package junit;

import java.io.File;
import java.io.IOException;
import java.text.ParseException;
import java.util.ArrayList;
import java.util.List;

import org.apache.commons.lang.math.NumberUtils;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
import org.apache.lucene.document.NumericField;
 
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.Term;
import org.apache.lucene.queryParser.MultiFieldQueryParser;
import org.apache.lucene.search.BooleanClause;
import org.apache.lucene.search.BooleanQuery;
import org.apache.lucene.search.Filter;
import org.apache.lucene.search.FuzzyQuery;
 
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.MultiPhraseQuery;
import org.apache.lucene.search.NumericRangeFilter;
import org.apache.lucene.search.PhraseQuery;
import org.apache.lucene.search.PrefixQuery;
import org.apache.lucene.search.Query;
import org.apache.lucene.search.ScoreDoc;
 
import org.apache.lucene.search.TermQuery;
import org.apache.lucene.search.TermRangeQuery;
import org.apache.lucene.search.TopDocs;
import org.apache.lucene.search.WildcardQuery;
import org.apache.lucene.search.highlight.Formatter;
import org.apache.lucene.search.highlight.Fragmenter;
import org.apache.lucene.search.highlight.Highlighter;
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.search.regex.RegexQuery;
import org.apache.lucene.store.FSDirectory;
import org.apache.lucene.util.Version;
import org.junit.Test;
import org.wltea.analyzer.lucene.IKAnalyzer;

import com.ljq.entity.Person;
import com.ljq.utils.Consts;
import com.ljq.utils.DateUtils;
import com.ljq.utils.LuceneUtil;
import com.ljq.utils.XMLPropertyConfig;

/**   
 * Lucene搜尋方式大合集<br/><br/>
 * 
 * Lucene搜尋種類很多。這裡就介紹幾個最常用的。其中TermQuery\BooleanQuery\RegexQuery功能最強大，最為常用。
 *
 * @author 林計欽
 * @version 1.0 2013-6-7 上午09:34:08   
 */
public class IndexQueryTest {
    
    /**
     * 詞條搜尋(單個關鍵字查詢)<br/><br/>
     * 
     * 主要物件是TermQuery，呼叫方式如下：<br/>
     * Term term=new Term(欄位名, 搜尋關鍵字);<br/>
     * Query query=new TermQuery(term);<br/>
     * Hits hits=searcher.search(query);<br/>
     * @throws Exception
     */
    @Test
    public void termQuery() throws Exception {
        IndexReader reader = IndexReader.open(FSDirectory.open(new File(XMLPropertyConfig.getConfigXML().getString("index_path"))), true);
        IndexSearcher searcher = new IndexSearcher(reader);
        
        //Term term=new Term("ids", "1");
        //Term term=new Term("ages", "20");
        //Term term=new Term("birthdays", "2008-06-12");
        //Term term=new Term("name", "張三");
        Term term=new Term("city", "廈門");
        
        Query query=new TermQuery(term);
        TopDocs topDocs=searcher.search(query, 1000);
        System.out.println("共檢索出 " + topDocs.totalHits + " 條記錄");
        System.out.println();
        
        ScoreDoc[] scoreDocs = topDocs.scoreDocs;
        for (ScoreDoc scDoc : scoreDocs) {
            Document document = searcher.doc(scDoc.doc);
            String id = document.get("id");
            String name = document.get("name");
            String age = document.get("age");
            String city = document.get("city");
            String birthday = document.get("birthday");
            float score = scDoc.score; //相似度
            
            System.out.println(String.format("id:%s, name:%s, age:%s, city:%s, birthday:%s, 相關度:%s.", 
                    id, name, age, city, DateUtils.longToString(Long.parseLong(birthday), Consts.FORMAT_SHORT), score));
        }
        
        searcher.close();
        reader.close();
    }
    
    /**
     * 組合搜尋(允許多個關鍵字組合搜尋)<br/><br/>
     * 
     * 主要物件是BooleanQuery，呼叫方式如下：<br/>
     * Term term1=new Term(欄位名, 搜尋關鍵字);<br/>
     * TermQuery query1=new TermQuery(term1);<br/><br/>
     * 
     * Term term2=new Term(欄位名, 搜尋關鍵字);<br/>
     * TermQuery query2=new TermQuery(term2);<br/><br/>
     * 
     * BooleanQuery booleanQuery=new BooleanQuery();<br/>
     * booleanQuery.add(query1, 引數);<br/>
     * booleanQuery.add(query2, 引數);<br/><br/>
     * 
     * Hits hits=searcher.search(booleanquery);<br/>
     * 此方法中的核心在BooleanQuery的add方法上，其第二個引數有三個可選值，對應著邏輯上的與或非關係。<br/><br/>
     * 
     * 引數如下：<br/>
     * BooleanClause.Occur.MUST：必須包含，類似於邏輯運算的與<br/>
     * BooleanClause.Occur.MUST_NOT：必須不包含，類似於邏輯運算的非<br/>
     * BooleanClause.Occur.SHOULD：可以包含，類似於邏輯運算的或<br/>
     * 這三者組合，妙用無窮。<br/>
     * @throws Exception
     */
    @Test
    public void booleanQuery() throws Exception {
        IndexReader reader = IndexReader.open(FSDirectory.open(new File(XMLPropertyConfig.getConfigXML().getString("index_path"))), true);
        IndexSearcher searcher = new IndexSearcher(reader);
        
        //組合條件：
        //年齡(或)：10、20、30、40
        //名字(與): 四
        //城市(非): 莆田
        TermQuery ageQuery10=new TermQuery(new Term("ages", "10"));
        TermQuery ageQuery20=new TermQuery(new Term("ages", "20"));
        TermQuery ageQuery30=new TermQuery(new Term("ages", "30"));
        TermQuery ageQuery40=new TermQuery(new Term("ages", "40"));
        
        TermQuery nameQuery=new TermQuery(new Term("name", "四"));
        
        TermQuery cityQuery=new TermQuery(new Term("city", "莆田"));
        
        BooleanQuery booleanQuery=new BooleanQuery();
        booleanQuery.add(ageQuery10, BooleanClause.Occur.SHOULD);
        booleanQuery.add(ageQuery20, BooleanClause.Occur.SHOULD);
        booleanQuery.add(ageQuery30, BooleanClause.Occur.SHOULD);
        booleanQuery.add(ageQuery40, BooleanClause.Occur.SHOULD);
        booleanQuery.add(nameQuery, BooleanClause.Occur.MUST);
        booleanQuery.add(cityQuery, BooleanClause.Occur.MUST_NOT); 
        
        TopDocs topDocs=searcher.search(booleanQuery, 1000);
        System.out.println("共檢索出 " + topDocs.totalHits + " 條記錄");
        System.out.println();
        
        ScoreDoc[] scoreDocs = topDocs.scoreDocs;
        for (ScoreDoc scDoc : scoreDocs) {
            Document document = searcher.doc(scDoc.doc);
            String id = document.get("id");
            String name = document.get("name");
            String age = document.get("age");
            String city = document.get("city");
            String birthday = document.get("birthday");
            float score = scDoc.score; //相似度
            
            System.out.println(String.format("id:%s, name:%s, age:%s, city:%s, birthday:%s, 相關度:%s.", 
                    id, name, age, city, DateUtils.longToString(Long.parseLong(birthday), Consts.FORMAT_SHORT), score));
        }
        
        searcher.close();
        reader.close();
    }
    
    /**
     * 範圍搜尋(允許搜尋指定範圍內的關鍵字結果)<br/><br/>
     * 
     * 主要物件是TermRangeQuery，呼叫方式如下：<br/>
     * TermRangeQuery rangequery=new TermRangeQuery(欄位名, 起始值, 終止值, 起始值是否包含邊界, 終止值是否包含邊界); <br/><br/>
     * 
     * Hits hits=searcher.search(rangequery);<br/>
     * 此方法中的引數是Boolean型別的，表示是否包含邊界 。<br/>
     * true 包含邊界<br/>
     * false不包含邊界<br/>
     * @throws Exception
     */
    @Test
    public void rangeQuery() throws Exception {
        IndexReader reader = IndexReader.open(FSDirectory.open(new File(XMLPropertyConfig.getConfigXML().getString("index_path"))), true);
        IndexSearcher searcher = new IndexSearcher(reader);
        
        TermRangeQuery idQuery=new TermRangeQuery("ids", "1", "3", true, true);  
        TermRangeQuery ageQuery=new TermRangeQuery("ages", "10", "30", true, true);  
        TermRangeQuery timeQuery=new TermRangeQuery("birthdays", "2011-03-09", "2013-01-07", true, true);
        
        TopDocs topDocs=searcher.search(timeQuery, 1000);
        System.out.println("共檢索出 " + topDocs.totalHits + " 條記錄");
        System.out.println();
        
        ScoreDoc[] scoreDocs = topDocs.scoreDocs;
        for (ScoreDoc scDoc : scoreDocs) {
            Document document = searcher.doc(scDoc.doc);
            String id = document.get("id");
            String name = document.get("name");
            String age = document.get("age");
            String city = document.get("city");
            String birthday = document.get("birthday");
            float score = scDoc.score; //相似度
            
            System.out.println(String.format("id:%s, name:%s, age:%s, city:%s, birthday:%s, 相關度:%s.", 
                    id, name, age, city, DateUtils.longToString(Long.parseLong(birthday), Consts.FORMAT_SHORT), score));
        }
        
        searcher.close();
        reader.close();
    }
    
    /**
     * 字首搜尋(搜尋起始位置符合要求的結果)<br/><br/>
     * 
     * 主要物件是PrefixQuery，呼叫方式如下：<br/>
     * Term term=new Term(欄位名, 搜尋關鍵字);<br/>
     * PrefixQuery prefixquery=new PrefixQuery(term);<br/>
     * Hits hits=searcher.search(prefixquery);<br/>
     * 
     * @throws Exception
     */
    @Test
    public void prefixQuery() throws Exception {
        IndexReader reader = IndexReader.open(FSDirectory.open(new File(XMLPropertyConfig.getConfigXML().getString("index_path"))), true);
        IndexSearcher searcher = new IndexSearcher(reader);
        
        Term term=new Term("name", "王"); 
        PrefixQuery prefixquery=new PrefixQuery(term);
        
        TopDocs topDocs=searcher.search(prefixquery, 1000);
        System.out.println("共檢索出 " + topDocs.totalHits + " 條記錄");
        System.out.println();
        
        ScoreDoc[] scoreDocs = topDocs.scoreDocs;
        for (ScoreDoc scDoc : scoreDocs) {
            Document document = searcher.doc(scDoc.doc);
            String id = document.get("id");
            String name = document.get("name");
            String age = document.get("age");
            String city = document.get("city");
            String birthday = document.get("birthday");
            float score = scDoc.score; //相似度
            
            System.out.println(String.format("id:%s, name:%s, age:%s, city:%s, birthday:%s, 相關度:%s.", 
                    id, name, age, city, DateUtils.longToString(Long.parseLong(birthday), Consts.FORMAT_SHORT), score));
        }
        
        searcher.close();
        reader.close();
    }
    
    /**
     * 短語搜尋(根據零碎的短語組合成新的片語進行搜尋)<br/><br/>
     * 
     * 主要物件是PhraseQuery，呼叫方式如下：<br/>
     * Term term1=new Term(欄位名, 搜尋關鍵字);<br/>
     * Term term2=new Term(欄位名, 搜尋關鍵字);<br/><br/>
     * 
     * PhraseQuery phrasequery=new PhraseQuery();<br/>
     * phrasequery.setSlop(引數);<br/>
     * phrasequery.add(term1);<br/>
     * phrasequery.add(term2);<br/>
     * Hits hits=searcher.search(phrasequery);<br/>
     * 其中setSlop的引數是設定兩個關鍵字之間允許間隔的最大值。<br/>
     * @throws Exception
     */
    @Test
    public void phraseQuery() throws Exception {
        IndexReader reader = IndexReader.open(FSDirectory.open(new File(XMLPropertyConfig.getConfigXML().getString("index_path"))), true);
        IndexSearcher searcher = new IndexSearcher(reader);
        
        Term term1=new Term("name", "林"); 
        Term term2=new Term("name", "欽"); 
        
        PhraseQuery phrasequery=new PhraseQuery(); 
        phrasequery.setSlop(100); 
        phrasequery.add(term1); 
        phrasequery.add(term2); 
        
        TopDocs topDocs=searcher.search(phrasequery, 1000);
        System.out.println("共檢索出 " + topDocs.totalHits + " 條記錄");
        System.out.println();
        
        ScoreDoc[] scoreDocs = topDocs.scoreDocs;
        for (ScoreDoc scDoc : scoreDocs) {
            Document document = searcher.doc(scDoc.doc);
            String id = document.get("id");
            String name = document.get("name");
            String age = document.get("age");
            String city = document.get("city");
            String birthday = document.get("birthday");
            float score = scDoc.score; //相似度
            
            System.out.println(String.format("id:%s, name:%s, age:%s, city:%s, birthday:%s, 相關度:%s.", 
                    id, name, age, city, DateUtils.longToString(Long.parseLong(birthday), Consts.FORMAT_SHORT), score));
        }
        
        searcher.close();
        reader.close();
    }
    
    /**
     * 多短語搜尋(先指定一個字首關鍵字，然後其他的關鍵字加在此關鍵字之後，組成詞語進行搜尋)<br/><br/>
     * 
     * 主要物件是MultiPhraseQuery，呼叫方式如下：<br/>
     * 
     * Term term=new Term(欄位名,前置關鍵字);<br/>
     * Term term1=new Term(欄位名,搜尋關鍵字);<br/>
     * Term term2=new Term(欄位名,搜尋關鍵字);<br/><br/>
     * 
     * MultiPhraseQuery multiPhraseQuery=new MultiPhraseQuery();<br/><br/>
     * 
     * multiPhraseQuery.add(term);<br/>
     * multiPhraseQuery.add(new Term[]{term1, term2});<br/><br/>
     * 
     * Hits hits=searcher.search(multiPhraseQuery);<br/>
     * @throws Exception
     */
    @Test
    public void multiPhraseQuery() throws Exception {
        IndexReader reader = IndexReader.open(FSDirectory.open(new File(XMLPropertyConfig.getConfigXML().getString("index_path"))), true);
        IndexSearcher searcher = new IndexSearcher(reader);
        
        //查詢“計張”、“計欽”組合的關鍵詞，先指定一個字首關鍵字，然後其他的關鍵字加在此關鍵字之後，組成詞語進行搜尋
        Term term=new Term("name", "計"); //前置關鍵字
        Term term1=new Term("name", "張"); //搜尋關鍵字
        Term term2=new Term("name", "欽"); //搜尋關鍵字
        
        MultiPhraseQuery multiPhraseQuery=new MultiPhraseQuery();
        multiPhraseQuery.add(term);
        multiPhraseQuery.add(new Term[]{term1, term2});
        
        
        TopDocs topDocs=searcher.search(multiPhraseQuery, 1000);
        System.out.println("共檢索出 " + topDocs.totalHits + " 條記錄");
        System.out.println();
        
        ScoreDoc[] scoreDocs = topDocs.scoreDocs;
        for (ScoreDoc scDoc : scoreDocs) {
            Document document = searcher.doc(scDoc.doc);
            String id = document.get("id");
            String name = document.get("name");
            String age = document.get("age");
            String city = document.get("city");
            String birthday = document.get("birthday");
            float score = scDoc.score; //相似度
            
            System.out.println(String.format("id:%s, name:%s, age:%s, city:%s, birthday:%s, 相關度:%s.", 
                    id, name, age, city, DateUtils.longToString(Long.parseLong(birthday), Consts.FORMAT_SHORT), score));
        }
        
        searcher.close();
        reader.close();
    }
    
    /**
     * 模糊搜尋(顧名思義)<br/><br/>
     *
     * 主要物件是FuzzyQuery，呼叫方式如下：<br/><br/>
     *
     * Term term=new Term(欄位名, 搜尋關鍵字);<br/>
     * FuzzyQuery fuzzyquery=new FuzzyQuery(term,引數);<br/>
     * Hits hits=searcher.search(fuzzyquery);<br/>
     * 此中的引數是表示模糊度，是小於1的浮點小數，比如0.5f
     * @throws Exception
     */
    @Test
    public void fuzzyQuery() throws Exception {
        IndexReader reader = IndexReader.open(FSDirectory.open(new File(XMLPropertyConfig.getConfigXML().getString("index_path"))), true);
        IndexSearcher searcher = new IndexSearcher(reader);
        
        Term term=new Term("name", "三張");
        FuzzyQuery fuzzyquery=new FuzzyQuery(term, 0.5f); 
        
        TopDocs topDocs=searcher.search(fuzzyquery, 1000);
        System.out.println("共檢索出 " + topDocs.totalHits + " 條記錄");
        System.out.println();
        
        ScoreDoc[] scoreDocs = topDocs.scoreDocs;
        for (ScoreDoc scDoc : scoreDocs) {
            Document document = searcher.doc(scDoc.doc);
            String id = document.get("id");
            String name = document.get("name");
            String age = document.get("age");
            String city = document.get("city");
            String birthday = document.get("birthday");
            float score = scDoc.score; //相似度
            
            System.out.println(String.format("id:%s, name:%s, age:%s, city:%s, birthday:%s, 相關度:%s.", 
                    id, name, age, city, DateUtils.longToString(Long.parseLong(birthday), Consts.FORMAT_SHORT), score));
        }
        
        searcher.close();
        reader.close();
    }

    /**
     * 萬用字元搜尋（顧名思義）<br/><br/>
     * 
     * 主要物件是：WildcardQuery，呼叫方式如下：<br/><br/>
     * 
     * Term term=new Term(欄位名,搜尋關鍵字+萬用字元);<br/>
     * WildcardQuery wildcardquery=new WildcardQuery(term);<br/>
     * Hits hits=searcher.search(wildcardquery);<br/><br/>
     * 
     * 其中的萬用字元分兩種，即*和？<br/>
     * * 表示任意多的自負<br/>
     * ？表示任意一個字元
     * @throws Exception
     */
    @Test
    public void wildcardQuery() throws Exception {
        IndexReader reader = IndexReader.open(FSDirectory.open(new File(XMLPropertyConfig.getConfigXML().getString("index_path"))), true);
        IndexSearcher searcher = new IndexSearcher(reader);
        
        Term term=new Term("name", "三?");
        WildcardQuery wildcardQuery=new WildcardQuery(term);

        TopDocs topDocs=searcher.search(wildcardQuery, 1000);
        System.out.println("共檢索出 " + topDocs.totalHits + " 條記錄");
        System.out.println();
        
        ScoreDoc[] scoreDocs = topDocs.scoreDocs;
        for (ScoreDoc scDoc : scoreDocs) {
            Document document = searcher.doc(scDoc.doc);
            String id = document.get("id");
            String name = document.get("name");
            String age = document.get("age");
            String city = document.get("city");
            String birthday = document.get("birthday");
            float score = scDoc.score; //相似度
            
            System.out.println(String.format("id:%s, name:%s, age:%s, city:%s, birthday:%s, 相關度:%s.", 
                    id, name, age, city, DateUtils.longToString(Long.parseLong(birthday), Consts.FORMAT_SHORT), score));
        }
        
        searcher.close();
        reader.close();
    }
    
    /**
     * 正則表示式搜尋（顧名思義，這個類引入lucene-queries-3.5.0.jar包）<br/><br/>
     * 
     * 主要物件是：RegexQuery，呼叫方式如下 <br/>
     * String regex = ".*"; <br/>
     * Term term = new Term (search_field_name, regex); <br/>
     * RegexQuery query = new RegexQuery (term); <br/>
     * TopDocs hits = searcher.search (query, 100); <br/>
     * @throws Exception
     */
    @Test
    public void regexQuery() throws Exception {
        IndexReader reader = IndexReader.open(FSDirectory.open(new File(XMLPropertyConfig.getConfigXML().getString("index_path"))), true);
        IndexSearcher searcher = new IndexSearcher(reader);
         
        String regex = "林*"; 
        Term term=new Term("name", regex);
        RegexQuery query = new RegexQuery(term);
        
        TopDocs topDocs=searcher.search(query, 1000);
        System.out.println("共檢索出 " + topDocs.totalHits + " 條記錄");
        System.out.println();
        
        ScoreDoc[] scoreDocs = topDocs.scoreDocs;
        for (ScoreDoc scDoc : scoreDocs) {
            Document document = searcher.doc(scDoc.doc);
            String id = document.get("id");
            String name = document.get("name");
            String age = document.get("age");
            String city = document.get("city");
            String birthday = document.get("birthday");
            float score = scDoc.score; //相似度
            
            System.out.println(String.format("id:%s, name:%s, age:%s, city:%s, birthday:%s, 相關度:%s.", 
                    id, name, age, city, DateUtils.longToString(Long.parseLong(birthday), Consts.FORMAT_SHORT), score));
        }
        
        searcher.close();
        reader.close();
    }

    /**
     * 數值範圍過濾器，如：int、long、float型別等
     * 
     * @throws Exception
     */
    @Test
    public void numericFilter() throws Exception{ //CustomScoreQuery
        //Filter filter = NumericRangeFilter.newLongRange("id", 1l, 3l, true, true);
        Filter filter = NumericRangeFilter.newIntRange("age", 1, 39, true, true);
        List<Person> persons=search(filter, new String[]{"name","city"}, "廈門");
        for(Person person : persons){
            System.out.println(String.format("id:%s, name:%s, age:%s, city:%s, birthday:%s.", 
                    person.getId(), person.getName(), person.getAge(), person.getCity(), DateUtils.dateToString(person.getBirthday(), Consts.FORMAT_SHORT)));
        }
    }
    
    /**
     * 時間範圍過濾器
     * @throws Exception 
     */
    @Test
    public void dateFilter() throws Exception{
        //2008-06-12
        long min=DateUtils.stringToDate("2008-06-12", Consts.FORMAT_SHORT).getTime();
        //2013-01-07
        long max=DateUtils.stringToDate("2013-01-07", Consts.FORMAT_SHORT).getTime();
        Filter filter = NumericRangeFilter.newLongRange("birthday", min, max, true, true);
        List<Person> persons=search(filter, new String[]{"name","city"}, "廈門");
        for(Person person : persons){
            System.out.println(String.format("id:%s, name:%s, age:%s, city:%s, birthday:%s.", 
                    person.getId(), person.getName(), person.getAge(), person.getCity(), DateUtils.dateToString(person.getBirthday(), Consts.FORMAT_SHORT)));
        }
    }
    
    /**
     * 建立索引
     * 
     * @throws Exception
     */
    @Test
    public void createIndex() throws Exception {
        List<Document> docs = new ArrayList<Document>();
        for (Person person : getPersons()) {
            Document doc = new Document();
            //宣告為NumericField的欄位，只能用NumericRangeFilter物件範圍查詢，不能用作關鍵字查詢。
            //NumericField不推薦，統一用Field
            doc.add(new NumericField("id", Field.Store.YES, true).setLongValue(person.getId()));
            doc.add(new NumericField("age", Field.Store.YES, true).setIntValue(person.getAge()));
            doc.add(new NumericField("birthday", Field.Store.YES, true).setLongValue(person.getBirthday().getTime()));
            
            doc.add(new Field("ids", person.getId()+"", Field.Store.YES, Field.Index.NOT_ANALYZED));
            doc.add(new Field("ages", person.getAge()+"", Field.Store.YES, Field.Index.NOT_ANALYZED));
            doc.add(new Field("birthdays", DateUtils.dateToString(person.getBirthday(), Consts.FORMAT_SHORT), 
                    Field.Store.YES, Field.Index.NOT_ANALYZED));
            doc.add(new Field("name", person.getName(), Field.Store.YES, Field.Index.ANALYZED));
            doc.add(new Field("city", person.getCity(), Field.Store.YES, Field.Index.ANALYZED));
            
            docs.add(doc);
        } 
        LuceneUtil.createIndex(docs);
    }
    
    private List<Person> search(Filter filter, String[] fields, String keyword) {
        List<Person> result = new ArrayList<Person>();
        
        IndexSearcher indexSearcher = null;
        TopDocs topDocs = null;
        try {
            // 建立索引搜尋器,且只讀
            IndexReader indexReader = IndexReader.open(FSDirectory.open(new File(XMLPropertyConfig.getConfigXML().getString("index_path"))), true);
            indexSearcher = new IndexSearcher(indexReader);

            MultiFieldQueryParser queryParser = new MultiFieldQueryParser(Version.LUCENE_35,
                    fields, new IKAnalyzer());
            Query query = queryParser.parse(keyword);

            // 返回前number條記錄
            if(filter == null){
                topDocs=indexSearcher.search(query, 100000);
            }else {
                topDocs=indexSearcher.search(query, filter, 100000);
            }
            
            // 資訊展示
            int totalCount = topDocs.totalHits;
            System.out.println("共檢索出 " + totalCount + " 條記錄");

            //高亮顯示
            Formatter formatter = new SimpleHTMLFormatter("<font color='red'>", "</font>");
            QueryScorer fragmentScorer = new QueryScorer(query);
            Highlighter highlighter = new Highlighter(formatter, fragmentScorer);
            Fragmenter fragmenter = new SimpleFragmenter(100);
            highlighter.setTextFragmenter(fragmenter);

            ScoreDoc[] scoreDocs = topDocs.scoreDocs;

            for (ScoreDoc scDoc : scoreDocs) {
                Document document = indexSearcher.doc(scDoc.doc);
                String id = document.get("id");
                String name = document.get("name");
                String age = document.get("age");
                String city = document.get("city");
                String birthday = document.get("birthday");
                float score = scDoc.score; //相似度
                System.out.println("相似度："+score);

                String lighterName = highlighter.getBestFragment(new IKAnalyzer(), "name", name);
                if (null == lighterName) {
                    lighterName = name;
                }

                String lighterAge = highlighter.getBestFragment(new IKAnalyzer(), "age", age);
                if (null == lighterAge) {
                    lighterAge = age;
                }
                
                String lighterCity= highlighter.getBestFragment(new IKAnalyzer(), "city", city);
                if (null == lighterCity) {
                    lighterCity = c