| /* |
| * Created on 28-Oct-2004 |
| */ |
| package org.apache.lucene.search.highlight; |
| |
| /** |
| * 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.io.IOException; |
| import java.io.StringReader; |
| import java.util.ArrayList; |
| import java.util.Comparator; |
| |
| import org.apache.lucene.analysis.Analyzer; |
| import org.apache.lucene.analysis.Token; |
| import org.apache.lucene.analysis.TokenStream; |
| import org.apache.lucene.analysis.tokenattributes.CharTermAttribute; |
| import org.apache.lucene.analysis.tokenattributes.OffsetAttribute; |
| import org.apache.lucene.analysis.tokenattributes.PositionIncrementAttribute; |
| import org.apache.lucene.document.Document; |
| import org.apache.lucene.index.IndexReader; |
| import org.apache.lucene.index.TermFreqVector; |
| import org.apache.lucene.index.TermPositionVector; |
| import org.apache.lucene.index.TermVectorOffsetInfo; |
| import org.apache.lucene.util.ArrayUtil; |
| import org.apache.lucene.util.BytesRef; |
| |
| /** |
| * Hides implementation issues associated with obtaining a TokenStream for use |
| * with the higlighter - can obtain from TermFreqVectors with offsets and |
| * (optionally) positions or from Analyzer class reparsing the stored content. |
| */ |
| public class TokenSources { |
| /** |
| * A convenience method that tries to first get a TermPositionVector 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 doc 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 |
| */ |
| |
| public static TokenStream getAnyTokenStream(IndexReader reader, int docId, |
| String field, Document doc, Analyzer analyzer) throws IOException { |
| TokenStream ts = null; |
| |
| TermFreqVector tfv = reader.getTermFreqVector(docId, field); |
| if (tfv != null) { |
| if (tfv instanceof TermPositionVector) { |
| ts = getTokenStream((TermPositionVector) tfv); |
| } |
| } |
| // No token info stored so fall back to analyzing raw content |
| if (ts == null) { |
| ts = getTokenStream(doc, 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 |
| * |
| * @param reader |
| * @param docId |
| * @param field |
| * @param analyzer |
| * @return null if field not stored correctly |
| * @throws IOException |
| */ |
| public static TokenStream getAnyTokenStream(IndexReader reader, int docId, |
| String field, Analyzer analyzer) throws IOException { |
| TokenStream ts = null; |
| |
| TermFreqVector tfv = reader.getTermFreqVector(docId, field); |
| if (tfv != null) { |
| if (tfv instanceof TermPositionVector) { |
| ts = getTokenStream((TermPositionVector) tfv); |
| } |
| } |
| // No token info stored so fall back to analyzing raw content |
| if (ts == null) { |
| ts = getTokenStream(reader, docId, field, analyzer); |
| } |
| return ts; |
| } |
| |
| public static TokenStream getTokenStream(TermPositionVector tpv) { |
| // assumes the worst and makes no assumptions about token position |
| // sequences. |
| return getTokenStream(tpv, false); |
| } |
| |
| /** |
| * Low level api. Returns a token stream or null if no offset info available |
| * in index. This can be used to feed the highlighter with a pre-parsed token |
| * stream |
| * |
| * In my tests the speeds to recreate 1000 token streams using this method |
| * are: - with TermVector offset only data stored - 420 milliseconds - with |
| * TermVector offset AND position data stored - 271 milliseconds (nb timings |
| * for TermVector with position data are based on a tokenizer with contiguous |
| * positions - no overlaps or gaps) The cost of not using TermPositionVector |
| * to store pre-parsed content and using an analyzer to re-parse the original |
| * content: - reanalyzing the original content - 980 milliseconds |
| * |
| * The re-analyze timings will typically vary depending on - 1) The complexity |
| * of the analyzer code (timings above were using a |
| * stemmer/lowercaser/stopword combo) 2) The number of other fields (Lucene |
| * reads ALL fields off the disk when accessing just one document field - can |
| * cost dear!) 3) Use of compression on field storage - could be faster due to |
| * compression (less disk IO) or slower (more CPU burn) depending on the |
| * content. |
| * |
| * @param tpv |
| * @param tokenPositionsGuaranteedContiguous true if the token position |
| * numbers have no overlaps or gaps. If looking to eek out the last |
| * drops of performance, set to true. If in doubt, set to false. |
| */ |
| public static TokenStream getTokenStream(TermPositionVector tpv, |
| boolean tokenPositionsGuaranteedContiguous) { |
| if (!tokenPositionsGuaranteedContiguous && tpv.getTermPositions(0) != null) { |
| return new TokenStreamFromTermPositionVector(tpv); |
| } |
| |
| // an object used to iterate across an array of tokens |
| final class StoredTokenStream extends TokenStream { |
| Token tokens[]; |
| |
| int currentToken = 0; |
| |
| CharTermAttribute termAtt; |
| |
| OffsetAttribute offsetAtt; |
| |
| PositionIncrementAttribute posincAtt; |
| |
| StoredTokenStream(Token tokens[]) { |
| this.tokens = tokens; |
| termAtt = addAttribute(CharTermAttribute.class); |
| offsetAtt = addAttribute(OffsetAttribute.class); |
| posincAtt = addAttribute(PositionIncrementAttribute.class); |
| } |
| |
| @Override |
| public boolean incrementToken() throws IOException { |
| if (currentToken >= tokens.length) { |
| return false; |
| } |
| Token token = tokens[currentToken++]; |
| clearAttributes(); |
| termAtt.setEmpty().append(token); |
| offsetAtt.setOffset(token.startOffset(), token.endOffset()); |
| posincAtt |
| .setPositionIncrement(currentToken <= 1 |
| || tokens[currentToken - 1].startOffset() > tokens[currentToken - 2] |
| .startOffset() ? 1 : 0); |
| return true; |
| } |
| } |
| // code to reconstruct the original sequence of Tokens |
| BytesRef[] terms = tpv.getTerms(); |
| int[] freq = tpv.getTermFrequencies(); |
| int totalTokens = 0; |
| for (int t = 0; t < freq.length; t++) { |
| totalTokens += freq[t]; |
| } |
| Token tokensInOriginalOrder[] = new Token[totalTokens]; |
| ArrayList<Token> unsortedTokens = null; |
| for (int t = 0; t < freq.length; t++) { |
| TermVectorOffsetInfo[] offsets = tpv.getOffsets(t); |
| if (offsets == null) { |
| throw new IllegalArgumentException( |
| "Required TermVector Offset information was not found"); |
| } |
| |
| int[] pos = null; |
| if (tokenPositionsGuaranteedContiguous) { |
| // try get the token position info to speed up assembly of tokens into |
| // sorted sequence |
| pos = tpv.getTermPositions(t); |
| } |
| if (pos == null) { |
| // tokens NOT stored with positions or not guaranteed contiguous - must |
| // add to list and sort later |
| if (unsortedTokens == null) { |
| unsortedTokens = new ArrayList<Token>(); |
| } |
| for (int tp = 0; tp < offsets.length; tp++) { |
| Token token = new Token(terms[t].utf8ToString(), |
| offsets[tp].getStartOffset(), offsets[tp].getEndOffset()); |
| unsortedTokens.add(token); |
| } |
| } else { |
| // We have positions stored and a guarantee that the token position |
| // information is contiguous |
| |
| // This may be fast BUT wont work if Tokenizers used which create >1 |
| // token in same position or |
| // creates jumps in position numbers - this code would fail under those |
| // circumstances |
| |
| // tokens stored with positions - can use this to index straight into |
| // sorted array |
| for (int tp = 0; tp < pos.length; tp++) { |
| Token token = new Token(terms[t].utf8ToString(), |
| offsets[tp].getStartOffset(), offsets[tp].getEndOffset()); |
| tokensInOriginalOrder[pos[tp]] = token; |
| } |
| } |
| } |
| // If the field has been stored without position data we must perform a sort |
| if (unsortedTokens != null) { |
| tokensInOriginalOrder = unsortedTokens.toArray(new Token[unsortedTokens |
| .size()]); |
| ArrayUtil.mergeSort(tokensInOriginalOrder, new Comparator<Token>() { |
| public int compare(Token t1, Token t2) { |
| if (t1.startOffset() == t2.startOffset()) return t1.endOffset() |
| - t2.endOffset(); |
| else return t1.startOffset() - t2.startOffset(); |
| } |
| }); |
| } |
| return new StoredTokenStream(tokensInOriginalOrder); |
| } |
| |
| public static TokenStream getTokenStream(IndexReader reader, int docId, |
| String field) throws IOException { |
| TermFreqVector tfv = reader.getTermFreqVector(docId, field); |
| if (tfv == null) { |
| throw new IllegalArgumentException(field + " in doc #" + docId |
| + "does not have any term position data stored"); |
| } |
| if (tfv instanceof TermPositionVector) { |
| TermPositionVector tpv = (TermPositionVector) reader.getTermFreqVector( |
| docId, field); |
| return getTokenStream(tpv); |
| } |
| throw new IllegalArgumentException(field + " in doc #" + docId |
| + "does not have any term position data stored"); |
| } |
| |
| // convenience method |
| public static TokenStream getTokenStream(IndexReader reader, int docId, |
| String field, Analyzer analyzer) throws IOException { |
| Document doc = reader.document(docId); |
| return getTokenStream(doc, field, analyzer); |
| } |
| |
| 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); |
| } |
| |
| // convenience method |
| public static TokenStream getTokenStream(String field, String contents, |
| Analyzer analyzer) { |
| try { |
| return analyzer.reusableTokenStream(field, new StringReader(contents)); |
| } catch (IOException ex) { |
| throw new RuntimeException(ex); |
| } |
| } |
| |
| } |
