前言
本章代码已分享至Gitee: https://gitee.com/lengcz/springbootlucene01
接上文。Lucene(1):Springboot整合全文检索引擎Lucene常规入门附源码
如何在指定范围内查询。从lucene 7 开始,filter 被弃用,导致无法进行调节过滤。
TermInSetQuery 指定集合条件过滤
如图,想要设定fromType为CSDN和小米,不需要查询其他来源的文字该怎么办?
前文提到的TermRangeQuery 属于数值范围的条件,这里显然不适用。
TermRangeQuery query2 = new TermRangeQuery("id", new BytesRef("1001".getBytes()), new BytesRef("1005".getBytes()), true, true);builder.add(query2, BooleanClause.Occur.MUST);
我们需要使用TermInSetQuery
List<BytesRef> bytesRefList = Arrays.asList(new BytesRef("CSDN".getBytes()),new BytesRef("小米".getBytes()));TermInSetQuery query3 = new TermInSetQuery("fromType",bytesRefList);builder.add(query3, BooleanClause.Occur.MUST);
多关键词在多字段中搜索
//多条件查询构造BooleanQuery.Builder builder = new BooleanQuery.Builder();// // 条件一
// MultiFieldQueryParser parser = new MultiFieldQueryParser(str, new IKAnalyzer());// 创建查询对象
// Query query = parser.parse(text);
// builder.add(query, BooleanClause.Occur.MUST);BooleanQuery.Builder builder2 = new BooleanQuery.Builder();//这里很重要,必须单独构建一个query,相当于预设一个括号,把几个关键词放到括号里for (String key : text.split(",")) {String fields[] = {"title", "description"};//在标题和描述中搜索String kws[] = {key, key};BooleanClause.Occur[] flags = new BooleanClause.Occur[]{BooleanClause.Occur.SHOULD, BooleanClause.Occur.SHOULD};Query queryKey = MultiFieldQueryParser.parse(kws, fields, flags, new IKAnalyzer()); //通常就是关键词搜索if (rule.equals("and")) { // and 或者 orbuilder2.add(queryKey, BooleanClause.Occur.MUST); //相当于各关键词之间的关系是AND} else {builder2.add(queryKey, BooleanClause.Occur.SHOULD); /// 相当于各关键词之间的关系是OR}}builder.add(builder2.build(), BooleanClause.Occur.MUST);
完整示例
/**** @param text 关键词,多关键词逗号分割* @param rule 规则, 多关键词之间的关系是and 还是or* @return* @throws IOException* @throws ParseException* @throws InvalidTokenOffsetsException*/@GetMapping("/searchTextMoreParam")public List<BlogTitle> searchTextMoreParam(String text,String rule) throws IOException, ParseException, InvalidTokenOffsetsException {String[] str = {"title", "description"};Directory directory = FSDirectory.open(FileSystems.getDefault().getPath("d:\\indexDir"));// 索引读取工具IndexReader reader = DirectoryReader.open(directory);// 索引搜索工具IndexSearcher searcher = new IndexSearcher(reader);//多条件查询构造BooleanQuery.Builder builder = new BooleanQuery.Builder();// // 条件一
// MultiFieldQueryParser parser = new MultiFieldQueryParser(str, new IKAnalyzer());// 创建查询对象
// Query query = parser.parse(text);
// builder.add(query, BooleanClause.Occur.MUST);BooleanQuery.Builder builder2 = new BooleanQuery.Builder();//这里很重要,必须单独构建一个query,相当于预设一个括号,把几个关键词放到括号里for (String key : text.split(",")) {String fields[] = {"title", "description"};String kws[] = {key, key};BooleanClause.Occur[] flags = new BooleanClause.Occur[]{BooleanClause.Occur.SHOULD, BooleanClause.Occur.SHOULD};Query queryKey = MultiFieldQueryParser.parse(kws, fields, flags, new IKAnalyzer()); //通常就是关键词搜索if (rule.equals("and")) { //builder2.add(queryKey, BooleanClause.Occur.MUST); //相当于各关键词之间的关系是AND} else {builder2.add(queryKey, BooleanClause.Occur.SHOULD); /// 相当于各关键词之间的关系是OR}}builder.add(builder2.build(), BooleanClause.Occur.MUST);// 条件二// TermQuery不使用分析器所以建议匹配不分词的Field域(StringField, )查询,比如价格、分类ID号等。这里只能演示个ID了。。。
// Query termQuery = new TermQuery(new Term("id", "1001"));
// builder.add(termQuery, BooleanClause.Occur.MUST);// TermRangeQuery query2 = new TermRangeQuery("id", new BytesRef("1001".getBytes()), new BytesRef("1005".getBytes()), true, true);
// builder.add(query2, BooleanClause.Occur.MUST);List<BytesRef> bytesRefList = Arrays.asList(new BytesRef("CSDN".getBytes()),new BytesRef("小米".getBytes()));TermInSetQuery query3 = new TermInSetQuery("fromType",bytesRefList);builder.add(query3, BooleanClause.Occur.MUST);// 获取前十条记录TopDocs topDocs = searcher.search(builder.build(), 100);// 获取总条数log.info("本次搜索共找到" + topDocs.totalHits + "条数据");//高亮显示SimpleHTMLFormatter simpleHTMLFormatter = new SimpleHTMLFormatter("<span style='color:red'>", "</span>");Highlighter highlighter = new Highlighter(simpleHTMLFormatter, new QueryScorer(builder2.build()));//高亮只是关键词,其他属于过滤条件//高亮后的段落范围在100字内Fragmenter fragmenter = new SimpleFragmenter(100);highlighter.setTextFragmenter(fragmenter);// 获取得分文档对象(ScoreDoc)数组.SocreDoc中包含:文档的编号、文档的得分ScoreDoc[] scoreDocs = topDocs.scoreDocs;List<BlogTitle> list = new ArrayList<>();for (ScoreDoc scoreDoc : scoreDocs) {// 取出文档编号int docId = scoreDoc.doc;// 根据编号去找文档Document doc = reader.document(docId);BlogTitle content = selectById(doc.get("id"));//处理高亮字段显示String title = highlighter.getBestFragment(new IKAnalyzer(), "title", doc.get("title"));if (title == null) {title = content.getTitle();}String description = highlighter.getBestFragment(new IKAnalyzer(), "description", content.getDescription());content.setDescription(description);content.setTitle(title);list.add(content);}return list;}