lucene 查询示例
排序
Lucene默认按照相关度(score)排序,为了能支持其他的排序方式,比如日期,我们在add Field的时候,必须保证field被Index且不能被tokenized(分词),并且排序的只能是数字,日期,字符三种类型之一
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实体类
public class Article {
? private String id;
? private String title;
? private String keyWords;
? private String content;
? private int order;
????????????? 省略set..get 方法
}
?组织数据
import java.util.ArrayList;import java.util.List;import com.company.project.entity.Article;public class DATAUTIls {public static List<Article> luceneDatas = new ArrayList<Article>();static {Article a1 = new Article();a1.setContent("我们都是中国人" );a1.setId("1");a1.setTitle("法眼看中国是怎么样的一个中国" ) ;//有两个中国a1.setKeyWords("中国，中国，中国") ;a1.setOrder(1);Article a2 = new Article();a2.setContent("我们是两个中国 中国" );a2.setId("2");a2.setTitle("法眼看中国是怎么样的一个中国 中国" ) ;//有两个中国a2.setKeyWords("中国，中国") ;a2.setOrder(2);Article a3 = new Article();a3.setContent("我们都是中国人" );a3.setId("3");a3.setTitle("法眼看怎么样的一个中国" ) ;//有两个中国a3.setKeyWords("中国 ") ;a3.setOrder(3);Article a4 = new Article();a4.setContent("我们都是国中人" );a4.setId("4");a4.setTitle("法眼看" ) ;//有两个中国a4.setKeyWords("无") ;a4.setOrder(4);luceneDatas.add(a1);luceneDatas.add(a3);luceneDatas.add(a2);luceneDatas.add(a4);}}??
建造索引
import java.io.File;import java.io.IOException;import java.util.List;import org.apache.lucene.analysis.Analyzer;import org.apache.lucene.analysis.standard.StandardAnalyzer;import org.apache.lucene.document.Document;import org.apache.lucene.document.Field;import org.apache.lucene.index.IndexWriter;import org.apache.lucene.index.IndexWriterConfig;import org.apache.lucene.index.IndexWriterConfig.OpenMode;import org.apache.lucene.store.Directory;import org.apache.lucene.store.FSDirectory;import org.apache.lucene.store.NRTCachingDirectory;import org.apache.lucene.util.Version;import com.company.project.entity.Article;public class IndexRunner { private String INDEX_STORe_PATH = "D:\\workplace\\company\\mylucene\\indexstore"; public IndexRunner(){}; public IndexRunner(String index_path) { this.INDEX_STORe_PATH = index_path; File dir = new File(index_path); if(dir.exists()) { dir.mkdir(); } } //创建索引 public void createIndex(List<Article> datas,boolean isCreate) throws IOException { //待创建得文档目录 Directory dir = FSDirectory.open(new File(INDEX_STORe_PATH)); //选择得分词工具 Analyzer analyzer = new StandardAnalyzer(Version.LUCENE_34); //建立索引的配置类，包含了一个解析器 IndexWriterConfig iwc = new IndexWriterConfig(Version.LUCENE_34, analyzer); //设置我们的解析器是新建还是追加更新 if(isCreate){ iwc.setOpenMode(OpenMode.CREATE);//每次建立都覆盖原来的索引 } else{ iwc.setOpenMode(OpenMode.CREATE_OR_APPEND);//每次都追加更新 } NRTCachingDirectory cachedFSDir = new NRTCachingDirectory(dir, 5.0, 60.0); iwc.setMergeScheduler(cachedFSDir.getMergeScheduler()); //索引的建立类 第一个参数索引的存放位置，第二个参数索引的配置对象 IndexWriter writer = new IndexWriter(dir, iwc); for(int i=0;i<datas.size();i++) { Article article = datas.get(i ); /* * Field.Store.YES:存储字段值（未分词前的字段值） Field.Store.NO:不存储,存储与索引没有关系 * Field.Store.COMPRESS:压缩存储,用于长文本或二进制，但性能受损 Field.Index.ANALYZED:分词建索引 * Field.Index.ANALYZED_NO_NORMS:分词建索引，但是Field的值不像通常那样被保存，而是只取一个byte，这样节约存储空间 * Field.Index.NOT_ANALYZED:不分词且索引 * Field.Index.NOT_ANALYZED_NO_NORMS:不分词建索引，Field的值去一个byte保存 */ Field f0 = new Field("title", article.getTitle(), Field.Store.YES, Field.Index.ANALYZED); Field f1 = new Field("content",article.getContent(),Field.Store.YES,Field.Index.ANALYZED); Field f2 = new Field("order",String.valueOf(article.getOrder()),Field.Store.YES,Field.Index.NOT_ANALYZED); Field f3 = new Field("id",String.valueOf(article.getId()),Field.Store.YES,Field.Index.NOT_ANALYZED); Document doc = new Document(); doc.add(f0) ; doc.add(f1); doc.add(f2); doc.add(f3); writer.addDocument(doc); } //这个方法在新增索引的情况会很有用，就是讲原来散落的索引文件重新进行整理合并！ // writer.forceMerge(1); writer.close(); System.out.println("索引创建成功"); } public static void main(String[] args) { IndexRunner indexRunner = new IndexRunner(); try { indexRunner.createIndex(DATAUTIls.luceneDatas,true); } catch (IOException e) { // TODO Auto-generated catch block e.printStackTrace(); } }}?
查询
此处有三种查询，一种是多字段查询一个关键字， 一种是多字段组合查询，还有一种是分页查询
import java.io.File;import java.io.IOException;import java.io.StringReader;import java.util.ArrayList;import java.util.HashMap;import java.util.List;import java.util.Map;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.CorruptIndexException;import org.apache.lucene.index.IndexReader;import org.apache.lucene.queryParser.ParseException;import org.apache.lucene.queryParser.QueryParser;import org.apache.lucene.search.Filter;import org.apache.lucene.search.IndexSearcher;import org.apache.lucene.search.Query;import org.apache.lucene.search.ScoreDoc;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.SimpleHTMLFormatter;import org.apache.lucene.store.FSDirectory;import org.apache.lucene.util.Version;import com.company.project.entity.Article;public class SearchRunner { private static String PATH = "D:\\workplace\\company\\mylucene\\indexstore"; public static void main(String [] arg) throws Exception{ String[] queryFileds = { "title", "content" }; String queryString = "中国"; //SearchRunner.searchList(queryFileds, queryString ); // SearchRunner.combinationSearch(); SearchRunner.pagingSearch("中", null); } /** * 在多个字段查找同一个值 */ public static void searchList(String[] queryFileds,String queryString) throws Exception { // 查询的字符串:输入不存在的字符串是查询不到的,如：中国 IndexReader reader = IndexReader.open(FSDirectory.open(new File(PATH))); IndexSearcher searcher = new IndexSearcher(reader); Query query = LuceneUtils.createQuery(queryFileds, queryString); // 在搜索器中进行查询 // 对查询内容进行过滤 Filter filter = null; // 一次在索引器查询多少条数据 int queryCount = 100; TopDocs results = searcher.search(query, filter, queryCount); System.out.println("总符合: " + results.totalHits + "条数！"); // 显示记录 for (ScoreDoc sr : results.scoreDocs) { // 文档编号 int docID = sr.doc; // 真正的内容 Document doc = searcher.doc(docID); System.out.println("inof = " + doc.get("title")); System.out.println("info2 = " + doc.get("content")); } } public static void combinationSearch() throws CorruptIndexException, IOException, ParseException{ IndexReader reader = IndexReader.open(FSDirectory.open(new File(PATH))); IndexSearcher searcher = new IndexSearcher(reader);//选择得分词工具 Analyzer analyzer = new StandardAnalyzer(Version.LUCENE_34); QueryParser parser = new QueryParser(Version.LUCENE_34, "content", analyzer); //注意此处AND一定要大写 Query query = parser.parse("content:中 国 AND title:中 国"); // 一次在索引器查询多少条数据 int queryCount = 100;// Sort sort = new Sort(new SortField("order",SortField.DOUBLE,false)); //排序 false 升序 true降序 //TopDocs results = searcher.search(query, queryCount,sort); TopDocs results = searcher.search(query, queryCount); System.out.println("总符合: " + results.totalHits + "条数！"); // 显示记录 for (ScoreDoc sr : results.scoreDocs) { //Sort(field,true) // 文档编号 int docID = sr.doc; // 真正的内容 Document doc = searcher.doc(docID); System.out.println("id="+doc.get("id")+"\torder="+doc.get("order")+"\ttitle = " + doc.get("title")+"\tcontent = " + doc.get("content")); } }//分页查询 public static Map pagingSearch(String title,String content) throws CorruptIndexException, IOException, ParseException, InvalidTokenOffsetsException{ Map pager = new HashMap(); List<Article> blogList=new ArrayList<Article>() ; TokenStream tokenStream=null; Analyzer analyzer = new StandardAnalyzer(Version.LUCENE_34); //获取IndexSearcher 对象 IndexReader reader = IndexReader.open(FSDirectory.open(new File(PATH))); IndexSearcher indexSearch = new IndexSearcher(reader); QueryParser queryParser = new QueryParser(Version.LUCENE_34, "content", analyzer); //搜索条件的结合 String str=""; if(title!=null &&title.length()>0){ str="title:"+title; } if(content!=null &&content.length()>0){ if(str.trim().length()>0) { str +=" AND"; } str="content:"+content; } //设置搜索条件 Query query=queryParser.parse(str); //查询搜索引擎 TopDocs result = indexSearch.search(query, 10); //上一页的最后一个document索引 第一页为0,其余也该页的起始记录条数 int index=2; ScoreDoc scoreDoc=null; //如果当前页是第一页面scoreDoc=null。 if(index>0){ //因为索引是从0开始所以要index-1 scoreDoc=result.scoreDocs[index-1]; } //分页处理 int pageSize = 2; TopDocs hits= indexSearch.searchAfter(scoreDoc, query, pageSize); //设置分页的总记录数 //循环hits.scoreDocs数据，并使用indexSearch.doc方法把Document还原，再拿出对应的字段的值 for (int i = 0; i < hits.scoreDocs.length; i++) { ScoreDoc sdoc = hits.scoreDocs[i]; Document doc = indexSearch.doc(sdoc.doc); Article article = new Article(); String stitle = doc.get("title"); String scontent = doc.get("content"); String id = doc.get("id"); //加亮处理 SimpleHTMLFormatter simplehtml=new SimpleHTMLFormatter("<font color='red'>", "</font>"); Highlighter highlighter = new Highlighter(simplehtml,new QueryScorer(query)); if(title!=null){ tokenStream = analyzer.tokenStream("title",new StringReader(title)); String highLightText = highlighter.getBestFragment(tokenStream, title); article.setTitle(highLightText==null?title:highLightText); }else { article.setTitle(stitle); } if(content!=null){ tokenStream = analyzer.tokenStream("content",new StringReader(content)); String highLightText = highlighter.getBestFragment(tokenStream, content); article.setContent(highLightText==null?title:highLightText); }else { article.setContent(scontent); } article.setId(id); System.out.println(article); blogList.add(article); } pager.put("content",hits.totalHits); pager.put("data",blogList); return pager; }}?
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