一步一步跟我学习lucene(11)---lucene搜索之高亮显示highlighter
highlighter介绍
这几天一直加班,博客有三天没有更新了,望见谅;我们在做查询的时候,希望对我们自己的搜索结果与搜索内容相近的地方进行着重显示,就如下面的效果
这里我们搜索的内容是“一步一步跟我学习lucene”,搜索引擎展示的结果中对用户的输入信息进行了配色方面的处理,这种区分正常文本和输入内容的效果即是高亮显示;
这样做的好处:
- 视觉上让人便于查找有搜索对应的文本块;
- 界面展示更友好;
lucene提供了highlighter插件来体现类似的效果;
highlighter对查询关键字高亮处理;
highlighter包包含了用于处理结果页查询内容高亮显示的功能,其中Highlighter类highlighter包的核心组件,借助Fragmenter, fragment Scorer, 和Formatter等类来支持用户自定义高亮展示的功能;
示例程序
这里边我利用了之前的做的目录文件索引
package com.lucene.search.util; import java.io.IOException; import java.io.StringReader; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; import org.apache.lucene.analysis.Analyzer; import org.apache.lucene.analysis.TokenStream; import org.apache.lucene.analysis.standard.StandardAnalyzer; import org.apache.lucene.document.Document; import org.apache.lucene.index.Term; import org.apache.lucene.search.IndexSearcher; import org.apache.lucene.search.ScoreDoc; import org.apache.lucene.search.TermQuery; import org.apache.lucene.search.TopDocs; import org.apache.lucene.search.highlight.Highlighter; import org.apache.lucene.search.highlight.InvalidTokenOffsetsException; import org.apache.lucene.search.highlight.QueryScorer; import org.apache.lucene.search.highlight.SimpleFragmenter; import org.apache.lucene.search.highlight.SimpleHTMLFormatter; import org.apache.lucene.util.BytesRef; public class HighlighterTest { public static void main(String[] args) { IndexSearcher searcher; TopDocs docs; ExecutorService service = Executors.newCachedThreadPool(); try { searcher = SearchUtil.getMultiSearcher("index", service); Term term = new Term("content",new BytesRef("lucene")); TermQuery termQuery = new TermQuery(term); docs = SearchUtil.getScoreDocsByPerPage(1, 30, searcher, termQuery); ScoreDoc[] hits = docs.scoreDocs; QueryScorer scorer = new QueryScorer(termQuery); SimpleHTMLFormatter simpleHtmlFormatter = new SimpleHTMLFormatter("<B>","</B>");//设定高亮显示的格式<B>keyword</B>,此为默认的格式 Highlighter highlighter = new Highlighter(simpleHtmlFormatter,scorer); highlighter.setTextFragmenter(new SimpleFragmenter(20));//设置每次返回的字符数 Analyzer analyzer = new StandardAnalyzer(); for(int i=0;i<hits.length;i++){ Document doc = searcher.doc(hits[i].doc); String str = highlighter.getBestFragment(analyzer, "content", doc.get("content")) ; System.out.println(str); } } catch (IOException e1) { // TODO Auto-generated catch block e1.printStackTrace(); } catch (InvalidTokenOffsetsException e) { // TODO Auto-generated catch block e.printStackTrace(); }finally{ service.shutdown(); } } }
lucene的highlighter高亮展示的原理:
- 根据Formatter和Scorer创建highlighter对象,formatter定义了高亮的显示方式,而scorer定义了高亮的评分;
评分的算法是先根据term的评分值获取对应的document的权重,在此基础上对文本的内容进行轮询,获取对应的文本出现的次数,和它在term对应的文本中出现的位置(便于高亮处理),评分并分词的算法为:
public float getTokenScore() { position += posIncAtt.getPositionIncrement();//记录出现的位置 String termText = termAtt.toString(); WeightedSpanTerm weightedSpanTerm; if ((weightedSpanTerm = fieldWeightedSpanTerms.get( termText)) == null) { return 0; } if (weightedSpanTerm.positionSensitive && !weightedSpanTerm.checkPosition(position)) { return 0; } float score = weightedSpanTerm.getWeight();//获取权重 // found a query term - is it unique in this doc? if (!foundTerms.contains(termText)) {//结果排重处理 totalScore += score; foundTerms.add(termText); } return score; }
formatter的原理为:对搜索的文本进行判断,如果scorer获取的totalScore不小于0,即查询内容在对应的term中存在,则按照格式拼接成preTag+查询内容+postTag的格式
详细算法如下:
public String highlightTerm(String originalText, TokenGroup tokenGroup) { if (tokenGroup.getTotalScore() <= 0) { return originalText; } // Allocate StringBuilder with the right number of characters from the // beginning, to avoid char[] allocations in the middle of appends. StringBuilder returnBuffer = new StringBuilder(preTag.length() + originalText.length() + postTag.length()); returnBuffer.append(preTag); returnBuffer.append(originalText); returnBuffer.append(postTag); return returnBuffer.toString(); }
其默认格式为“<B></B>”的形式;
- Highlighter根据scorer和formatter,对document进行分析,查询结果调用getBestTextFragments,TokenStream tokenStream,String text,boolean mergeContiguousFragments,int maxNumFragments),其过程为
- scorer首先初始化查询内容对应的出现位置的下标,然后对tokenstream添加PositionIncrementAttribute,此类记录单词出现的位置;
- 对文本内容进行轮询,判断查询的文本长度是否超出限制,如果超出文本长度提示过长内容;
- 如果获取到指定的文本,先对单次查询的内容进行内容的截取(截取值根据setTextFragmenter指定的值决定),再调用formatter的highlightTerm方法对文本进行重新构建
- 在本次轮询和下次单词出现之前对文本内容进行处理
查询工具类
package com.lucene.search.util; import java.io.File; import java.io.IOException; import java.nio.file.Paths; import java.util.Set; import java.util.concurrent.ExecutorService; import org.apache.lucene.analysis.Analyzer; import org.apache.lucene.analysis.standard.StandardAnalyzer; import org.apache.lucene.document.Document; import org.apache.lucene.index.DirectoryReader; import org.apache.lucene.index.IndexReader; import org.apache.lucene.index.MultiReader; import org.apache.lucene.index.Term; import org.apache.lucene.queryparser.classic.ParseException; import org.apache.lucene.queryparser.classic.QueryParser; import org.apache.lucene.search.BooleanQuery; import org.apache.lucene.search.IndexSearcher; import org.apache.lucene.search.MatchAllDocsQuery; import org.apache.lucene.search.NumericRangeQuery; import org.apache.lucene.search.Query; import org.apache.lucene.search.ScoreDoc; import org.apache.lucene.search.TermQuery; import org.apache.lucene.search.TopDocs; import org.apache.lucene.search.BooleanClause.Occur; import org.apache.lucene.search.highlight.Highlighter; import org.apache.lucene.search.highlight.InvalidTokenOffsetsException; import org.apache.lucene.search.highlight.QueryScorer; import org.apache.lucene.search.highlight.SimpleFragmenter; import org.apache.lucene.search.highlight.SimpleHTMLFormatter; import org.apache.lucene.store.FSDirectory; import org.apache.lucene.util.BytesRef; /**lucene索引查询工具类 * @author lenovo * */ public class SearchUtil { /**获取IndexSearcher对象 * @param indexPath * @param service * @return * @throws IOException */ public static IndexSearcher getIndexSearcherByParentPath(String parentPath,ExecutorService service) throws IOException{ MultiReader reader = null; //设置 try { File[] files = new File(parentPath).listFiles(); IndexReader[] readers = new IndexReader[files.length]; for (int i = 0 ; i < files.length ; i ++) { readers[i] = DirectoryReader.open(FSDirectory.open(Paths.get(files[i].getPath(), new String[0]))); } reader = new MultiReader(readers); } catch (IOException e) { // TODO Auto-generated catch block e.printStackTrace(); } return new IndexSearcher(reader,service); } /**多目录多线程查询 * @param parentPath 父级索引目录 * @param service 多线程查询 * @return * @throws IOException */ public static IndexSearcher getMultiSearcher(String parentPath,ExecutorService service) throws IOException{ File file = new File(parentPath); File[] files = file.listFiles(); IndexReader[] readers = new IndexReader[files.length]; for (int i = 0 ; i < files.length ; i ++) { readers[i] = DirectoryReader.open(FSDirectory.open(Paths.get(files[i].getPath(), new String[0]))); } MultiReader multiReader = new MultiReader(readers); IndexSearcher searcher = new IndexSearcher(multiReader,service); return searcher; } /**根据索引路径获取IndexReader * @param indexPath * @return * @throws IOException */ public static DirectoryReader getIndexReader(String indexPath) throws IOException{ return DirectoryReader.open(FSDirectory.open(Paths.get(indexPath, new String[0]))); } /**根据索引路径获取IndexSearcher * @param indexPath * @param service * @return * @throws IOException */ public static IndexSearcher getIndexSearcherByIndexPath(String indexPath,ExecutorService service) throws IOException{ IndexReader reader = getIndexReader(indexPath); return new IndexSearcher(reader,service); } /**如果索引目录会有变更用此方法获取新的IndexSearcher这种方式会占用较少的资源 * @param oldSearcher * @param service * @return * @throws IOException */ public static IndexSearcher getIndexSearcherOpenIfChanged(IndexSearcher oldSearcher,ExecutorService service) throws IOException{ DirectoryReader reader = (DirectoryReader) oldSearcher.getIndexReader(); DirectoryReader newReader = DirectoryReader.openIfChanged(reader); return new IndexSearcher(newReader, service); } /**多条件查询类似于sql in * @param querys * @return */ public static Query getMultiQueryLikeSqlIn(Query ... querys){ BooleanQuery query = new BooleanQuery(); for (Query subQuery : querys) { query.add(subQuery,Occur.SHOULD); } return query; } /**多条件查询类似于sql and * @param querys * @return */ public static Query getMultiQueryLikeSqlAnd(Query ... querys){ BooleanQuery query = new BooleanQuery(); for (Query subQuery : querys) { query.add(subQuery,Occur.MUST); } return query; } /**从指定配置项中查询 * @return * @param analyzer 分词器 * @param field 字段 * @param fieldType 字段类型 * @param queryStr 查询条件 * @param range 是否区间查询 * @return */ public static Query getQuery(String field,String fieldType,String queryStr,boolean range){ Query q = null; try { if(queryStr != null && !"".equals(queryStr)){ if(range){ String[] strs = queryStr.split("\\|"); if("int".equals(fieldType)){ int min = new Integer(strs[0]); int max = new Integer(strs[1]); q = NumericRangeQuery.newIntRange(field, min, max, true, true); }else if("double".equals(fieldType)){ Double min = new Double(strs[0]); Double max = new Double(strs[1]); q = NumericRangeQuery.newDoubleRange(field, min, max, true, true); }else if("float".equals(fieldType)){ Float min = new Float(strs[0]); Float max = new Float(strs[1]); q = NumericRangeQuery.newFloatRange(field, min, max, true, true); }else if("long".equals(fieldType)){ Long min = new Long(strs[0]); Long max = new Long(strs[1]); q = NumericRangeQuery.newLongRange(field, min, max, true, true); } }else{ if("int".equals(fieldType)){ q = NumericRangeQuery.newIntRange(field, new Integer(queryStr), new Integer(queryStr), true, true); }else if("double".equals(fieldType)){ q = NumericRangeQuery.newDoubleRange(field, new Double(queryStr), new Double(queryStr), true, true); }else if("float".equals(fieldType)){ q = NumericRangeQuery.newFloatRange(field, new Float(queryStr), new Float(queryStr), true, true); }else{ Analyzer analyzer = new StandardAnalyzer(); q = new QueryParser(field, analyzer).parse(queryStr); } } }else{ q= new MatchAllDocsQuery(); } System.out.println(q); } catch (ParseException e) { // TODO Auto-generated catch block e.printStackTrace(); } return q; } /**根据field和值获取对应的内容 * @param fieldName * @param fieldValue * @return */ public static Query getQuery(String fieldName,Object fieldValue){ Term term = new Term(fieldName, new BytesRef(fieldValue.toString())); return new TermQuery(term); } /**根据IndexSearcher和docID获取默认的document * @param searcher * @param docID * @return * @throws IOException */ public static Document getDefaultFullDocument(IndexSearcher searcher,int docID) throws IOException{ return searcher.doc(docID); } /**根据IndexSearcher和docID * @param searcher * @param docID * @param listField * @return * @throws IOException */ public static Document getDocumentByListField(IndexSearcher searcher,int docID,Set<String> listField) throws IOException{ return searcher.doc(docID, listField); } /**分页查询 * @param page 当前页数 * @param perPage 每页显示条数 * @param searcher searcher查询器 * @param query 查询条件 * @return * @throws IOException */ public static TopDocs getScoreDocsByPerPage(int page,int perPage,IndexSearcher searcher,Query query) throws IOException{ TopDocs result = null; if(query == null){ System.out.println(" Query is null return null "); return null; } ScoreDoc before = null; if(page != 1){ TopDocs docsBefore = searcher.search(query, (page-1)*perPage); ScoreDoc[] scoreDocs = docsBefore.scoreDocs; if(scoreDocs.length > 0){ before = scoreDocs[scoreDocs.length - 1]; } } result = searcher.searchAfter(before, query, perPage); return result; } public static TopDocs getScoreDocs(IndexSearcher searcher,Query query) throws IOException{ TopDocs docs = searcher.search(query, getMaxDocId(searcher)); return docs; } /**高亮显示字段 * @param searcher * @param field * @param keyword * @param preTag * @param postTag * @param fragmentSize * @return * @throws IOException * @throws InvalidTokenOffsetsException */ public static String[] highlighter(IndexSearcher searcher,String field,String keyword,String preTag, String postTag,int fragmentSize) throws IOException, InvalidTokenOffsetsException{ Term term = new Term("content",new BytesRef("lucene")); TermQuery termQuery = new TermQuery(term); TopDocs docs = getScoreDocs(searcher, termQuery); ScoreDoc[] hits = docs.scoreDocs; QueryScorer scorer = new QueryScorer(termQuery); SimpleHTMLFormatter simpleHtmlFormatter = new SimpleHTMLFormatter(preTag,postTag);//设定高亮显示的格式<B>keyword</B>,此为默认的格式 Highlighter highlighter = new Highlighter(simpleHtmlFormatter,scorer); highlighter.setTextFragmenter(new SimpleFragmenter(fragmentSize));//设置每次返回的字符数 Analyzer analyzer = new StandardAnalyzer(); String[] result = new String[hits.length]; for (int i = 0; i < result.length ; i++) { Document doc = searcher.doc(hits[i].doc); result[i] = highlighter.getBestFragment(analyzer, field, doc.get(field)); } return result; } /**统计document的数量,此方法等同于matchAllDocsQuery查询 * @param searcher * @return */ public static int getMaxDocId(IndexSearcher searcher){ return searcher.getIndexReader().maxDoc(); } }时间不早了,明天会附上源码
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