--- /dev/null
+package org.apache.lucene.search;
+
+/**
+ * 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.
+ */
+
+import java.util.List;
+import java.util.Arrays;
+import java.io.IOException;
+
+import org.apache.lucene.analysis.MockAnalyzer;
+import org.apache.lucene.analysis.standard.StandardAnalyzer;
+import org.apache.lucene.util.LuceneTestCase;
+import org.apache.lucene.document.Document;
+import org.apache.lucene.document.Field;
+import org.apache.lucene.index.IndexReader;
+import org.apache.lucene.index.MultiReader;
+import org.apache.lucene.index.RandomIndexWriter;
+import org.apache.lucene.index.Term;
+import org.apache.lucene.store.Directory;
+import org.apache.lucene.queryParser.QueryParser;
+
+/**
+ * Tests {@link FuzzyQuery}.
+ *
+ */
+public class TestFuzzyQuery extends LuceneTestCase {
+
+ public void testFuzziness() throws Exception {
+ Directory directory = newDirectory();
+ RandomIndexWriter writer = new RandomIndexWriter(random, directory);
+ addDoc("aaaaa", writer);
+ addDoc("aaaab", writer);
+ addDoc("aaabb", writer);
+ addDoc("aabbb", writer);
+ addDoc("abbbb", writer);
+ addDoc("bbbbb", writer);
+ addDoc("ddddd", writer);
+
+ IndexReader reader = writer.getReader();
+ IndexSearcher searcher = newSearcher(reader);
+ writer.close();
+
+ FuzzyQuery query = new FuzzyQuery(new Term("field", "aaaaa"), FuzzyQuery.defaultMinSimilarity, 0);
+ ScoreDoc[] hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(3, hits.length);
+
+ // same with prefix
+ query = new FuzzyQuery(new Term("field", "aaaaa"), FuzzyQuery.defaultMinSimilarity, 1);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(3, hits.length);
+ query = new FuzzyQuery(new Term("field", "aaaaa"), FuzzyQuery.defaultMinSimilarity, 2);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(3, hits.length);
+ query = new FuzzyQuery(new Term("field", "aaaaa"), FuzzyQuery.defaultMinSimilarity, 3);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(3, hits.length);
+ query = new FuzzyQuery(new Term("field", "aaaaa"), FuzzyQuery.defaultMinSimilarity, 4);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(2, hits.length);
+ query = new FuzzyQuery(new Term("field", "aaaaa"), FuzzyQuery.defaultMinSimilarity, 5);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(1, hits.length);
+ query = new FuzzyQuery(new Term("field", "aaaaa"), FuzzyQuery.defaultMinSimilarity, 6);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(1, hits.length);
+
+ // test scoring
+ query = new FuzzyQuery(new Term("field", "bbbbb"), FuzzyQuery.defaultMinSimilarity, 0);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals("3 documents should match", 3, hits.length);
+ List<String> order = Arrays.asList("bbbbb","abbbb","aabbb");
+ for (int i = 0; i < hits.length; i++) {
+ final String term = searcher.doc(hits[i].doc).get("field");
+ //System.out.println(hits[i].score);
+ assertEquals(order.get(i), term);
+ }
+
+ // test pq size by supplying maxExpansions=2
+ // This query would normally return 3 documents, because 3 terms match (see above):
+ query = new FuzzyQuery(new Term("field", "bbbbb"), FuzzyQuery.defaultMinSimilarity, 0, 2);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals("only 2 documents should match", 2, hits.length);
+ order = Arrays.asList("bbbbb","abbbb");
+ for (int i = 0; i < hits.length; i++) {
+ final String term = searcher.doc(hits[i].doc).get("field");
+ //System.out.println(hits[i].score);
+ assertEquals(order.get(i), term);
+ }
+
+ // not similar enough:
+ query = new FuzzyQuery(new Term("field", "xxxxx"), FuzzyQuery.defaultMinSimilarity, 0);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(0, hits.length);
+ query = new FuzzyQuery(new Term("field", "aaccc"), FuzzyQuery.defaultMinSimilarity, 0); // edit distance to "aaaaa" = 3
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(0, hits.length);
+
+ // query identical to a word in the index:
+ query = new FuzzyQuery(new Term("field", "aaaaa"), FuzzyQuery.defaultMinSimilarity, 0);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(3, hits.length);
+ assertEquals(searcher.doc(hits[0].doc).get("field"), ("aaaaa"));
+ // default allows for up to two edits:
+ assertEquals(searcher.doc(hits[1].doc).get("field"), ("aaaab"));
+ assertEquals(searcher.doc(hits[2].doc).get("field"), ("aaabb"));
+
+ // query similar to a word in the index:
+ query = new FuzzyQuery(new Term("field", "aaaac"), FuzzyQuery.defaultMinSimilarity, 0);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(3, hits.length);
+ assertEquals(searcher.doc(hits[0].doc).get("field"), ("aaaaa"));
+ assertEquals(searcher.doc(hits[1].doc).get("field"), ("aaaab"));
+ assertEquals(searcher.doc(hits[2].doc).get("field"), ("aaabb"));
+
+ // now with prefix
+ query = new FuzzyQuery(new Term("field", "aaaac"), FuzzyQuery.defaultMinSimilarity, 1);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(3, hits.length);
+ assertEquals(searcher.doc(hits[0].doc).get("field"), ("aaaaa"));
+ assertEquals(searcher.doc(hits[1].doc).get("field"), ("aaaab"));
+ assertEquals(searcher.doc(hits[2].doc).get("field"), ("aaabb"));
+ query = new FuzzyQuery(new Term("field", "aaaac"), FuzzyQuery.defaultMinSimilarity, 2);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(3, hits.length);
+ assertEquals(searcher.doc(hits[0].doc).get("field"), ("aaaaa"));
+ assertEquals(searcher.doc(hits[1].doc).get("field"), ("aaaab"));
+ assertEquals(searcher.doc(hits[2].doc).get("field"), ("aaabb"));
+ query = new FuzzyQuery(new Term("field", "aaaac"), FuzzyQuery.defaultMinSimilarity, 3);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(3, hits.length);
+ assertEquals(searcher.doc(hits[0].doc).get("field"), ("aaaaa"));
+ assertEquals(searcher.doc(hits[1].doc).get("field"), ("aaaab"));
+ assertEquals(searcher.doc(hits[2].doc).get("field"), ("aaabb"));
+ query = new FuzzyQuery(new Term("field", "aaaac"), FuzzyQuery.defaultMinSimilarity, 4);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(2, hits.length);
+ assertEquals(searcher.doc(hits[0].doc).get("field"), ("aaaaa"));
+ assertEquals(searcher.doc(hits[1].doc).get("field"), ("aaaab"));
+ query = new FuzzyQuery(new Term("field", "aaaac"), FuzzyQuery.defaultMinSimilarity, 5);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(0, hits.length);
+
+
+ query = new FuzzyQuery(new Term("field", "ddddX"), FuzzyQuery.defaultMinSimilarity, 0);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(1, hits.length);
+ assertEquals(searcher.doc(hits[0].doc).get("field"), ("ddddd"));
+
+ // now with prefix
+ query = new FuzzyQuery(new Term("field", "ddddX"), FuzzyQuery.defaultMinSimilarity, 1);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(1, hits.length);
+ assertEquals(searcher.doc(hits[0].doc).get("field"), ("ddddd"));
+ query = new FuzzyQuery(new Term("field", "ddddX"), FuzzyQuery.defaultMinSimilarity, 2);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(1, hits.length);
+ assertEquals(searcher.doc(hits[0].doc).get("field"), ("ddddd"));
+ query = new FuzzyQuery(new Term("field", "ddddX"), FuzzyQuery.defaultMinSimilarity, 3);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(1, hits.length);
+ assertEquals(searcher.doc(hits[0].doc).get("field"), ("ddddd"));
+ query = new FuzzyQuery(new Term("field", "ddddX"), FuzzyQuery.defaultMinSimilarity, 4);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(1, hits.length);
+ assertEquals(searcher.doc(hits[0].doc).get("field"), ("ddddd"));
+ query = new FuzzyQuery(new Term("field", "ddddX"), FuzzyQuery.defaultMinSimilarity, 5);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(0, hits.length);
+
+
+ // different field = no match:
+ query = new FuzzyQuery(new Term("anotherfield", "ddddX"), FuzzyQuery.defaultMinSimilarity, 0);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(0, hits.length);
+
+ searcher.close();
+ reader.close();
+ directory.close();
+ }
+
+ public void testFuzzinessLong() throws Exception {
+ Directory directory = newDirectory();
+ RandomIndexWriter writer = new RandomIndexWriter(random, directory);
+ addDoc("aaaaaaa", writer);
+ addDoc("segment", writer);
+
+ IndexReader reader = writer.getReader();
+ IndexSearcher searcher = newSearcher(reader);
+ writer.close();
+
+ FuzzyQuery query;
+ // not similar enough:
+ query = new FuzzyQuery(new Term("field", "xxxxx"), FuzzyQuery.defaultMinSimilarity, 0);
+ ScoreDoc[] hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(0, hits.length);
+ // edit distance to "aaaaaaa" = 3, this matches because the string is longer than
+ // in testDefaultFuzziness so a bigger difference is allowed:
+ query = new FuzzyQuery(new Term("field", "aaaaccc"), FuzzyQuery.defaultMinSimilarity, 0);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(1, hits.length);
+ assertEquals(searcher.doc(hits[0].doc).get("field"), ("aaaaaaa"));
+
+ // now with prefix
+ query = new FuzzyQuery(new Term("field", "aaaaccc"), FuzzyQuery.defaultMinSimilarity, 1);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(1, hits.length);
+ assertEquals(searcher.doc(hits[0].doc).get("field"), ("aaaaaaa"));
+ query = new FuzzyQuery(new Term("field", "aaaaccc"), FuzzyQuery.defaultMinSimilarity, 4);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(1, hits.length);
+ assertEquals(searcher.doc(hits[0].doc).get("field"), ("aaaaaaa"));
+ query = new FuzzyQuery(new Term("field", "aaaaccc"), FuzzyQuery.defaultMinSimilarity, 5);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(0, hits.length);
+
+ // no match, more than half of the characters is wrong:
+ query = new FuzzyQuery(new Term("field", "aaacccc"), FuzzyQuery.defaultMinSimilarity, 0);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(0, hits.length);
+
+ // now with prefix
+ query = new FuzzyQuery(new Term("field", "aaacccc"), FuzzyQuery.defaultMinSimilarity, 2);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(0, hits.length);
+
+ // "student" and "stellent" are indeed similar to "segment" by default:
+ query = new FuzzyQuery(new Term("field", "student"), FuzzyQuery.defaultMinSimilarity, 0);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(1, hits.length);
+ query = new FuzzyQuery(new Term("field", "stellent"), FuzzyQuery.defaultMinSimilarity, 0);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(1, hits.length);
+
+ // now with prefix
+ query = new FuzzyQuery(new Term("field", "student"), FuzzyQuery.defaultMinSimilarity, 1);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(1, hits.length);
+ query = new FuzzyQuery(new Term("field", "stellent"), FuzzyQuery.defaultMinSimilarity, 1);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(1, hits.length);
+ query = new FuzzyQuery(new Term("field", "student"), FuzzyQuery.defaultMinSimilarity, 2);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(0, hits.length);
+ query = new FuzzyQuery(new Term("field", "stellent"), FuzzyQuery.defaultMinSimilarity, 2);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(0, hits.length);
+
+ // "student" doesn't match anymore thanks to increased minimum similarity:
+ query = new FuzzyQuery(new Term("field", "student"), 0.6f, 0);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(0, hits.length);
+
+ try {
+ query = new FuzzyQuery(new Term("field", "student"), 1.1f);
+ fail("Expected IllegalArgumentException");
+ } catch (IllegalArgumentException e) {
+ // expecting exception
+ }
+ try {
+ query = new FuzzyQuery(new Term("field", "student"), -0.1f);
+ fail("Expected IllegalArgumentException");
+ } catch (IllegalArgumentException e) {
+ // expecting exception
+ }
+
+ searcher.close();
+ reader.close();
+ directory.close();
+ }
+
+ public void testTokenLengthOpt() throws IOException {
+ Directory directory = newDirectory();
+ RandomIndexWriter writer = new RandomIndexWriter(random, directory);
+ addDoc("12345678911", writer);
+ addDoc("segment", writer);
+
+ IndexReader reader = writer.getReader();
+ IndexSearcher searcher = newSearcher(reader);
+ writer.close();
+
+ Query query;
+ // term not over 10 chars, so optimization shortcuts
+ query = new FuzzyQuery(new Term("field", "1234569"), 0.9f);
+ ScoreDoc[] hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(0, hits.length);
+
+ // 10 chars, so no optimization
+ query = new FuzzyQuery(new Term("field", "1234567891"), 0.9f);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(0, hits.length);
+
+ // over 10 chars, so no optimization
+ query = new FuzzyQuery(new Term("field", "12345678911"), 0.9f);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(1, hits.length);
+
+ // over 10 chars, no match
+ query = new FuzzyQuery(new Term("field", "sdfsdfsdfsdf"), 0.9f);
+ hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(0, hits.length);
+
+ searcher.close();
+ reader.close();
+ directory.close();
+ }
+
+ /** Test the TopTermsBoostOnlyBooleanQueryRewrite rewrite method. */
+ public void testBoostOnlyRewrite() throws Exception {
+ Directory directory = newDirectory();
+ RandomIndexWriter writer = new RandomIndexWriter(random, directory);
+ addDoc("Lucene", writer);
+ addDoc("Lucene", writer);
+ addDoc("Lucenne", writer);
+
+ IndexReader reader = writer.getReader();
+ IndexSearcher searcher = newSearcher(reader);
+ writer.close();
+
+ FuzzyQuery query = new FuzzyQuery(new Term("field", "Lucene"));
+ query.setRewriteMethod(new MultiTermQuery.TopTermsBoostOnlyBooleanQueryRewrite(50));
+ ScoreDoc[] hits = searcher.search(query, null, 1000).scoreDocs;
+ assertEquals(3, hits.length);
+ // normally, 'Lucenne' would be the first result as IDF will skew the score.
+ assertEquals("Lucene", reader.document(hits[0].doc).get("field"));
+ assertEquals("Lucene", reader.document(hits[1].doc).get("field"));
+ assertEquals("Lucenne", reader.document(hits[2].doc).get("field"));
+ searcher.close();
+ reader.close();
+ directory.close();
+ }
+
+ public void testGiga() throws Exception {
+
+ MockAnalyzer analyzer = new MockAnalyzer(random);
+ Directory index = newDirectory();
+ RandomIndexWriter w = new RandomIndexWriter(random, index);
+
+ addDoc("Lucene in Action", w);
+ addDoc("Lucene for Dummies", w);
+
+ //addDoc("Giga", w);
+ addDoc("Giga byte", w);
+
+ addDoc("ManagingGigabytesManagingGigabyte", w);
+ addDoc("ManagingGigabytesManagingGigabytes", w);
+
+ addDoc("The Art of Computer Science", w);
+ addDoc("J. K. Rowling", w);
+ addDoc("JK Rowling", w);
+ addDoc("Joanne K Roling", w);
+ addDoc("Bruce Willis", w);
+ addDoc("Willis bruce", w);
+ addDoc("Brute willis", w);
+ addDoc("B. willis", w);
+ IndexReader r = w.getReader();
+ w.close();
+
+ Query q = new QueryParser(TEST_VERSION_CURRENT, "field", analyzer).parse( "giga~0.9" );
+
+ // 3. search
+ IndexSearcher searcher = newSearcher(r);
+ ScoreDoc[] hits = searcher.search(q, 10).scoreDocs;
+ assertEquals(1, hits.length);
+ assertEquals("Giga byte", searcher.doc(hits[0].doc).get("field"));
+ searcher.close();
+ r.close();
+ index.close();
+ }
+
+ private void addDoc(String text, RandomIndexWriter writer) throws IOException {
+ Document doc = new Document();
+ doc.add(newField("field", text, Field.Store.YES, Field.Index.ANALYZED));
+ writer.addDocument(doc);
+ }
+
+}
fnp / pylucene.git / blobdiff