/* * RapidMiner * * Copyright (C) 2001-2008 by Rapid-I and the contributors * * Complete list of developers available at our web site: * * http://rapid-i.com * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU Affero General Public License as published by * the Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU Affero General Public License for more details. * * You should have received a copy of the GNU Affero General Public License * along with this program. If not, see http://www.gnu.org/licenses/. */ package com.rapidminer.operator.meta; import java.util.List; import com.rapidminer.example.ExampleSet; import com.rapidminer.example.Tools; import com.rapidminer.operator.IOContainer; import com.rapidminer.operator.IOObject; import com.rapidminer.operator.Operator; import com.rapidminer.operator.OperatorChain; import com.rapidminer.operator.OperatorCreationException; import com.rapidminer.operator.OperatorDescription; import com.rapidminer.operator.OperatorException; import com.rapidminer.operator.condition.FirstInnerOperatorCondition; import com.rapidminer.operator.condition.InnerOperatorCondition; import com.rapidminer.operator.preprocessing.MaterializeDataInMemory; import com.rapidminer.parameter.ParameterType; import com.rapidminer.parameter.ParameterTypeInt; import com.rapidminer.tools.OperatorService; /** * This operator groups the input examples into batches of the specified size and performs * the inner operators on all batches subsequently. This might be useful for very large data * sets which cannot be load into memory but must be handled in a database. In these cases, * preprocessing methods or model applications and other tasks can be performed on each batch * and the result might be again written into a database table (by using the DatabaseExampleSetWriter * in its append mode). * * @author Ingo Mierswa * @version $Id: BatchProcessing.java,v 1.3 2008/07/15 15:07:24 ingomierswa Exp $ */ public class BatchProcessing extends OperatorChain { public static final String PARAMETER_BATCH_SIZE = "batch_size"; public BatchProcessing(OperatorDescription description) { super(description); } public IOObject[] apply() throws OperatorException { ExampleSet exampleSet = getInput(ExampleSet.class); Operator materialization = null; try { materialization = OperatorService.createOperator(MaterializeDataInMemory.class); } catch (OperatorCreationException e) { throw new OperatorException("Cannot create materialization: " + e); } if (materialization != null) { int batchSize = getParameterAsInt(PARAMETER_BATCH_SIZE); int size = exampleSet.size(); int currentStart = 0; while (currentStart < size) { ExampleSet materializedSet = Tools.getLinearSubsetCopy(exampleSet, batchSize, currentStart); IOContainer innerInput = new IOContainer(materializedSet); for (int o = 0; o < getNumberOfOperators(); o++) { innerInput = getOperator(o).apply(innerInput); } currentStart += batchSize; } } return new IOObject[] { exampleSet }; } public InnerOperatorCondition getInnerOperatorCondition() { return new FirstInnerOperatorCondition(new Class[] { ExampleSet.class }); } public int getMaxNumberOfInnerOperators() { return Integer.MAX_VALUE; } public int getMinNumberOfInnerOperators() { return 1; } public Class<?>[] getInputClasses() { return new Class[] { ExampleSet.class }; } public Class<?>[] getOutputClasses() { return new Class[] { ExampleSet.class }; } public List<ParameterType> getParameterTypes() { List<ParameterType> types = super.getParameterTypes(); types.add(new ParameterTypeInt(PARAMETER_BATCH_SIZE, "This number of examples is processed batch-wise by the inner operators of this operator.", 1, Integer.MAX_VALUE, 1000)); return types; } }