabaseType p2 = new DatabaseType(DatabaseParameters.DATABASEPASSWORD, "DatabasePassword", "db password");
-		DatabaseType p3 = new DatabaseType(DatabaseParameters.DATABASEDRIVER, "DatabaseDriver", "db driver");
-		DatabaseType p4 = new DatabaseType(DatabaseParameters.DATABASEURL, "DatabaseURL", "db url");
-		DatabaseType p5 = new DatabaseType(DatabaseParameters.DATABASEDIALECT, "DatabaseDialect", "db dialect");
-		DatabaseType p6 = new DatabaseType(DatabaseParameters.DATABASETABLESPACE, "DatabaseTableSpace", "db dialect");
-
 		List<TableTemplates> templateHspec = new ArrayList<TableTemplates>();
 		templateHspec.add(TableTemplates.HCAF);
 		TablesList p7 = new TablesList(templateHspec, "HCAF_TABLE_LIST", "List of HCAF tables to analyze", false);
 		PrimitiveTypesList p8 = new PrimitiveTypesList(PrimitiveTypes.STRING, "HCAF_TABLE_NAMES", "List of HCAF table names to be used as labels", false);
 		
-		parameters.add(p1);
-		parameters.add(p2);
-		parameters.add(p3);
-		parameters.add(p4);
-		parameters.add(p5);
-		parameters.add(p6);
 		parameters.add(p7);
 		parameters.add(p8);
 		
+		DatabaseType.addDefaultDBPars(parameters);
 		return parameters;
 	}
 

src/main/java/org/gcube/dataanalysis/ecoengine/transducers/BioClimateHSPECTransducer.java

@@ -72,13 +72,6 @@ public class BioClimateHSPECTransducer implements Transducerer{
 	public List<StatisticalType> getInputParameters() {
 		List<StatisticalType> parameters = new ArrayList<StatisticalType>();
 		
-		DatabaseType p1 = new DatabaseType(DatabaseParameters.DATABASEUSERNAME, "DatabaseUserName", "db user name");
-		DatabaseType p2 = new DatabaseType(DatabaseParameters.DATABASEPASSWORD, "DatabasePassword", "db password");
-		DatabaseType p3 = new DatabaseType(DatabaseParameters.DATABASEDRIVER, "DatabaseDriver", "db driver");
-		DatabaseType p4 = new DatabaseType(DatabaseParameters.DATABASEURL, "DatabaseURL", "db url");
-		DatabaseType p5 = new DatabaseType(DatabaseParameters.DATABASEDIALECT, "DatabaseDialect", "db dialect");
-		DatabaseType p6 = new DatabaseType(DatabaseParameters.DATABASETABLESPACE, "DatabaseTableSpace", "db dialect");
-
 		List<TableTemplates> templateHspec = new ArrayList<TableTemplates>();
 		templateHspec.add(TableTemplates.HSPEC);
 		TablesList p7 = new TablesList(templateHspec, "HSPEC_TABLE_LIST", "List of HSPEC tables to analyze", false);
@@ -86,16 +79,10 @@ public class BioClimateHSPECTransducer implements Transducerer{
 		
 		PrimitiveType p9 = new PrimitiveType(Double.class.getName(), null, PrimitiveTypes.NUMBER, "Threshold", "A threshold of probability over which the abundancy per species will be calculated","0.5");
 		
-		parameters.add(p1);
-		parameters.add(p2);
-		parameters.add(p3);
-		parameters.add(p4);
-		parameters.add(p5);
-		parameters.add(p6);
 		parameters.add(p7);
 		parameters.add(p8);
 		parameters.add(p9);
-		
+		DatabaseType.addDefaultDBPars(parameters);
 		return parameters;
 	}
 

src/main/java/org/gcube/dataanalysis/ecoengine/transducers/BioClimateHSPENTransducer.java

@@ -35,28 +35,14 @@ public class BioClimateHSPENTransducer extends BioClimateHSPECTransducer{
 	@Override
 	public List<StatisticalType> getInputParameters() {
 		List<StatisticalType> parameters = new ArrayList<StatisticalType>();
-		
-		DatabaseType p1 = new DatabaseType(DatabaseParameters.DATABASEUSERNAME, "DatabaseUserName", "db user name");
-		DatabaseType p2 = new DatabaseType(DatabaseParameters.DATABASEPASSWORD, "DatabasePassword", "db password");
-		DatabaseType p3 = new DatabaseType(DatabaseParameters.DATABASEDRIVER, "DatabaseDriver", "db driver");
-		DatabaseType p4 = new DatabaseType(DatabaseParameters.DATABASEURL, "DatabaseURL", "db url");
-		DatabaseType p5 = new DatabaseType(DatabaseParameters.DATABASEDIALECT, "DatabaseDialect", "db dialect");
-		DatabaseType p6 = new DatabaseType(DatabaseParameters.DATABASETABLESPACE, "DatabaseTableSpace", "db dialect");
-
 		List<TableTemplates> templateHspec = new ArrayList<TableTemplates>();
 		templateHspec.add(TableTemplates.HSPEN);
 		TablesList p7 = new TablesList(templateHspec, "HSPEN_TABLE_LIST", "List of HSPEN tables containing the species for which the salinity will be analyzed", false);
 		PrimitiveTypesList p8 = new PrimitiveTypesList(PrimitiveTypes.STRING, "HSPEN_TABLE_NAMES", "List of HSPEN table names to be used as labels", false);
 		
-		parameters.add(p1);
-		parameters.add(p2);
-		parameters.add(p3);
-		parameters.add(p4);
-		parameters.add(p5);
-		parameters.add(p6);
 		parameters.add(p7);
 		parameters.add(p8);
-		
+		DatabaseType.addDefaultDBPars(parameters);
 		return parameters;
 	}
 

src/main/java/org/gcube/dataanalysis/ecoengine/transducers/InterpolationTransducer.java

@@ -1,8 +1,6 @@
 package org.gcube.dataanalysis.ecoengine.transducers;
 
-import java.awt.Image;
 import java.util.ArrayList;
-import java.util.HashMap;
 import java.util.List;
 
 import org.gcube.dataanalysis.ecoengine.configuration.AlgorithmConfiguration;
@@ -10,10 +8,9 @@ import org.gcube.dataanalysis.ecoengine.configuration.INFRASTRUCTURE;
 import org.gcube.dataanalysis.ecoengine.datatypes.DatabaseType;
 import org.gcube.dataanalysis.ecoengine.datatypes.InputTable;
 import org.gcube.dataanalysis.ecoengine.datatypes.OutputTable;
-import org.gcube.dataanalysis.ecoengine.datatypes.TablesList;
 import org.gcube.dataanalysis.ecoengine.datatypes.PrimitiveType;
 import org.gcube.dataanalysis.ecoengine.datatypes.StatisticalType;
-import org.gcube.dataanalysis.ecoengine.datatypes.enumtypes.DatabaseParameters;
+import org.gcube.dataanalysis.ecoengine.datatypes.TablesList;
 import org.gcube.dataanalysis.ecoengine.datatypes.enumtypes.PrimitiveTypes;
 import org.gcube.dataanalysis.ecoengine.datatypes.enumtypes.TableTemplates;
 import org.gcube.dataanalysis.ecoengine.evaluation.bioclimate.InterpolateTables;
@@ -67,14 +64,6 @@ public class InterpolationTransducer implements Transducerer{
 	@Override
 	public List<StatisticalType> getInputParameters() {
 		List<StatisticalType> parameters = new ArrayList<StatisticalType>();
-		
-		DatabaseType p1 = new DatabaseType(DatabaseParameters.DATABASEUSERNAME, "DatabaseUserName", "db user name");
-		DatabaseType p2 = new DatabaseType(DatabaseParameters.DATABASEPASSWORD, "DatabasePassword", "db password");
-		DatabaseType p3 = new DatabaseType(DatabaseParameters.DATABASEDRIVER, "DatabaseDriver", "db driver");
-		DatabaseType p4 = new DatabaseType(DatabaseParameters.DATABASEURL, "DatabaseURL", "db url");
-		DatabaseType p5 = new DatabaseType(DatabaseParameters.DATABASEDIALECT, "DatabaseDialect", "db dialect");
-		DatabaseType p6 = new DatabaseType(DatabaseParameters.DATABASETABLESPACE, "DatabaseTableSpace", "db dialect");
-
 		List<TableTemplates> templates = new ArrayList<TableTemplates>();
 		templates.add(TableTemplates.HCAF);
 		
@@ -86,12 +75,6 @@ public class InterpolationTransducer implements Transducerer{
 		
 		PrimitiveType p12 = new PrimitiveType(Enum.class.getName(), InterpolateTables.INTERPOLATIONFUNCTIONS.values(), PrimitiveTypes.ENUMERATED, "InterpolationFunction", "The interpolation Function to use",""+InterpolateTables.INTERPOLATIONFUNCTIONS.LINEAR);
 				
-		parameters.add(p1);
-		parameters.add(p2);
-		parameters.add(p3);
-		parameters.add(p4);
-		parameters.add(p5);
-		parameters.add(p6);
 		parameters.add(p7);
 		parameters.add(p8);
 		parameters.add(p9);
@@ -99,7 +82,7 @@ public class InterpolationTransducer implements Transducerer{
 		parameters.add(p11);
 		parameters.add(p12);
 		
-		
+		DatabaseType.addDefaultDBPars(parameters);
 		return parameters;
 	}
 

src/main/java/org/gcube/dataanalysis/ecoengine/transducers/OccurrencePointsMerger.java

@@ -1,12 +1,10 @@
 package org.gcube.dataanalysis.ecoengine.transducers;
 
-import java.text.ParseException;
 import java.text.SimpleDateFormat;
 import java.util.ArrayList;
 import java.util.Calendar;
 import java.util.Date;
 import java.util.List;
-import java.util.Locale;
 
 import org.gcube.contentmanagement.graphtools.utils.DateGuesser;
 import org.gcube.contentmanagement.lexicalmatcher.utils.AnalysisLogger;
@@ -14,30 +12,40 @@ import org.gcube.contentmanagement.lexicalmatcher.utils.DatabaseFactory;
 import org.gcube.contentmanagement.lexicalmatcher.utils.DistanceCalculator;
 import org.gcube.dataanalysis.ecoengine.configuration.AlgorithmConfiguration;
 import org.gcube.dataanalysis.ecoengine.configuration.INFRASTRUCTURE;
+import org.gcube.dataanalysis.ecoengine.datatypes.ColumnType;
+import org.gcube.dataanalysis.ecoengine.datatypes.DatabaseType;
+import org.gcube.dataanalysis.ecoengine.datatypes.InputTable;
+import org.gcube.dataanalysis.ecoengine.datatypes.OutputTable;
+import org.gcube.dataanalysis.ecoengine.datatypes.PrimitiveType;
+import org.gcube.dataanalysis.ecoengine.datatypes.ServiceType;
 import org.gcube.dataanalysis.ecoengine.datatypes.StatisticalType;
+import org.gcube.dataanalysis.ecoengine.datatypes.enumtypes.PrimitiveTypes;
+import org.gcube.dataanalysis.ecoengine.datatypes.enumtypes.ServiceParameters;
+import org.gcube.dataanalysis.ecoengine.datatypes.enumtypes.TableTemplates;
 import org.gcube.dataanalysis.ecoengine.interfaces.Transducerer;
 import org.gcube.dataanalysis.ecoengine.test.regression.Regressor;
 import org.gcube.dataanalysis.ecoengine.utils.DatabaseUtils;
+import org.gcube.dataanalysis.ecoengine.utils.ResourceFactory;
 import org.hibernate.SessionFactory;
 
-public class OccurrencePointsMerger implements Transducerer{
+public class OccurrencePointsMerger implements Transducerer {
 
-	static String longitudeColumn= "longitudeColumn";
+	static String longitudeColumn = "longitudeColumn";
-	static String latitudeColumn= "latitudeColumn";
+	static String latitudeColumn = "latitudeColumn";
-	static String recordedByColumn= "recordedByColumn";
+	static String recordedByColumn = "recordedByColumn";
 	static String scientificNameColumn = "scientificNameColumn";
 	static String eventDateColumn = "eventDateColumn";
 	static String lastModificationColumn = "lastModificationColumn";
-	static String rightTableNameF= "rightTableName";
+	static String rightTableNameF = "rightTableName";
 	static String leftTableNameF = "leftTableName";
 	static String mergedTableNameF = "mergedTableName";
-	static String spatialTolerance= "spatialTolerance";
+	static String spatialTolerance = "spatialTolerance";
-	static String confidence= "confidence";
+	static String confidence = "confidence";
-	
+
 	protected List<OccurrenceRecord> records_left;
 	protected List<OccurrenceRecord> records_right;
 	protected AlgorithmConfiguration config;
-	
+
 	protected String lonFld;
 	protected String latFld;
 	protected String recordedByFld;
@@ -54,377 +62,428 @@ public class OccurrencePointsMerger implements Transducerer{
 	protected List<OccurrenceRecord> objectstodelete;
 	protected List<Object> columnsNames;
 	protected SessionFactory dbconnection;
-	
+	protected float status;
-	protected class OccurrenceRecord{
+
-		
+	protected class OccurrenceRecord {
+
 		public String scientificName;
 		public String recordedby;
 		public Calendar eventdate;
 		public Calendar modifdate;
-//		public String locality;
+		// public String locality;
-//		public String country;
+		// public String country;
 		public float x;
 		public float y;
-		
+
-//		Map<String,String> metadata;
+		// Map<String,String> metadata;
 		public List<String> otherValues;
-		public OccurrenceRecord(){
+
+		public OccurrenceRecord() {
 			otherValues = new ArrayList<String>();
 		}
 	}
 
-	public static String convert2conventionalFormat(Calendar date){
+	public static String convert2conventionalFormat(Calendar date) {
-		if (date==null)
+		if (date == null)
-				return "";
+			return "";
 		SimpleDateFormat formatter = new SimpleDateFormat("MM/dd/yy KK:mm:ss a");
 		String formattedDate = formatter.format(new Date(date.getTimeInMillis()));
 		return formattedDate;
-		
+	}
-}
+
 	boolean displaydateconvert = true;
-	public OccurrenceRecord row2OccurrenceRecord(Object[] row){
+
+	public OccurrenceRecord row2OccurrenceRecord(Object[] row) {
 		OccurrenceRecord record = new OccurrenceRecord();
 		int index = 0;
-		
+
-		for (Object name:columnsNames){
+		for (Object name : columnsNames) {
-			String name$ = ""+name;
+			String name$ = "" + name;
-			String value$ = ""+row[index];
+			String value$ = "" + row[index];
-			if (name$.equalsIgnoreCase(lonFld)){
+			if (name$.equalsIgnoreCase(lonFld)) {
-				record.x=Float.parseFloat(value$);
+				record.x = Float.parseFloat(value$);
-			}
+			} else if (name$.equalsIgnoreCase(latFld)) {
-			else if (name$.equalsIgnoreCase(latFld)){
+				record.y = Float.parseFloat(value$);
-				record.y=Float.parseFloat(value$);
+			} else if (name$.equalsIgnoreCase(recordedByFld)) {
-			}
+				record.recordedby = value$;
-			else if (name$.equalsIgnoreCase(recordedByFld)){
+			} else if (name$.equalsIgnoreCase(scientificNameFld)) {
-				record.recordedby=value$;
+				record.scientificName = value$;
-			}
+			} else if (name$.equalsIgnoreCase(eventDatFld)) {
-			else if (name$.equalsIgnoreCase(scientificNameFld)){
+				if ((value$ == null) || (value$.length() == 0)) {
-				record.scientificName=value$;
+					record.eventdate = null;
-			}
+				} else {
-			else if (name$.equalsIgnoreCase(eventDatFld)){
+					/*
-				if ((value$==null) || (value$.length()==0)){
+					 * SimpleDateFormat formatter = new SimpleDateFormat("MM/dd/yy KK:mm a",Locale.UK); try { Date d = (Date) formatter.parse(value$); Calendar cal = Calendar.getInstance(); cal.setTime(d); System.out.println("From "+value$+"->"+(cal.get(Calendar.MONTH)+1)+" "+cal.get(Calendar.DAY_OF_MONTH)+" "+cal.get(Calendar.YEAR)+" "+cal.get(Calendar.HOUR)+" "+cal.get(Calendar.MINUTE)); // System.out.println("->"+cal.toString()); } catch (ParseException e) { // TODO Auto-generated catch block e.printStackTrace(); }
-					record.eventdate=null;
+					 */
-				}
+					record.eventdate = DateGuesser.convertDate(value$);
-				else{
+					if (displaydateconvert) {
-				/*	
+						AnalysisLogger.getLogger().trace("From " + value$ + "->" + convert2conventionalFormat(record.eventdate) + " pattern " + DateGuesser.getPattern(value$));
-				SimpleDateFormat formatter = new SimpleDateFormat("MM/dd/yy KK:mm a",Locale.UK);
+						displaydateconvert = false;
-				try {
-					Date d = (Date) formatter.parse(value$);
-					Calendar cal = Calendar.getInstance();
-					cal.setTime(d);
-					System.out.println("From "+value$+"->"+(cal.get(Calendar.MONTH)+1)+" "+cal.get(Calendar.DAY_OF_MONTH)+" "+cal.get(Calendar.YEAR)+" "+cal.get(Calendar.HOUR)+" "+cal.get(Calendar.MINUTE));	
-//					System.out.println("->"+cal.toString());
-				} catch (ParseException e) {
-					// TODO Auto-generated catch block
-					e.printStackTrace();
-				}
-				*/
-					record.eventdate=DateGuesser.convertDate(value$);
-					if (displaydateconvert)
-					{	AnalysisLogger.getLogger().trace("From "+value$+"->"+convert2conventionalFormat(record.eventdate)+" pattern "+DateGuesser.getPattern(value$));
-						displaydateconvert=false;
 					}
-					
+
-				
 				}
-			}
+			} else if (name$.equalsIgnoreCase(modifDatFld)) {
-			else if (name$.equalsIgnoreCase(modifDatFld)){
+				record.modifdate = DateGuesser.convertDate(value$);
-				record.modifdate=DateGuesser.convertDate(value$);
+			} else
-			}
-			else
 				record.otherValues.add(value$);
-			
+
 			index++;
 		}
-		
+
 		return record;
 	}
-	
+
-	public String occurrenceRecord2String(OccurrenceRecord record){
+	public String occurrenceRecord2String(OccurrenceRecord record) {
-		StringBuffer buffer =new StringBuffer();
+		StringBuffer buffer = new StringBuffer();
 		int index = 0;
-		int k=0;
+		int k = 0;
 		int nNames = columnsNames.size();
-		for (Object name:columnsNames){
+		for (Object name : columnsNames) {
-			
+
-			String name$ = ""+name;
+			String name$ = "" + name;
 			String value$ = "''";
-			if (name$.equalsIgnoreCase(lonFld)){
+			if (name$.equalsIgnoreCase(lonFld)) {
-				value$="'"+record.x+"'";
+				value$ = "'" + record.x + "'";
-			}
+			} else if (name$.equalsIgnoreCase(latFld)) {
-			else if (name$.equalsIgnoreCase(latFld)){
+				value$ = "'" + record.y + "'";
-				value$="'"+record.y+"'";
+			} else if (name$.equalsIgnoreCase(recordedByFld)) {
-			}
+				if (record.recordedby != null)
-			else if (name$.equalsIgnoreCase(recordedByFld)){
+					value$ = "'" + record.recordedby + "'";
-				if (record.recordedby!=null)
+			} else if (name$.equalsIgnoreCase(scientificNameFld)) {
-					value$="'"+record.recordedby+"'";
+				if (record.scientificName != null)
-			}
+					value$ = "'" + record.scientificName + "'";
-			else if (name$.equalsIgnoreCase(scientificNameFld)){
+			} else if (name$.equalsIgnoreCase(eventDatFld)) {
-				if (record.scientificName!=null)
+				if (record.eventdate != null) {
-					value$="'"+record.scientificName+"'";
+					value$ = "'" + convert2conventionalFormat(record.eventdate) + "'";
-			}
+					// value$="'"+record.eventdate.getTimeInMillis()+"'";
-			else if (name$.equalsIgnoreCase(eventDatFld)){
-				if (record.eventdate!=null){
-					value$="'"+convert2conventionalFormat(record.eventdate)+"'";
-//					value$="'"+record.eventdate.getTimeInMillis()+"'";
 				}
-			}
+			} else if (name$.equalsIgnoreCase(modifDatFld)) {
-			else if (name$.equalsIgnoreCase(modifDatFld)){
+				if (record.modifdate != null) {
-				if (record.modifdate!=null){
+					value$ = "'" + convert2conventionalFormat(record.modifdate) + "'";
-					value$="'"+convert2conventionalFormat(record.modifdate)+"'";
+					// value$="'"+record.modifdate.getTimeInMillis()+"'";
-//					value$="'"+record.modifdate.getTimeInMillis()+"'";
 				}
-			}
+			} else {
-			else{
+				if (record.otherValues != null) {
-				if (record.otherValues!=null){
+					value$ = "'" + record.otherValues.get(k) + "'";
-					value$ = "'"+record.otherValues.get(k)+"'";
 					k++;
 				}
 			}
 			buffer.append(value$);
-			if (index<nNames-1){
+			if (index < nNames - 1) {
 				buffer.append(",");
 			}
-			
+
 			index++;
 		}
-		
+
 		return buffer.toString();
 	}
-	
+
-	
+	public static void main(String[] args) throws Exception {
-	public static void main(String[] args) throws Exception{
 		AlgorithmConfiguration config = Regressor.getConfig();
 		config.setNumberOfResources(1);
-		config.setParam(longitudeColumn,"decimallongitude");
+		config.setParam(longitudeColumn, "decimallongitude");
-		config.setParam(latitudeColumn,"decimallatitude");
+		config.setParam(latitudeColumn, "decimallatitude");
-		config.setParam(recordedByColumn,"recordedby");
+		config.setParam(recordedByColumn, "recordedby");
-		config.setParam(scientificNameColumn,"scientificname");
+		config.setParam(scientificNameColumn, "scientificname");
-		config.setParam(eventDateColumn,"eventdate");
+		config.setParam(eventDateColumn, "eventdate");
-		config.setParam(lastModificationColumn,"modified");
+		config.setParam(lastModificationColumn, "modified");
-		config.setParam(rightTableNameF,"whitesharkoccurrences2");
+		config.setParam(rightTableNameF, "whitesharkoccurrences2");
-		config.setParam(leftTableNameF,"whitesharkoccurrences1");
+		config.setParam(leftTableNameF, "whitesharkoccurrences1");
-//		config.setParam(rightTableNameF,"whitesharkoccurrences2");
+		// config.setParam(rightTableNameF,"whitesharkoccurrences2");
-//		config.setParam(rightTableNameF,"whitesharkoccurrences1");
+		// config.setParam(rightTableNameF,"whitesharkoccurrences1");
-		config.setParam(mergedTableNameF,"whitesharkoccurrencesmerged");
+		config.setParam(mergedTableNameF, "whitesharkoccurrencesmerged");
-		config.setParam(spatialTolerance,"0.5");
+		config.setParam(spatialTolerance, "0.5");
-		config.setParam(confidence,"0.8");
+		config.setParam(confidence, "0.8");
-		
+
+		List<TableTemplates> templatesOccurrence = new ArrayList<TableTemplates>();
+		templatesOccurrence.add(TableTemplates.OCCURRENCE_AQUAMAPS);
 		OccurrencePointsMerger occm = new OccurrencePointsMerger();
 		occm.setConfiguration(config);
 		occm.init();
 		occm.compute();
 	}
-	
+
 	@Override
 	public List<StatisticalType> getInputParameters() {
-		// TODO Auto-generated method stub
+		List<TableTemplates> templatesOccurrence = new ArrayList<TableTemplates>();
-		return null;
+		templatesOccurrence.add(TableTemplates.OCCURRENCE_SPECIES);
+		// occurrence points tables
+		InputTable p1 = new InputTable(templatesOccurrence, leftTableNameF, "The First table containing the occurrence points", "");
+		InputTable p2 = new InputTable(templatesOccurrence, rightTableNameF, "The Second table containing the occurrence points", "");
+
+		// string parameters
+		ColumnType p3 = new ColumnType(leftTableNameF, longitudeColumn, "column with longitude values", "decimallongitude", false);
+		ColumnType p4 = new ColumnType(leftTableNameF, latitudeColumn, "column with latitude values", "decimallatitude", false);
+		ColumnType p5 = new ColumnType(leftTableNameF, recordedByColumn, "column with RecordedBy values", "recordedby", false);
+		ColumnType p6 = new ColumnType(leftTableNameF, scientificNameColumn, "column with Scientific Names", "scientificname", false);
+		ColumnType p7 = new ColumnType(leftTableNameF, eventDateColumn, "column with EventDate values", "eventdate", false);
+		ColumnType p8 = new ColumnType(leftTableNameF, lastModificationColumn, "column with Modified values", "modified", false);
+		ServiceType p9 = new ServiceType(ServiceParameters.RANDOMSTRING, mergedTableNameF, "Name of the final produced", "mergedoccurrences_");
+		PrimitiveType p10 = new PrimitiveType(Float.class.getName(), null, PrimitiveTypes.NUMBER, spatialTolerance, "The tolerance in degree for assessing that two points could be the same", "0.5");
+		PrimitiveType p11 = new PrimitiveType(Float.class.getName(), null, PrimitiveTypes.NUMBER, confidence, "The overall acceptance similarity threshold over which two points are the same", "0.8");
+
+		List<StatisticalType> inputs = new ArrayList<StatisticalType>();
+		inputs.add(p1);
+		inputs.add(p2);
+		inputs.add(p3);
+		inputs.add(p4);
+		inputs.add(p5);
+		inputs.add(p6);
+		inputs.add(p7);
+		inputs.add(p8);
+		inputs.add(p9);
+		inputs.add(p10);
+		inputs.add(p11);
+		
+		DatabaseType.addDefaultDBPars(inputs);
+		return inputs;
 	}
 
-
-	@Override
-	public String getResourceLoad() {
-		// TODO Auto-generated method stub
-		return null;
-	}
-
-
 	@Override
 	public String getResources() {
-		// TODO Auto-generated method stub
+		if ((status > 0) && (status < 100))
-		return null;
+			return ResourceFactory.getResources(100f);
+		else
+			return ResourceFactory.getResources(0f);
 	}
 
+	ResourceFactory resourceManager;
+
+	@Override
+	public String getResourceLoad() {
+		if (resourceManager == null)
+			resourceManager = new ResourceFactory();
+		return resourceManager.getResourceLoad(1);
+	}
 
 	@Override
 	public float getStatus() {
-		// TODO Auto-generated method stub
+		return status;
-		return 0;
 	}
 
-
 	@Override
 	public INFRASTRUCTURE getInfrastructure() {
-		// TODO Auto-generated method stub
+		return INFRASTRUCTURE.LOCAL;
-		return null;
 	}
 
-
 	@Override
 	public StatisticalType getOutput() {
-		// TODO Auto-generated method stub
+		List<TableTemplates> templatesOccurrence = new ArrayList<TableTemplates>();
-		return null;
+		templatesOccurrence.add(TableTemplates.OCCURRENCE_SPECIES);
-	}
+		// occurrence points tables
+		OutputTable p = new OutputTable(templatesOccurrence, mergedTableName, mergedTableName, "The output table containing the merged points");
 
+		return p;
+	}
 
 	@Override
 	public void init() throws Exception {
-		
+
-		AnalysisLogger.setLogger(config.getConfigPath()+AlgorithmConfiguration.defaultLoggerFile);
+		AnalysisLogger.setLogger(config.getConfigPath() + AlgorithmConfiguration.defaultLoggerFile);
-		lonFld=config.getParam(longitudeColumn);
+		lonFld = config.getParam(longitudeColumn);
-		latFld=config.getParam(latitudeColumn);
+		latFld = config.getParam(latitudeColumn);
-		recordedByFld=config.getParam(recordedByColumn);
+		recordedByFld = config.getParam(recordedByColumn);
-		scientificNameFld=config.getParam(scientificNameColumn);
+		scientificNameFld = config.getParam(scientificNameColumn);
-		eventDatFld=config.getParam(eventDateColumn);
+		eventDatFld = config.getParam(eventDateColumn);
-		modifDatFld=config.getParam(lastModificationColumn);
+		modifDatFld = config.getParam(lastModificationColumn);
-		leftTableName=config.getParam(leftTableNameF);
+		leftTableName = config.getParam(leftTableNameF);
-		rightTableName=config.getParam(rightTableNameF);
+		rightTableName = config.getParam(rightTableNameF);
-		mergedTableName=config.getParam(mergedTableNameF);
+		mergedTableName = config.getParam(mergedTableNameF);
-		spatialToleranceValue=Float.parseFloat(config.getParam(spatialTolerance));
+		spatialToleranceValue = Float.parseFloat(config.getParam(spatialTolerance));
-		confidenceValue=Float.parseFloat(config.getParam(confidence));
+		confidenceValue = Float.parseFloat(config.getParam(confidence));
-		
+
 		objectstoinsert = new ArrayList<OccurrencePointsMerger.OccurrenceRecord>();
 		objectstodelete = new ArrayList<OccurrencePointsMerger.OccurrenceRecord>();
+		status = 0;
 	}
 
-
 	@Override
 	public void setConfiguration(AlgorithmConfiguration config) {
-		this.config=config;
+		this.config = config;
 	}
 
-
 	@Override
 	public void shutdown() {
-		// TODO Auto-generated method stub
-		
-	}
 
+	}
 
 	@Override
 	public String getDescription() {
-		// TODO Auto-generated method stub
+		return "An algorithm for merging two sets of occurrence points of species coming from the Species Discovery Facility of D4Science";
-		return null;
 	}
 
-	protected float probabilityStrings(String first, String second){
+	protected float probabilityStrings(String first, String second) {
-		if ((first==null) ||(second==null))
+		if ((first == null) || (second == null))
 			return 1;
-		
+
 		return (float) new DistanceCalculator().CD(false, first, second);
 	}
-	
+
-	protected float probabilityDates(Calendar first, Calendar second){
+	protected float probabilityDates(Calendar first, Calendar second) {
-		if ((first==null) ||(second==null))
+		if ((first == null) || (second == null))
 			return 1;
-		if (first.compareTo(second)==0)
+		if (first.compareTo(second) == 0)
 			return 1;
 		else
 			return 0;
 	}
-	
-	protected float extProb(OccurrenceRecord right,OccurrenceRecord left){
-		float probability = 0;
-			float distance = (float)Math.sqrt(Math.abs(left.x-right.x)+Math.abs(left.y-right.y));
-			if (distance>spatialToleranceValue)
-				probability=0;
-			else{
-				float pSpecies = probabilityStrings(right.scientificName, left.scientificName);
-				float pRecordedBy= probabilityStrings(right.recordedby, left.recordedby);
-				float pDates = probabilityDates(right.eventdate, left.eventdate);
-				probability = pSpecies*pRecordedBy*pDates;
-			}
-				
-			return probability*100;
-	}
-	
-	protected void manageHighProbability(float probability, OccurrenceRecord leftOcc, OccurrenceRecord rightOcc){
-		//if over the threshold then don't add
-	}
-	
-	protected void manageLowProbability(float probability, OccurrenceRecord leftOcc, OccurrenceRecord rightOcc){
-		//if over the threshold then add to the element
-				objectstoinsert.add(rightOcc);
-		}
-	
-	protected void persist(){
-		StringBuffer buffer = new StringBuffer();
-		int toins = objectstoinsert.size();
-		int counter = 0;
-		if (toins>0){
-		for (OccurrenceRecord record:objectstoinsert){
-			buffer.append("(");
-			buffer.append(occurrenceRecord2String(record));
-			buffer.append(")");
-			if (counter<toins-1)
-				buffer.append(",");
 
-			counter++;
+	protected float extProb(OccurrenceRecord right, OccurrenceRecord left) {
+		float probability = 0;
+		float distance = (float) Math.sqrt(Math.abs(left.x - right.x) + Math.abs(left.y - right.y));
+		if (distance > spatialToleranceValue)
+			probability = 0;
+		else {
+			float pSpecies = probabilityStrings(right.scientificName, left.scientificName);
+			float pRecordedBy = probabilityStrings(right.recordedby, left.recordedby);
+			float pDates = probabilityDates(right.eventdate, left.eventdate);
+			probability = pSpecies * pRecordedBy * pDates;
 		}
+
+		return probability * 100;
+	}
+
+	protected void manageHighProbability(float probability, OccurrenceRecord leftOcc, OccurrenceRecord rightOcc) {
+		// insert the most recent:
+		// if it is the left then leave it as is
+		// otherwise put the left in the deletion list and the right in the insertion list
 		
-		String updateQ = DatabaseUtils.insertFromBuffer(mergedTableName,columns.toString(),buffer);
+		if (
-//		System.out.println("Update:\n"+updateQ);
+				((leftOcc.modifdate!=null)&&(rightOcc.modifdate!=null)&&leftOcc.modifdate.before(rightOcc.modifdate)) 
-		DatabaseFactory.executeSQLUpdate(updateQ, dbconnection);
+				|| 
+				(leftOcc.modifdate==null)&&(rightOcc.modifdate!=null)
+				)
+		{
+		
+			objectstodelete.add(leftOcc);
+			objectstoinsert.add(rightOcc);
 		}
 	}
-	
+
+	protected void manageLowProbability(float probability, OccurrenceRecord leftOcc, OccurrenceRecord rightOcc) {
+		// if over the threshold then add to the element
+		objectstoinsert.add(rightOcc);
+	}
+
+	protected void persist() {
+
+		// DELETE ELEMENTS IN THE DELETION LIST
+		int todel = objectstodelete.size();
+		int counter = 0;
+		StringBuffer buffer = new StringBuffer();
+		AnalysisLogger.getLogger().debug("Deleting " + todel + " objects");
+		if (todel > 0) {
+			for (OccurrenceRecord record : objectstodelete) {
+				String rec = recordedByFld + "='" + record.recordedby.replace("'","")+"'";
+				String sci = scientificNameFld + "='" + record.scientificName.replace("'","")+"'";
+				String x = lonFld + "='" + record.x+"'";
+				String y = latFld + "='" + record.y+"'";
+
+				buffer.append("(");
+				buffer.append(rec + " AND " + sci + " AND " + x + " AND " + y);
+				buffer.append(")");
+				if (counter < todel - 1)
+					buffer.append(" OR ");
+
+				counter++;
+			}
+
+			String updateQ = DatabaseUtils.deleteFromBuffer(mergedTableName, buffer);
+//			 System.out.println("Update:\n"+updateQ);
+			DatabaseFactory.executeSQLUpdate(updateQ, dbconnection);
+			AnalysisLogger.getLogger().debug("Objects deleted");
+		}
+
+		buffer = new StringBuffer();
+		int toins = objectstoinsert.size();
+		AnalysisLogger.getLogger().debug("Inserting " + toins + " objects");
+		counter = 0;
+		if (toins > 0) {
+			for (OccurrenceRecord record : objectstoinsert) {
+				buffer.append("(");
+				buffer.append(occurrenceRecord2String(record));
+				buffer.append(")");
+				if (counter < toins - 1)
+					buffer.append(",");
+
+				counter++;
+			}
+
+			String updateQ = DatabaseUtils.insertFromBuffer(mergedTableName, columns.toString(), buffer);
+			// System.out.println("Update:\n"+updateQ);
+			DatabaseFactory.executeSQLUpdate(updateQ, dbconnection);
+			AnalysisLogger.getLogger().debug("Objects inserted");
+		}
+
+	}
+
 	@Override
 	public void compute() throws Exception {
-		
+
-		try{
+		try {
-			//init DB connection
+			// init DB connection
 			AnalysisLogger.getLogger().trace("Initializing DB Connection");
 			dbconnection = DatabaseUtils.initDBSession(config);
 			AnalysisLogger.getLogger().trace("Taking Table Description");
-			//take the description of the table
+			// take the description of the table
-			columnsNames = DatabaseFactory.executeSQLQuery(DatabaseUtils.getColumnsNamesStatement(rightTableName),dbconnection);
+			columnsNames = DatabaseFactory.executeSQLQuery(DatabaseUtils.getColumnsNamesStatement(rightTableName), dbconnection);
-			
+
 			int nCols = columnsNames.size();
 			columns = new StringBuffer();
-			for (int i=0;i<nCols;i++){
+			for (int i = 0; i < nCols; i++) {
-				columns.append("\""+columnsNames.get(i)+"\"");
+				columns.append("\"" + columnsNames.get(i) + "\"");
-				if (i<nCols-1)
+				if (i < nCols - 1)
 					columns.append(",");
 			}
-			
+
-			AnalysisLogger.getLogger().trace("Taken Table Description: "+columns);
+			AnalysisLogger.getLogger().trace("Taken Table Description: " + columns);
-			AnalysisLogger.getLogger().trace("Creating merged table: "+mergedTableName);
+			AnalysisLogger.getLogger().trace("Creating merged table: " + mergedTableName);
-			//create new merged table
+			// create new merged table
 			DatabaseFactory.executeSQLUpdate(DatabaseUtils.dropTableStatement(mergedTableName), dbconnection);
 			DatabaseFactory.executeSQLUpdate(DatabaseUtils.duplicateTableStatement(leftTableName, mergedTableName), dbconnection);
-			//take the elements from sx table
+			// take the elements from sx table
-			AnalysisLogger.getLogger().trace("Taking elements from left table: "+leftTableName);
+			AnalysisLogger.getLogger().trace("Taking elements from left table: " + leftTableName);
-			List<Object> leftRows = DatabaseFactory.executeSQLQuery(DatabaseUtils.getColumnsElementsStatement(leftTableName, columns.toString(),""),dbconnection);
+			List<Object> leftRows = DatabaseFactory.executeSQLQuery(DatabaseUtils.getColumnsElementsStatement(leftTableName, columns.toString(), ""), dbconnection);
-			//take the elements from dx table
+			// take the elements from dx table
-			AnalysisLogger.getLogger().trace("Taking elements from right table: "+rightTableName);
+			AnalysisLogger.getLogger().trace("Taking elements from right table: " + rightTableName);
-			List<Object> rightRows = DatabaseFactory.executeSQLQuery(DatabaseUtils.getColumnsElementsStatement(rightTableName, columns.toString(),""),dbconnection);
+			List<Object> rightRows = DatabaseFactory.executeSQLQuery(DatabaseUtils.getColumnsElementsStatement(rightTableName, columns.toString(), ""), dbconnection);
-			//for each element in dx
+			// for each element in dx
 			List<OccurrenceRecord> leftRecords = new ArrayList<OccurrencePointsMerger.OccurrenceRecord>();
-			AnalysisLogger.getLogger().trace("Processing "+leftTableName+" vs "+rightTableName);
+			AnalysisLogger.getLogger().trace("Processing " + leftTableName + " vs " + rightTableName);
+			status = 10;
 			int rightCounter = 0;
 			int similaritiesCounter = 0;
-			for (Object rRow:rightRows){
+			int allrightrows = rightRows.size();
-				//transform into an occurrence object
+			for (Object rRow : rightRows) {
-				OccurrenceRecord rightOcc = row2OccurrenceRecord((Object[])rRow);
+				// transform into an occurrence object
-				//for each element in sx
+				OccurrenceRecord rightOcc = row2OccurrenceRecord((Object[]) rRow);
-				int k=0;
+				// for each element in sx
+				int k = 0;
 				int leftrecordsSize = 0;
 				boolean found = false;
 				float p = 0;
 				OccurrenceRecord bestleftOcc = null;
-				for (Object lRow:leftRows){
+				for (Object lRow : leftRows) {
 					OccurrenceRecord leftOcc = null;
-					//only for the first iteration on the left occurrences perform the transformation
+					// only for the first iteration on the left occurrences perform the transformation
-					if (leftrecordsSize<=k){
+					if (leftrecordsSize <= k) {
-						//transform into an occurrence object
+						// transform into an occurrence object
-						leftOcc = row2OccurrenceRecord((Object[])lRow);
+						leftOcc = row2OccurrenceRecord((Object[]) lRow);
 						leftRecords.add(leftOcc);
 						leftrecordsSize++;
-//						System.out.println("ADDED "+k+"-th elements size: "+leftRecords.size());
+						// System.out.println("ADDED "+k+"-th elements size: "+leftRecords.size());
-					}
+					} else
-					else
+						leftOcc = leftRecords.get(k);
-						leftOcc =leftRecords.get(k); 
 
-					//evaluate P(dx,sx)
+					// evaluate P(dx,sx)
-					p = extProb(leftOcc,rightOcc);
+					p = extProb(leftOcc, rightOcc);
-					
+
-					if (p>=confidenceValue){
+					if (p >= confidenceValue) {
-						bestleftOcc=leftOcc;
+						bestleftOcc = leftOcc;
-						found=true;
+						found = true;
 						similaritiesCounter++;
-						AnalysisLogger.getLogger().trace("Found a similarity with P="+p+" between ("+"\""+leftOcc.scientificName+"\""+","+leftOcc.x+"\""+","+"\""+leftOcc.y+"\""+","+"\""+leftOcc.recordedby+"\""+","+"\""+ convert2conventionalFormat(leftOcc.eventdate)+"\""+") VS "+
+						AnalysisLogger.getLogger().trace("Found a similarity with P=" + p + " between (" + "\"" + leftOcc.scientificName + "\"" + "," + leftOcc.x + "\"" + "," + "\"" + leftOcc.y + "\"" + "," + "\"" + leftOcc.recordedby + "\"" + "," + "\"" + convert2conventionalFormat(leftOcc.eventdate) + "\"" + ") VS " + "(" + "\"" + rightOcc.scientificName + "\"" + "," + "\"" + rightOcc.x + "\"" + "," + "\"" + rightOcc.y + "\"" + "," + "\"" + rightOcc.recordedby + "\"" + "," + "\"" + convert2conventionalFormat(rightOcc.eventdate) + "\"" + ")");
-						"("+"\""+rightOcc.scientificName+"\""+","+"\""+rightOcc.x+"\""+","+"\""+rightOcc.y+"\""+","+"\""+rightOcc.recordedby+"\""+","+"\""+ convert2conventionalFormat(rightOcc.eventdate)+"\""+")");
 						break;
 					}
 					k++;
@@ -434,19 +493,21 @@ public class OccurrencePointsMerger implements Transducerer{
 					manageHighProbability(p, bestleftOcc, rightOcc);
 				else
 					manageLowProbability(p, bestleftOcc, rightOcc);
+
+				status = Math.min(90, 10f + (80 * ((float) rightCounter) / ((float) allrightrows)));
 			}
-			
+
-			AnalysisLogger.getLogger().trace("Found "+similaritiesCounter+" similarities on "+rightCounter+" elements");
+			AnalysisLogger.getLogger().trace("Found " + similaritiesCounter + " similarities on " + rightCounter + " elements");
-			
+			status = 90;
-			//transform the complete list into a table
+			// transform the complete list into a table
 			persist();
-			//close DB connection
+			// close DB connection
-		}catch(Exception e){
+		} catch (Exception e) {
 			throw e;
-		}
+		} finally {
-		finally{
+			if (dbconnection != null)
-			if (dbconnection!=null)
 				dbconnection.close();
+			status = 100;
 			AnalysisLogger.getLogger().trace("Occ Points Processing Finished and db closed");
 		}
 	}

src/main/java/org/gcube/dataanalysis/ecoengine/utils/DatabaseUtils.java

@@ -158,6 +158,10 @@ public class DatabaseUtils {
 		return "insert into "+table+" ("+columnsNames+") values "+values;
 	}
 	
+	public static String deleteFromBuffer(String table, StringBuffer couples) {
+
+		return "delete from "+table+" where "+couples;
+	}
 	
 	public static String copyFileToTableStatement (String file, String table){
 		return "COPY "+table+" FROM '"+file+"' DELIMITERS ';' WITH NULL AS 'null string'";