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package org.apache.lucene.index;
/*
* 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.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
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.search.similarities.DefaultSimilarity;
import org.apache.lucene.store.Directory;
import org.apache.lucene.util.LuceneTestCase;
import org.apache.lucene.util._TestUtil;
/**
* Tests the maxTermFrequency statistic in FieldInvertState
*/
public class TestMaxTermFrequency extends LuceneTestCase {
Directory dir;
IndexReader reader;
/* expected maxTermFrequency values for our documents */
ArrayList<Integer> expected = new ArrayList<Integer>();
@Override
public void setUp() throws Exception {
super.setUp();
dir = newDirectory();
IndexWriterConfig config = newIndexWriterConfig(TEST_VERSION_CURRENT,
new MockAnalyzer(random(), MockTokenizer.SIMPLE, true)).setMergePolicy(newLogMergePolicy());
config.setSimilarity(new TestSimilarity());
RandomIndexWriter writer = new RandomIndexWriter(random(), dir, config);
Document doc = new Document();
Field foo = newTextField("foo", "", Field.Store.NO);
doc.add(foo);
for (int i = 0; i < 100; i++) {
foo.setStringValue(addValue());
writer.addDocument(doc);
}
reader = writer.getReader();
writer.close();
}
@Override
public void tearDown() throws Exception {
reader.close();
dir.close();
super.tearDown();
}
public void test() throws Exception {
NumericDocValues fooNorms = MultiDocValues.getNormValues(reader, "foo");
for (int i = 0; i < reader.maxDoc(); i++) {
assertEquals(expected.get(i).intValue(), fooNorms.get(i) & 0xff);
}
}
/**
* Makes a bunch of single-char tokens (the max freq will at most be 255).
* shuffles them around, and returns the whole list with Arrays.toString().
* This works fine because we use lettertokenizer.
* puts the max-frequency term into expected, to be checked against the norm.
*/
private String addValue() {
List<String> terms = new ArrayList<String>();
int maxCeiling = _TestUtil.nextInt(random(), 0, 255);
int max = 0;
for (char ch = 'a'; ch <= 'z'; ch++) {
int num = _TestUtil.nextInt(random(), 0, maxCeiling);
for (int i = 0; i < num; i++)
terms.add(Character.toString(ch));
max = Math.max(max, num);
}
expected.add(max);
Collections.shuffle(terms, random());
return Arrays.toString(terms.toArray(new String[terms.size()]));
}
/**
* Simple similarity that encodes maxTermFrequency directly as a byte
*/
class TestSimilarity extends DefaultSimilarity {
@Override
public byte encodeNormValue(float f) {
return (byte) f;
}
@Override
public float decodeNormValue(byte b) {
return (float) b;
}
@Override
public float lengthNorm(FieldInvertState state) {
return state.getMaxTermFrequency();
}
}
}