Java tutorial
/* * Created on 28-Oct-2004 */ /* * 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.lucene.search.highlight; import java.io.IOException; import org.apache.lucene.analysis.Analyzer; import org.apache.lucene.analysis.TokenStream; import org.apache.lucene.document.Document; import org.apache.lucene.index.Fields; import org.apache.lucene.index.IndexReader; import org.apache.lucene.index.Terms; /** * Convenience methods for obtaining a {@link TokenStream} for use with the {@link Highlighter} - can obtain from * term vectors with offsets and positions or from an Analyzer re-parsing the stored content. * * @see TokenStreamFromTermVector */ public class TokenSources { private TokenSources() { } /** * Get a token stream from either un-inverting a term vector if possible, or by analyzing the text. * * WARNING: Don't call this if there is more than one value for this field. If there are, and if there are term * vectors, then there is a single tokenstream with offsets suggesting all the field values were concatenated. * * @param field The field to either get term vectors from or to analyze the text from. * @param tvFields from {@link IndexReader#getTermVectors(int)}. Possibly null. For performance, this instance should * be re-used for the same document (e.g. when highlighting multiple fields). * @param text the text to analyze, failing term vector un-inversion * @param analyzer the analyzer to analyze {@code text} with, failing term vector un-inversion * @param maxStartOffset Terms with a startOffset greater than this aren't returned. Use -1 for no limit. * Suggest using {@link Highlighter#getMaxDocCharsToAnalyze()} - 1. * * @return a token stream from either term vectors, or from analyzing the text. Never null. */ public static TokenStream getTokenStream(String field, Fields tvFields, String text, Analyzer analyzer, int maxStartOffset) throws IOException { TokenStream tokenStream = getTermVectorTokenStreamOrNull(field, tvFields, maxStartOffset); if (tokenStream != null) { return tokenStream; } tokenStream = analyzer.tokenStream(field, text); if (maxStartOffset >= 0 && maxStartOffset < text.length() - 1) { tokenStream = new LimitTokenOffsetFilter(tokenStream, maxStartOffset); } return tokenStream; } /** * Get a token stream by un-inverting the term vector. This method returns null if {@code tvFields} is null * or if the field has no term vector, or if the term vector doesn't have offsets. Positions are recommended on the * term vector but it isn't strictly required. * * @param field The field to get term vectors from. * @param tvFields from {@link IndexReader#getTermVectors(int)}. Possibly null. For performance, this instance should * be re-used for the same document (e.g. when highlighting multiple fields). * @param maxStartOffset Terms with a startOffset greater than this aren't returned. Use -1 for no limit. * Suggest using {@link Highlighter#getMaxDocCharsToAnalyze()} - 1 * @return a token stream from term vectors. Null if no term vectors with the right options. */ public static TokenStream getTermVectorTokenStreamOrNull(String field, Fields tvFields, int maxStartOffset) throws IOException { if (tvFields == null) { return null; } final Terms tvTerms = tvFields.terms(field); if (tvTerms == null || !tvTerms.hasOffsets()) { return null; } return new TokenStreamFromTermVector(tvTerms, maxStartOffset); } /** * A convenience method that tries to first get a {@link TokenStreamFromTermVector} for the * specified docId, then, falls back to using the passed in * {@link org.apache.lucene.document.Document} to retrieve the TokenStream. * This is useful when you already have the document, but would prefer to use * the vector first. * * @param reader The {@link org.apache.lucene.index.IndexReader} to use to try * and get the vector from * @param docId The docId to retrieve. * @param field The field to retrieve on the document * @param document The document to fall back on * @param analyzer The analyzer to use for creating the TokenStream if the * vector doesn't exist * @return The {@link org.apache.lucene.analysis.TokenStream} for the * {@link org.apache.lucene.index.IndexableField} on the * {@link org.apache.lucene.document.Document} * @throws IOException if there was an error loading */ @Deprecated // maintenance reasons LUCENE-6445 public static TokenStream getAnyTokenStream(IndexReader reader, int docId, String field, Document document, Analyzer analyzer) throws IOException { TokenStream ts = null; Fields vectors = reader.getTermVectors(docId); if (vectors != null) { Terms vector = vectors.terms(field); if (vector != null) { ts = getTokenStream(vector); } } // No token info stored so fall back to analyzing raw content if (ts == null) { ts = getTokenStream(document, field, analyzer); } return ts; } /** * A convenience method that tries a number of approaches to getting a token * stream. The cost of finding there are no termVectors in the index is * minimal (1000 invocations still registers 0 ms). So this "lazy" (flexible?) * approach to coding is probably acceptable * * @return null if field not stored correctly * @throws IOException If there is a low-level I/O error */ @Deprecated // maintenance reasons LUCENE-6445 public static TokenStream getAnyTokenStream(IndexReader reader, int docId, String field, Analyzer analyzer) throws IOException { TokenStream ts = null; Fields vectors = reader.getTermVectors(docId); if (vectors != null) { Terms vector = vectors.terms(field); if (vector != null) { ts = getTokenStream(vector); } } // No token info stored so fall back to analyzing raw content if (ts == null) { ts = getTokenStream(reader, docId, field, analyzer); } return ts; } /** Simply calls {@link #getTokenStream(org.apache.lucene.index.Terms)} now. */ @Deprecated // maintenance reasons LUCENE-6445 public static TokenStream getTokenStream(Terms vector, boolean tokenPositionsGuaranteedContiguous) throws IOException { return getTokenStream(vector); } /** * Returns a token stream generated from a {@link Terms}. This * can be used to feed the highlighter with a pre-parsed token * stream. The {@link Terms} must have offsets available. If there are no positions available, * all tokens will have position increments reflecting adjacent tokens, or coincident when terms * share a start offset. If there are stopwords filtered from the index, you probably want to ensure * term vectors have positions so that phrase queries won't match across stopwords. * * @throws IllegalArgumentException if no offsets are available */ @Deprecated // maintenance reasons LUCENE-6445 public static TokenStream getTokenStream(final Terms tpv) throws IOException { if (!tpv.hasOffsets()) { throw new IllegalArgumentException("Highlighting requires offsets from the TokenStream."); //TokenStreamFromTermVector can handle a lack of offsets if there are positions. But // highlighters require offsets, so we insist here. } return new TokenStreamFromTermVector(tpv, -1); // TODO propagate maxStartOffset; see LUCENE-6445 } /** * Returns a {@link TokenStream} with positions and offsets constructed from * field termvectors. If the field has no termvectors or offsets * are not included in the termvector, return null. See {@link #getTokenStream(org.apache.lucene.index.Terms)} * for an explanation of what happens when positions aren't present. * * @param reader the {@link IndexReader} to retrieve term vectors from * @param docId the document to retrieve termvectors for * @param field the field to retrieve termvectors for * @return a {@link TokenStream}, or null if offsets are not available * @throws IOException If there is a low-level I/O error * * @see #getTokenStream(org.apache.lucene.index.Terms) */ @Deprecated // maintenance reasons LUCENE-6445 public static TokenStream getTokenStreamWithOffsets(IndexReader reader, int docId, String field) throws IOException { Fields vectors = reader.getTermVectors(docId); if (vectors == null) { return null; } Terms vector = vectors.terms(field); if (vector == null) { return null; } if (!vector.hasOffsets()) { return null; } return getTokenStream(vector); } @Deprecated // maintenance reasons LUCENE-6445 public static TokenStream getTokenStream(IndexReader reader, int docId, String field, Analyzer analyzer) throws IOException { Document doc = reader.document(docId); return getTokenStream(doc, field, analyzer); } @Deprecated // maintenance reasons LUCENE-6445 public static TokenStream getTokenStream(Document doc, String field, Analyzer analyzer) { String contents = doc.get(field); if (contents == null) { throw new IllegalArgumentException( "Field " + field + " in document is not stored and cannot be analyzed"); } return getTokenStream(field, contents, analyzer); } @Deprecated // maintenance reasons LUCENE-6445 public static TokenStream getTokenStream(String field, String contents, Analyzer analyzer) { return analyzer.tokenStream(field, contents); } }