solr/core/src/test/org/apache/solr/update/processor/ClassificationUpdateProcessorTest.java - lucene-solr - Git at Google

 /*
  * Licensed to the Apache Software Foundation (ASF) under one or more
  * contributor license agreements.  See the NOTICE file distributed with
  * this work for additional information regarding copyright ownership.
  * The ASF licenses this file to You under the Apache License, Version 2.0
  * (the "License"); you may not use this file except in compliance with
  * the License.  You may obtain a copy of the License at
  *
  *     http://www.apache.org/licenses/LICENSE-2.0
  *
  * Unless required by applicable law or agreed to in writing, software
  * distributed under the License is distributed on an "AS IS" BASIS,
  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
 package org.apache.solr.update.processor;

 import java.io.IOException;
 import java.util.ArrayList;

 import org.apache.lucene.analysis.Analyzer;
 import org.apache.lucene.analysis.MockAnalyzer;
 import org.apache.lucene.analysis.MockTokenizer;
 import org.apache.lucene.document.Document;
 import org.apache.lucene.document.Field;
 import org.apache.lucene.index.IndexReader;
 import org.apache.lucene.index.RandomIndexWriter;
 import org.apache.lucene.index.Term;
 import org.apache.lucene.search.IndexSearcher;
 import org.apache.lucene.search.Query;
 import org.apache.lucene.search.TermQuery;
 import org.apache.lucene.store.Directory;
 import org.apache.solr.SolrTestCaseJ4;
 import org.apache.solr.common.SolrInputDocument;
 import org.apache.solr.update.AddUpdateCommand;
 import org.junit.BeforeClass;
 import org.junit.Test;

 import static org.hamcrest.core.Is.is;
 import static org.mockito.Mockito.mock;

 /**
  * Tests for {@link ClassificationUpdateProcessor}
  */
 public class ClassificationUpdateProcessorTest extends SolrTestCaseJ4 {
   /* field names are used in accordance with the solrconfig and schema supplied */
   private static final String ID = "id";
   private static final String TITLE = "title";
   private static final String CONTENT = "content";
   private static final String AUTHOR = "author";
   private static final String TRAINING_CLASS = "cat";
   private static final String PREDICTED_CLASS = "predicted";
   public static final String KNN = "knn";

   protected Directory directory;
   protected IndexReader reader;
   protected IndexSearcher searcher;
   protected Analyzer analyzer = new MockAnalyzer(random(), MockTokenizer.WHITESPACE, false);
   private ClassificationUpdateProcessor updateProcessorToTest;

   @BeforeClass
   public static void beforeClass() throws Exception {
     assumeWorkingMockito();
     System.setProperty("enable.update.log", "false");
     initCore("solrconfig-classification.xml", "schema-classification.xml");
   }

   @Override
   public void setUp() throws Exception {
     super.setUp();
   }

   @Override
   public void tearDown() throws Exception {
     if (null != reader) {
       reader.close();
       reader = null;
     }
     if (null != directory) {
       directory.close();
       directory = null;
     }
     if (null != analyzer) {
       analyzer.close();
       analyzer = null;
     }
     super.tearDown();
   }


   @Test
   public void classificationMonoClass_predictedClassFieldSet_shouldAssignClassInPredictedClassField() throws Exception {
     UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
     prepareTrainedIndexMonoClass();

     AddUpdateCommand update=new AddUpdateCommand(req());
     SolrInputDocument unseenDocument1 = sdoc(ID, "10",
         TITLE, "word4 word4 word4",
         CONTENT, "word2 word2 ",
         AUTHOR, "unseenAuthor");
     update.solrDoc=unseenDocument1;

     ClassificationUpdateProcessorParams params = initParams(ClassificationUpdateProcessorFactory.Algorithm.KNN);
     params.setPredictedClassField(PREDICTED_CLASS);

     updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());
     updateProcessorToTest.processAdd(update);

     assertThat(unseenDocument1.getFieldValue(PREDICTED_CLASS),is("class2"));
   }

   @Test
   public void knnMonoClass_sampleParams_shouldAssignCorrectClass() throws Exception {
     UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
     prepareTrainedIndexMonoClass();

     AddUpdateCommand update=new AddUpdateCommand(req());
     SolrInputDocument unseenDocument1 = sdoc(ID, "10",
         TITLE, "word4 word4 word4",
         CONTENT, "word2 word2 ",
         AUTHOR, "unseenAuthor");
     update.solrDoc=unseenDocument1;

     ClassificationUpdateProcessorParams params = initParams(ClassificationUpdateProcessorFactory.Algorithm.KNN);

     updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());
     updateProcessorToTest.processAdd(update);

     assertThat(unseenDocument1.getFieldValue(TRAINING_CLASS),is("class2"));
   }

   @Test
   public void knnMonoClass_boostFields_shouldAssignCorrectClass() throws Exception {
     UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
     prepareTrainedIndexMonoClass();

     AddUpdateCommand update=new AddUpdateCommand(req());
     SolrInputDocument unseenDocument1 = sdoc(ID, "10",
         TITLE, "word4 word4 word4",
         CONTENT, "word2 word2 ",
         AUTHOR, "unseenAuthor");
     update.solrDoc=unseenDocument1;

     ClassificationUpdateProcessorParams params = initParams(ClassificationUpdateProcessorFactory.Algorithm.KNN);
     params.setInputFieldNames(new String[]{TITLE + "^1.5", CONTENT + "^0.5", AUTHOR + "^2.5"});

     updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());

     updateProcessorToTest.processAdd(update);

     assertThat(unseenDocument1.getFieldValue(TRAINING_CLASS),is("class2"));
   }

   @Test
   public void bayesMonoClass_sampleParams_shouldAssignCorrectClass() throws Exception {
     UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
     prepareTrainedIndexMonoClass();

     AddUpdateCommand update=new AddUpdateCommand(req());
     SolrInputDocument unseenDocument1 = sdoc(ID, "10",
         TITLE, "word4 word4 word4",
         CONTENT, "word2 word2 ",
         AUTHOR, "unseenAuthor");
     update.solrDoc=unseenDocument1;

     ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.BAYES);

     updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());
     updateProcessorToTest.processAdd(update);

     assertThat(unseenDocument1.getFieldValue(TRAINING_CLASS),is("class1"));
   }

   @Test
   public void knnMonoClass_contextQueryFiltered_shouldAssignCorrectClass() throws Exception {
     UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
     prepareTrainedIndexMonoClass();

     AddUpdateCommand update=new AddUpdateCommand(req());
     SolrInputDocument unseenDocument1 = sdoc(ID, "10",
         TITLE, "word4 word4 word4",
         CONTENT, "word2 word2 ",
         AUTHOR, "a");
     update.solrDoc=unseenDocument1;

     ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.KNN);
     Query class3DocsChunk=new TermQuery(new Term(TITLE,"word6"));
     params.setTrainingFilterQuery(class3DocsChunk);

     updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());
     updateProcessorToTest.processAdd(update);

     assertThat(unseenDocument1.getFieldValue(TRAINING_CLASS),is("class3"));
   }

   @Test
   public void bayesMonoClass_boostFields_shouldAssignCorrectClass() throws Exception {
     UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
     prepareTrainedIndexMonoClass();

     AddUpdateCommand update=new AddUpdateCommand(req());
     SolrInputDocument unseenDocument1 = sdoc(ID, "10",
         TITLE, "word4 word4 word4",
         CONTENT, "word2 word2 ",
         AUTHOR, "unseenAuthor");
     update.solrDoc=unseenDocument1;

     ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.BAYES);
     params.setInputFieldNames(new String[]{TITLE+"^1.5",CONTENT+"^0.5",AUTHOR+"^2.5"});

     updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());

     updateProcessorToTest.processAdd(update);

     assertThat(unseenDocument1.getFieldValue(TRAINING_CLASS),is("class2"));
   }

   @Test
   public void knnClassification_maxOutputClassesGreaterThanAvailable_shouldAssignCorrectClass() throws Exception {
     UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
     prepareTrainedIndexMultiClass();

     AddUpdateCommand update=new AddUpdateCommand(req());
     SolrInputDocument unseenDocument1 = sdoc(ID, "10",
         TITLE, "word1 word1 word1",
         CONTENT, "word2 word2 ",
         AUTHOR, "unseenAuthor");
     update.solrDoc=unseenDocument1;

     ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.KNN);
     params.setMaxPredictedClasses(100);

     updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());
     updateProcessorToTest.processAdd(update);

     @SuppressWarnings({"unchecked"})
     ArrayList<Object> assignedClasses = (ArrayList)unseenDocument1.getFieldValues(TRAINING_CLASS);
     assertThat(assignedClasses.get(0),is("class2"));
     assertThat(assignedClasses.get(1),is("class1"));
   }

   @Test
   public void knnMultiClass_maxOutputClasses2_shouldAssignMax2Classes() throws Exception {
     UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
     prepareTrainedIndexMultiClass();

     AddUpdateCommand update=new AddUpdateCommand(req());
     SolrInputDocument unseenDocument1 = sdoc(ID, "10",
         TITLE, "word1 word1 word1",
         CONTENT, "word2 word2 ",
         AUTHOR, "unseenAuthor");
     update.solrDoc=unseenDocument1;

     ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.KNN);
     params.setMaxPredictedClasses(2);

     updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());
     updateProcessorToTest.processAdd(update);

     @SuppressWarnings({"unchecked"})
     ArrayList<Object> assignedClasses = (ArrayList)unseenDocument1.getFieldValues(TRAINING_CLASS);
     assertThat(assignedClasses.size(),is(2));
     assertThat(assignedClasses.get(0),is("class2"));
     assertThat(assignedClasses.get(1),is("class1"));
   }

   @Test
   public void bayesMultiClass_maxOutputClasses2_shouldAssignMax2Classes() throws Exception {
     UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
     prepareTrainedIndexMultiClass();

     AddUpdateCommand update=new AddUpdateCommand(req());
     SolrInputDocument unseenDocument1 = sdoc(ID, "10",
         TITLE, "word1 word1 word1",
         CONTENT, "word2 word2 ",
         AUTHOR, "unseenAuthor");
     update.solrDoc=unseenDocument1;

     ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.BAYES);
     params.setMaxPredictedClasses(2);

     updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());
     updateProcessorToTest.processAdd(update);

     @SuppressWarnings({"unchecked"})
     ArrayList<Object> assignedClasses = (ArrayList)unseenDocument1.getFieldValues(TRAINING_CLASS);
     assertThat(assignedClasses.size(),is(2));
     assertThat(assignedClasses.get(0),is("class2"));
     assertThat(assignedClasses.get(1),is("class1"));
   }

   @Test
   public void knnMultiClass_boostFieldsMaxOutputClasses2_shouldAssignMax2Classes() throws Exception {
     UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
     prepareTrainedIndexMultiClass();

     AddUpdateCommand update=new AddUpdateCommand(req());
     SolrInputDocument unseenDocument1 = sdoc(ID, "10",
         TITLE, "word4 word4 word4",
         CONTENT, "word2 word2 ",
         AUTHOR, "unseenAuthor");
     update.solrDoc=unseenDocument1;

     ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.KNN);
     params.setInputFieldNames(new String[]{TITLE+"^1.5",CONTENT+"^0.5",AUTHOR+"^2.5"});
     params.setMaxPredictedClasses(2);

     updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());

     updateProcessorToTest.processAdd(update);

     @SuppressWarnings({"unchecked"})
     ArrayList<Object> assignedClasses = (ArrayList)unseenDocument1.getFieldValues(TRAINING_CLASS);
     assertThat(assignedClasses.size(),is(2));
     assertThat(assignedClasses.get(0),is("class4"));
     assertThat(assignedClasses.get(1),is("class6"));
   }

   @Test
   public void bayesMultiClass_boostFieldsMaxOutputClasses2_shouldAssignMax2Classes() throws Exception {
     UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
     prepareTrainedIndexMultiClass();

     AddUpdateCommand update=new AddUpdateCommand(req());
     SolrInputDocument unseenDocument1 = sdoc(ID, "10",
         TITLE, "word4 word4 word4",
         CONTENT, "word2 word2 ",
         AUTHOR, "unseenAuthor");
     update.solrDoc=unseenDocument1;

     ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.BAYES);
     params.setInputFieldNames(new String[]{TITLE+"^1.5",CONTENT+"^0.5",AUTHOR+"^2.5"});
     params.setMaxPredictedClasses(2);

     updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());

     updateProcessorToTest.processAdd(update);

     @SuppressWarnings({"unchecked"})
     ArrayList<Object> assignedClasses = (ArrayList)unseenDocument1.getFieldValues(TRAINING_CLASS);
     assertThat(assignedClasses.size(),is(2));
     assertThat(assignedClasses.get(0),is("class4"));
     assertThat(assignedClasses.get(1),is("class6"));
   }

   private ClassificationUpdateProcessorParams initParams(ClassificationUpdateProcessorFactory.Algorithm classificationAlgorithm) {
     ClassificationUpdateProcessorParams params= new ClassificationUpdateProcessorParams();
     params.setInputFieldNames(new String[]{TITLE,CONTENT,AUTHOR});
     params.setTrainingClassField(TRAINING_CLASS);
     params.setPredictedClassField(TRAINING_CLASS);
     params.setMinTf(1);
     params.setMinDf(1);
     params.setK(5);
     params.setAlgorithm(classificationAlgorithm);
     params.setMaxPredictedClasses(1);
     return params;
   }

   /**
    * Index some example documents with a class manually assigned.
    * This will be our trained model.
    *
    * @throws Exception If there is a low-level I/O error
    */
   private void prepareTrainedIndexMonoClass() throws Exception {
     directory = newDirectory();
     RandomIndexWriter writer = new RandomIndexWriter(random(), directory);

     //class1
     addDoc(writer, buildLuceneDocument(ID, "1",
         TITLE, "word1 word1 word1",
         CONTENT, "word2 word2 word2",
         AUTHOR, "a",
         TRAINING_CLASS, "class1"));
     addDoc(writer, buildLuceneDocument(ID, "2",
         TITLE, "word1 word1",
         CONTENT, "word2 word2",
         AUTHOR, "a",
         TRAINING_CLASS, "class1"));
     addDoc(writer, buildLuceneDocument(ID, "3",
         TITLE, "word1 word1 word1",
         CONTENT, "word2",
         AUTHOR, "a",
         TRAINING_CLASS, "class1"));
     addDoc(writer, buildLuceneDocument(ID, "4",
         TITLE, "word1 word1 word1",
         CONTENT, "word2 word2 word2",
         AUTHOR, "a",
         TRAINING_CLASS, "class1"));
     //class2
     addDoc(writer, buildLuceneDocument(ID, "5",
         TITLE, "word4 word4 word4",
         CONTENT, "word5 word5",
         AUTHOR, "c",
         TRAINING_CLASS, "class2"));
     addDoc(writer, buildLuceneDocument(ID, "6",
         TITLE, "word4 word4",
         CONTENT, "word5",
         AUTHOR, "c",
         TRAINING_CLASS, "class2"));
     addDoc(writer, buildLuceneDocument(ID, "7",
         TITLE, "word4 word4 word4",
         CONTENT, "word5 word5 word5",
         AUTHOR, "c",
         TRAINING_CLASS, "class2"));
     addDoc(writer, buildLuceneDocument(ID, "8",
         TITLE, "word4",
         CONTENT, "word5 word5 word5 word5",
         AUTHOR, "c",
         TRAINING_CLASS, "class2"));
     //class3
     addDoc(writer, buildLuceneDocument(ID, "9",
         TITLE, "word6",
         CONTENT, "word7",
         AUTHOR, "a",
         TRAINING_CLASS, "class3"));
     addDoc(writer, buildLuceneDocument(ID, "10",
         TITLE, "word6",
         CONTENT, "word7",
         AUTHOR, "a",
         TRAINING_CLASS, "class3"));
     addDoc(writer, buildLuceneDocument(ID, "11",
         TITLE, "word6",
         CONTENT, "word7",
         AUTHOR, "a",
         TRAINING_CLASS, "class3"));
     addDoc(writer, buildLuceneDocument(ID, "12",
         TITLE, "word6",
         CONTENT, "word7",
         AUTHOR, "a",
         TRAINING_CLASS, "class3"));

     reader = writer.getReader();
     writer.close();
     searcher = newSearcher(reader);
   }

   private void prepareTrainedIndexMultiClass() throws Exception {
     directory = newDirectory();
     RandomIndexWriter writer = new RandomIndexWriter(random(), directory);

     //class1
     addDoc(writer, buildLuceneDocument(ID, "1",
         TITLE, "word1 word1 word1",
         CONTENT, "word2 word2 word2",
         AUTHOR, "Name Surname",
         TRAINING_CLASS, "class1",
         TRAINING_CLASS, "class2"
         ));
     addDoc(writer, buildLuceneDocument(ID, "2",
         TITLE, "word1 word1",
         CONTENT, "word2 word2",
         AUTHOR, "Name Surname",
         TRAINING_CLASS, "class3",
         TRAINING_CLASS, "class2"
     ));
     addDoc(writer, buildLuceneDocument(ID, "3",
         TITLE, "word1 word1 word1",
         CONTENT, "word2",
         AUTHOR, "Name Surname",
         TRAINING_CLASS, "class1",
         TRAINING_CLASS, "class2"
     ));
     addDoc(writer, buildLuceneDocument(ID, "4",
         TITLE, "word1 word1 word1",
         CONTENT, "word2 word2 word2",
         AUTHOR, "Name Surname",
         TRAINING_CLASS, "class1",
         TRAINING_CLASS, "class2"
     ));
     //class2
     addDoc(writer, buildLuceneDocument(ID, "5",
         TITLE, "word4 word4 word4",
         CONTENT, "word5 word5",
         AUTHOR, "Name1 Surname1",
         TRAINING_CLASS, "class6",
         TRAINING_CLASS, "class4"
     ));
     addDoc(writer, buildLuceneDocument(ID, "6",
         TITLE, "word4 word4",
         CONTENT, "word5",
         AUTHOR, "Name1 Surname1",
         TRAINING_CLASS, "class5",
         TRAINING_CLASS, "class4"
     ));
     addDoc(writer, buildLuceneDocument(ID, "7",
         TITLE, "word4 word4 word4",
         CONTENT, "word5 word5 word5",
         AUTHOR, "Name1 Surname1",
         TRAINING_CLASS, "class6",
         TRAINING_CLASS, "class4"
     ));
     addDoc(writer, buildLuceneDocument(ID, "8",
         TITLE, "word4",
         CONTENT, "word5 word5 word5 word5",
         AUTHOR, "Name1 Surname1",
         TRAINING_CLASS, "class6",
         TRAINING_CLASS, "class4"
     ));

     reader = writer.getReader();
     writer.close();
     searcher = newSearcher(reader);
   }

   public static Document buildLuceneDocument(Object... fieldsAndValues) {
     Document luceneDoc = new Document();
     for (int i=0; i<fieldsAndValues.length; i+=2) {
       luceneDoc.add(newTextField((String)fieldsAndValues[i], (String)fieldsAndValues[i+1], Field.Store.YES));
     }
     return luceneDoc;
   }

   private int addDoc(RandomIndexWriter writer, Document doc) throws IOException {
     writer.addDocument(doc);
     return writer.getDocStats().numDocs - 1;
   }
 }
	/*
	* Licensed to the Apache Software Foundation (ASF) under one or more
	* contributor license agreements. See the NOTICE file distributed with
	* this work for additional information regarding copyright ownership.
	* The ASF licenses this file to You under the Apache License, Version 2.0
	* (the "License"); you may not use this file except in compliance with
	* the License. You may obtain a copy of the License at
	*
	* http://www.apache.org/licenses/LICENSE-2.0
	*
	* Unless required by applicable law or agreed to in writing, software
	* distributed under the License is distributed on an "AS IS" BASIS,
	* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	* See the License for the specific language governing permissions and
	* limitations under the License.
	*/
	package org.apache.solr.update.processor;

	import java.io.IOException;
	import java.util.ArrayList;

	import org.apache.lucene.analysis.Analyzer;
	import org.apache.lucene.analysis.MockAnalyzer;
	import org.apache.lucene.analysis.MockTokenizer;
	import org.apache.lucene.document.Document;
	import org.apache.lucene.document.Field;
	import org.apache.lucene.index.IndexReader;
	import org.apache.lucene.index.RandomIndexWriter;
	import org.apache.lucene.index.Term;
	import org.apache.lucene.search.IndexSearcher;
	import org.apache.lucene.search.Query;
	import org.apache.lucene.search.TermQuery;
	import org.apache.lucene.store.Directory;
	import org.apache.solr.SolrTestCaseJ4;
	import org.apache.solr.common.SolrInputDocument;
	import org.apache.solr.update.AddUpdateCommand;
	import org.junit.BeforeClass;
	import org.junit.Test;

	import static org.hamcrest.core.Is.is;
	import static org.mockito.Mockito.mock;

	/**
	* Tests for {@link ClassificationUpdateProcessor}
	*/
	public class ClassificationUpdateProcessorTest extends SolrTestCaseJ4 {
	/* field names are used in accordance with the solrconfig and schema supplied */
	private static final String ID = "id";
	private static final String TITLE = "title";
	private static final String CONTENT = "content";
	private static final String AUTHOR = "author";
	private static final String TRAINING_CLASS = "cat";
	private static final String PREDICTED_CLASS = "predicted";
	public static final String KNN = "knn";

	protected Directory directory;
	protected IndexReader reader;
	protected IndexSearcher searcher;
	protected Analyzer analyzer = new MockAnalyzer(random(), MockTokenizer.WHITESPACE, false);
	private ClassificationUpdateProcessor updateProcessorToTest;

	@BeforeClass
	public static void beforeClass() throws Exception {
	assumeWorkingMockito();
	System.setProperty("enable.update.log", "false");
	initCore("solrconfig-classification.xml", "schema-classification.xml");
	}

	@Override
	public void setUp() throws Exception {
	super.setUp();
	}

	@Override
	public void tearDown() throws Exception {
	if (null != reader) {
	reader.close();
	reader = null;
	}
	if (null != directory) {
	directory.close();
	directory = null;
	}
	if (null != analyzer) {
	analyzer.close();
	analyzer = null;
	}
	super.tearDown();
	}




	@Test
	public void classificationMonoClass_predictedClassFieldSet_shouldAssignClassInPredictedClassField() throws Exception {
	UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
	prepareTrainedIndexMonoClass();

	AddUpdateCommand update=new AddUpdateCommand(req());
	SolrInputDocument unseenDocument1 = sdoc(ID, "10",
	TITLE, "word4 word4 word4",
	CONTENT, "word2 word2 ",
	AUTHOR, "unseenAuthor");
	update.solrDoc=unseenDocument1;

	ClassificationUpdateProcessorParams params = initParams(ClassificationUpdateProcessorFactory.Algorithm.KNN);
	params.setPredictedClassField(PREDICTED_CLASS);

	updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());
	updateProcessorToTest.processAdd(update);

	assertThat(unseenDocument1.getFieldValue(PREDICTED_CLASS),is("class2"));
	}

	@Test
	public void knnMonoClass_sampleParams_shouldAssignCorrectClass() throws Exception {
	UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
	prepareTrainedIndexMonoClass();

	AddUpdateCommand update=new AddUpdateCommand(req());
	SolrInputDocument unseenDocument1 = sdoc(ID, "10",
	TITLE, "word4 word4 word4",
	CONTENT, "word2 word2 ",
	AUTHOR, "unseenAuthor");
	update.solrDoc=unseenDocument1;

	ClassificationUpdateProcessorParams params = initParams(ClassificationUpdateProcessorFactory.Algorithm.KNN);

	updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());
	updateProcessorToTest.processAdd(update);

	assertThat(unseenDocument1.getFieldValue(TRAINING_CLASS),is("class2"));
	}

	@Test
	public void knnMonoClass_boostFields_shouldAssignCorrectClass() throws Exception {
	UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
	prepareTrainedIndexMonoClass();

	AddUpdateCommand update=new AddUpdateCommand(req());
	SolrInputDocument unseenDocument1 = sdoc(ID, "10",
	TITLE, "word4 word4 word4",
	CONTENT, "word2 word2 ",
	AUTHOR, "unseenAuthor");
	update.solrDoc=unseenDocument1;

	ClassificationUpdateProcessorParams params = initParams(ClassificationUpdateProcessorFactory.Algorithm.KNN);
	params.setInputFieldNames(new String[]{TITLE + "^1.5", CONTENT + "^0.5", AUTHOR + "^2.5"});

	updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());

	updateProcessorToTest.processAdd(update);

	assertThat(unseenDocument1.getFieldValue(TRAINING_CLASS),is("class2"));
	}

	@Test
	public void bayesMonoClass_sampleParams_shouldAssignCorrectClass() throws Exception {
	UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
	prepareTrainedIndexMonoClass();

	AddUpdateCommand update=new AddUpdateCommand(req());
	SolrInputDocument unseenDocument1 = sdoc(ID, "10",
	TITLE, "word4 word4 word4",
	CONTENT, "word2 word2 ",
	AUTHOR, "unseenAuthor");
	update.solrDoc=unseenDocument1;

	ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.BAYES);

	updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());
	updateProcessorToTest.processAdd(update);

	assertThat(unseenDocument1.getFieldValue(TRAINING_CLASS),is("class1"));
	}

	@Test
	public void knnMonoClass_contextQueryFiltered_shouldAssignCorrectClass() throws Exception {
	UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
	prepareTrainedIndexMonoClass();

	AddUpdateCommand update=new AddUpdateCommand(req());
	SolrInputDocument unseenDocument1 = sdoc(ID, "10",
	TITLE, "word4 word4 word4",
	CONTENT, "word2 word2 ",
	AUTHOR, "a");
	update.solrDoc=unseenDocument1;

	ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.KNN);
	Query class3DocsChunk=new TermQuery(new Term(TITLE,"word6"));
	params.setTrainingFilterQuery(class3DocsChunk);

	updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());
	updateProcessorToTest.processAdd(update);

	assertThat(unseenDocument1.getFieldValue(TRAINING_CLASS),is("class3"));
	}

	@Test
	public void bayesMonoClass_boostFields_shouldAssignCorrectClass() throws Exception {
	UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
	prepareTrainedIndexMonoClass();

	AddUpdateCommand update=new AddUpdateCommand(req());
	SolrInputDocument unseenDocument1 = sdoc(ID, "10",
	TITLE, "word4 word4 word4",
	CONTENT, "word2 word2 ",
	AUTHOR, "unseenAuthor");
	update.solrDoc=unseenDocument1;

	ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.BAYES);
	params.setInputFieldNames(new String[]{TITLE+"^1.5",CONTENT+"^0.5",AUTHOR+"^2.5"});

	updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());

	updateProcessorToTest.processAdd(update);

	assertThat(unseenDocument1.getFieldValue(TRAINING_CLASS),is("class2"));
	}

	@Test
	public void knnClassification_maxOutputClassesGreaterThanAvailable_shouldAssignCorrectClass() throws Exception {
	UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
	prepareTrainedIndexMultiClass();

	AddUpdateCommand update=new AddUpdateCommand(req());
	SolrInputDocument unseenDocument1 = sdoc(ID, "10",
	TITLE, "word1 word1 word1",
	CONTENT, "word2 word2 ",
	AUTHOR, "unseenAuthor");
	update.solrDoc=unseenDocument1;

	ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.KNN);
	params.setMaxPredictedClasses(100);

	updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());
	updateProcessorToTest.processAdd(update);

	@SuppressWarnings({"unchecked"})
	ArrayList<Object> assignedClasses = (ArrayList)unseenDocument1.getFieldValues(TRAINING_CLASS);
	assertThat(assignedClasses.get(0),is("class2"));
	assertThat(assignedClasses.get(1),is("class1"));
	}

	@Test
	public void knnMultiClass_maxOutputClasses2_shouldAssignMax2Classes() throws Exception {
	UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
	prepareTrainedIndexMultiClass();

	AddUpdateCommand update=new AddUpdateCommand(req());
	SolrInputDocument unseenDocument1 = sdoc(ID, "10",
	TITLE, "word1 word1 word1",
	CONTENT, "word2 word2 ",
	AUTHOR, "unseenAuthor");
	update.solrDoc=unseenDocument1;

	ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.KNN);
	params.setMaxPredictedClasses(2);

	updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());
	updateProcessorToTest.processAdd(update);

	@SuppressWarnings({"unchecked"})
	ArrayList<Object> assignedClasses = (ArrayList)unseenDocument1.getFieldValues(TRAINING_CLASS);
	assertThat(assignedClasses.size(),is(2));
	assertThat(assignedClasses.get(0),is("class2"));
	assertThat(assignedClasses.get(1),is("class1"));
	}

	@Test
	public void bayesMultiClass_maxOutputClasses2_shouldAssignMax2Classes() throws Exception {
	UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
	prepareTrainedIndexMultiClass();

	AddUpdateCommand update=new AddUpdateCommand(req());
	SolrInputDocument unseenDocument1 = sdoc(ID, "10",
	TITLE, "word1 word1 word1",
	CONTENT, "word2 word2 ",
	AUTHOR, "unseenAuthor");
	update.solrDoc=unseenDocument1;

	ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.BAYES);
	params.setMaxPredictedClasses(2);

	updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());
	updateProcessorToTest.processAdd(update);

	@SuppressWarnings({"unchecked"})
	ArrayList<Object> assignedClasses = (ArrayList)unseenDocument1.getFieldValues(TRAINING_CLASS);
	assertThat(assignedClasses.size(),is(2));
	assertThat(assignedClasses.get(0),is("class2"));
	assertThat(assignedClasses.get(1),is("class1"));
	}

	@Test
	public void knnMultiClass_boostFieldsMaxOutputClasses2_shouldAssignMax2Classes() throws Exception {
	UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
	prepareTrainedIndexMultiClass();

	AddUpdateCommand update=new AddUpdateCommand(req());
	SolrInputDocument unseenDocument1 = sdoc(ID, "10",
	TITLE, "word4 word4 word4",
	CONTENT, "word2 word2 ",
	AUTHOR, "unseenAuthor");
	update.solrDoc=unseenDocument1;

	ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.KNN);
	params.setInputFieldNames(new String[]{TITLE+"^1.5",CONTENT+"^0.5",AUTHOR+"^2.5"});
	params.setMaxPredictedClasses(2);

	updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());

	updateProcessorToTest.processAdd(update);

	@SuppressWarnings({"unchecked"})
	ArrayList<Object> assignedClasses = (ArrayList)unseenDocument1.getFieldValues(TRAINING_CLASS);
	assertThat(assignedClasses.size(),is(2));
	assertThat(assignedClasses.get(0),is("class4"));
	assertThat(assignedClasses.get(1),is("class6"));
	}

	@Test
	public void bayesMultiClass_boostFieldsMaxOutputClasses2_shouldAssignMax2Classes() throws Exception {
	UpdateRequestProcessor mockProcessor=mock(UpdateRequestProcessor.class);
	prepareTrainedIndexMultiClass();

	AddUpdateCommand update=new AddUpdateCommand(req());
	SolrInputDocument unseenDocument1 = sdoc(ID, "10",
	TITLE, "word4 word4 word4",
	CONTENT, "word2 word2 ",
	AUTHOR, "unseenAuthor");
	update.solrDoc=unseenDocument1;

	ClassificationUpdateProcessorParams params= initParams(ClassificationUpdateProcessorFactory.Algorithm.BAYES);
	params.setInputFieldNames(new String[]{TITLE+"^1.5",CONTENT+"^0.5",AUTHOR+"^2.5"});
	params.setMaxPredictedClasses(2);

	updateProcessorToTest=new ClassificationUpdateProcessor(params,mockProcessor,reader,req().getSchema());

	updateProcessorToTest.processAdd(update);

	@SuppressWarnings({"unchecked"})
	ArrayList<Object> assignedClasses = (ArrayList)unseenDocument1.getFieldValues(TRAINING_CLASS);
	assertThat(assignedClasses.size(),is(2));
	assertThat(assignedClasses.get(0),is("class4"));
	assertThat(assignedClasses.get(1),is("class6"));
	}

	private ClassificationUpdateProcessorParams initParams(ClassificationUpdateProcessorFactory.Algorithm classificationAlgorithm) {
	ClassificationUpdateProcessorParams params= new ClassificationUpdateProcessorParams();
	params.setInputFieldNames(new String[]{TITLE,CONTENT,AUTHOR});
	params.setTrainingClassField(TRAINING_CLASS);
	params.setPredictedClassField(TRAINING_CLASS);
	params.setMinTf(1);
	params.setMinDf(1);
	params.setK(5);
	params.setAlgorithm(classificationAlgorithm);
	params.setMaxPredictedClasses(1);
	return params;
	}

	/**
	* Index some example documents with a class manually assigned.
	* This will be our trained model.
	*
	* @throws Exception If there is a low-level I/O error
	*/
	private void prepareTrainedIndexMonoClass() throws Exception {
	directory = newDirectory();
	RandomIndexWriter writer = new RandomIndexWriter(random(), directory);

	//class1
	addDoc(writer, buildLuceneDocument(ID, "1",
	TITLE, "word1 word1 word1",
	CONTENT, "word2 word2 word2",
	AUTHOR, "a",
	TRAINING_CLASS, "class1"));
	addDoc(writer, buildLuceneDocument(ID, "2",
	TITLE, "word1 word1",
	CONTENT, "word2 word2",
	AUTHOR, "a",
	TRAINING_CLASS, "class1"));
	addDoc(writer, buildLuceneDocument(ID, "3",
	TITLE, "word1 word1 word1",
	CONTENT, "word2",
	AUTHOR, "a",
	TRAINING_CLASS, "class1"));
	addDoc(writer, buildLuceneDocument(ID, "4",
	TITLE, "word1 word1 word1",
	CONTENT, "word2 word2 word2",
	AUTHOR, "a",
	TRAINING_CLASS, "class1"));
	//class2
	addDoc(writer, buildLuceneDocument(ID, "5",
	TITLE, "word4 word4 word4",
	CONTENT, "word5 word5",
	AUTHOR, "c",
	TRAINING_CLASS, "class2"));
	addDoc(writer, buildLuceneDocument(ID, "6",
	TITLE, "word4 word4",
	CONTENT, "word5",
	AUTHOR, "c",
	TRAINING_CLASS, "class2"));
	addDoc(writer, buildLuceneDocument(ID, "7",
	TITLE, "word4 word4 word4",
	CONTENT, "word5 word5 word5",
	AUTHOR, "c",
	TRAINING_CLASS, "class2"));
	addDoc(writer, buildLuceneDocument(ID, "8",
	TITLE, "word4",
	CONTENT, "word5 word5 word5 word5",
	AUTHOR, "c",
	TRAINING_CLASS, "class2"));
	//class3
	addDoc(writer, buildLuceneDocument(ID, "9",
	TITLE, "word6",
	CONTENT, "word7",
	AUTHOR, "a",
	TRAINING_CLASS, "class3"));
	addDoc(writer, buildLuceneDocument(ID, "10",
	TITLE, "word6",
	CONTENT, "word7",
	AUTHOR, "a",
	TRAINING_CLASS, "class3"));
	addDoc(writer, buildLuceneDocument(ID, "11",
	TITLE, "word6",
	CONTENT, "word7",
	AUTHOR, "a",
	TRAINING_CLASS, "class3"));
	addDoc(writer, buildLuceneDocument(ID, "12",
	TITLE, "word6",
	CONTENT, "word7",
	AUTHOR, "a",
	TRAINING_CLASS, "class3"));

	reader = writer.getReader();
	writer.close();
	searcher = newSearcher(reader);
	}

	private void prepareTrainedIndexMultiClass() throws Exception {
	directory = newDirectory();
	RandomIndexWriter writer = new RandomIndexWriter(random(), directory);

	//class1
	addDoc(writer, buildLuceneDocument(ID, "1",
	TITLE, "word1 word1 word1",
	CONTENT, "word2 word2 word2",
	AUTHOR, "Name Surname",
	TRAINING_CLASS, "class1",
	TRAINING_CLASS, "class2"
	));
	addDoc(writer, buildLuceneDocument(ID, "2",
	TITLE, "word1 word1",
	CONTENT, "word2 word2",
	AUTHOR, "Name Surname",
	TRAINING_CLASS, "class3",
	TRAINING_CLASS, "class2"
	));
	addDoc(writer, buildLuceneDocument(ID, "3",
	TITLE, "word1 word1 word1",
	CONTENT, "word2",
	AUTHOR, "Name Surname",
	TRAINING_CLASS, "class1",
	TRAINING_CLASS, "class2"
	));
	addDoc(writer, buildLuceneDocument(ID, "4",
	TITLE, "word1 word1 word1",
	CONTENT, "word2 word2 word2",
	AUTHOR, "Name Surname",
	TRAINING_CLASS, "class1",
	TRAINING_CLASS, "class2"
	));
	//class2
	addDoc(writer, buildLuceneDocument(ID, "5",
	TITLE, "word4 word4 word4",
	CONTENT, "word5 word5",
	AUTHOR, "Name1 Surname1",
	TRAINING_CLASS, "class6",
	TRAINING_CLASS, "class4"
	));
	addDoc(writer, buildLuceneDocument(ID, "6",
	TITLE, "word4 word4",
	CONTENT, "word5",
	AUTHOR, "Name1 Surname1",
	TRAINING_CLASS, "class5",
	TRAINING_CLASS, "class4"
	));
	addDoc(writer, buildLuceneDocument(ID, "7",
	TITLE, "word4 word4 word4",
	CONTENT, "word5 word5 word5",
	AUTHOR, "Name1 Surname1",
	TRAINING_CLASS, "class6",
	TRAINING_CLASS, "class4"
	));
	addDoc(writer, buildLuceneDocument(ID, "8",
	TITLE, "word4",
	CONTENT, "word5 word5 word5 word5",
	AUTHOR, "Name1 Surname1",
	TRAINING_CLASS, "class6",
	TRAINING_CLASS, "class4"
	));

	reader = writer.getReader();
	writer.close();
	searcher = newSearcher(reader);
	}

	public static Document buildLuceneDocument(Object... fieldsAndValues) {
	Document luceneDoc = new Document();
	for (int i=0; i<fieldsAndValues.length; i+=2) {
	luceneDoc.add(newTextField((String)fieldsAndValues[i], (String)fieldsAndValues[i+1], Field.Store.YES));
	}
	return luceneDoc;
	}

	private int addDoc(RandomIndexWriter writer, Document doc) throws IOException {
	writer.addDocument(doc);
	return writer.getDocStats().numDocs - 1;
	}
	}