Lucence3.0学习（1）

1.简介

Lucene是apache软件基金会4 jakarta项目组的一个子项目，是一个开放源代码的全文检索引擎工具包，即它不是一个完整的全文检索引擎，而是一个全文检索引擎的架构，

提供了完整的查询引擎和索引引擎，部分文本分析引擎（英文与德文两种西方语言）。Lucene的目的是为软件开发人员提供一个简单易用的工具包，以方便的在目标系统中实现

全文检索的功能，或者是以此为基础建立起完整的全文检索引擎。

2. 下载

http://labs.renren.com/apache-mirror//lucene/java/3.0.3/

3.测试

在eclipse中邪见项目 Lucence3.0Test,将一下包导入到build 路径中

lucene-core-3.0.2.jar

lucene-demos-3.0.2.jar

lucene-analyzers-3.0.2.jar

lucene-fast-vector-highlighter-3.0.2.jar

lucene-highlighter-3.0.2.jar

lucene-memory-3.0.2.jar

在任意目录下新建两个文件夹：

用来存放lucence进行分词的文件和生成的index。如下图：file1用来存放进行分词的文件，里面存放有N个txt文件，txt文件的内容任意，如：我们都是中国人，index文件夹是新建的，里面不要有任何的文件，是用来存储生成的index的

4. 代码

新建创建索引的类，以及测试

import java.io.BufferedReader;
import java.io.File;
import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.util.Date;

import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.document.DateTools;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
import org.apache.lucene.index.IndexWriter;
import org.apache.lucene.store.FSDirectory;
import org.wltea.analyzer.lucene.IKAnalyzer;

public class IndexerOK {
private static String INDEX_DIR = "D:\\nutchwork\\LucenceTestDir\\index";// 索引存放目录
private static String DATA_DIR = "D:\\nutchwork\\LucenceTestDir\\file1";// 小文件存放的目录

public static void main(String[] args) throws Exception {

   long start = new Date().getTime();
   int numIndexed = index(new File(INDEX_DIR), new File(DATA_DIR));// 调用index方法
   long end = new Date().getTime();
   System.out.println("Indexing " + numIndexed + " files took "
     + (end - start) + " milliseconds");
}

/**
* 索引dataDir下的.txt文件，并储存在indexDir下，返回索引的文件数量
* 
* @param indexDir
* @param dataDir
* @return int
* @throws IOException
*/
public static int index(File indexDir, File dataDir) throws IOException {

   if (!dataDir.exists() || !dataDir.isDirectory()) {
    throw new IOException(dataDir
      + " does not exist or is not a directory");
   }
   Analyzer analyzer = new IKAnalyzer();// 采用的分词器

   //第三个参数 为true表示新建，false表示添加到原有索引中
   IndexWriter writer = new IndexWriter(FSDirectory.open(indexDir),
     analyzer, true, IndexWriter.MaxFieldLength.LIMITED);

   indexDirectory(writer, dataDir);// 调用indexDirectory方法
   int numIndexed = writer.numDocs();
   writer.optimize();
   writer.close();
   return numIndexed;
}

/**
* 循环遍历目录下的所有.txt文件并进行索引
* 
* @param writer
* @param dir
* @throws IOException
*/
private static void indexDirectory(IndexWriter writer, File dir)
    throws IOException {

   File[] files = dir.listFiles();

   for (int i = 0; i < files.length; i++) {
    File f = files[i];
    if (f.isDirectory()) {
     indexDirectory(writer, f); // recurse
    } else if (f.getName().endsWith(".txt")) {
     indexFile(writer, f);
    }
   }
}

/**
* 对单个txt文件进行索引
* 
* @param writer
* @param f
* @throws IOException
*/
private static void indexFile(IndexWriter writer, File f)
    throws IOException {

   if (f.isHidden() || !f.exists() || !f.canRead()) {
    return;
   }

   System.out.println("Indexing " + f.getCanonicalPath());

   Document doc = new Document();
   // doc.add(new Field("contents", new FileReader(f)));
   doc.add(new Field("filename", f.getCanonicalPath(), Field.Store.YES, Field.Index.ANALYZED));

   String temp = FileReaderAll(f.getCanonicalPath(), "GBK");
   System.out.println(temp);

   doc.add(new Field("TTT", temp, Field.Store.YES, Field.Index.ANALYZED));

   doc.add(new Field("path", f.getPath(), Field.Store.YES,
     Field.Index.ANALYZED));

   doc.add(new Field("modified", DateTools.timeToString(f.lastModified(),
     DateTools.Resolution.MINUTE), Field.Store.YES,
     Field.Index.ANALYZED));

   FileInputStream fis = new FileInputStream(f);
   // 按照 UTF-8 编码方式将字节流转化为字符流
   InputStreamReader isr = new InputStreamReader(fis, "utf-8");
   // 从字符流中获取文本并进行缓冲
   BufferedReader br = new BufferedReader(isr);

   doc.add(new Field("contents", br));

   writer.setUseCompoundFile(false);
   writer.addDocument(doc);
}

public static String FileReaderAll(String FileName, String charset)
    throws IOException {
   BufferedReader reader = new BufferedReader(new InputStreamReader(
     new FileInputStream(FileName), charset));
   String line = new String();
   String temp = new String();

   while ((line = reader.readLine()) != null) {
    temp += line;
   }
   reader.close();
   return temp;
}

}

　　运行结果：

Indexing D:\nutchwork\LucenceTestDir\file1\1.txt
我们是中国人
Indexing D:\nutchwork\LucenceTestDir\file1\2.txt
我们是中国人
Indexing D:\nutchwork\LucenceTestDir\file1\3.txt
我们是中国人
Indexing D:\nutchwork\LucenceTestDir\file1\4.txt
我们是中国人
Indexing 4 files took 2293 milliseconds

　　新建查询的类以及测试：

import java.io.File;
import java.io.StringReader;
import java.util.Date;
import java.util.List;

import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.TokenStream;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Fieldable;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.Query;
import org.apache.lucene.search.ScoreDoc;
import org.apache.lucene.search.Sort;
import org.apache.lucene.search.SortField;
import org.apache.lucene.search.TopDocs;
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.store.FSDirectory;
import org.wltea.analyzer.lucene.IKAnalyzer;
import org.wltea.analyzer.lucene.IKQueryParser;
import org.wltea.analyzer.lucene.IKSimilarity;

public class SearchQueryOK {
private static String INDEX_DIR = "D:\\nutchwork\\LucenceTestDir\\index";// 索引所在的路径
private static String KEYWORD = "中国人";// 关键词
private static int TOP_NUM = 100;// 显示前100条结果

public static void main(String[] args) throws Exception {
   File indexDir = new File(INDEX_DIR);
   if (!indexDir.exists() || !indexDir.isDirectory()) {
    throw new Exception(indexDir
      + " does not exist or is not a directory.");
   }
   search(indexDir, KEYWORD);// 调用search方法进行查询
}

/**
* 查询
* 
* @param indexDir
* @param q
* @throws Exception
*/
public static void search(File indexDir, String q) throws Exception {
   IndexSearcher is = new IndexSearcher(FSDirectory.open(indexDir), true);// read-only
   String[] field = {"TTT","modified","filename"};
   long start = new Date().getTime();// start time

   // 高亮设置
   Analyzer analyzer = new IKAnalyzer();// 设定分词器
   Query query2 = IKQueryParser.parseMultiField(field, KEYWORD);
   
   
   // 实例化搜索器
   IndexSearcher isearcher1 = new IndexSearcher(FSDirectory.open(indexDir));
   // 在索引器中使用IKSimilarity相似度评估器
   
   isearcher1.setSimilarity(new IKSimilarity());
  
   
   
   
   Sort sort = new Sort(new SortField("path", SortField.DOC,false));
   //TermQuery q1 = new TermQuery(new Term("filename", "1"));
   // 搜索相似度最高的记录
   TopDocs topDocs1 = isearcher1.search(query2,null, TOP_NUM,sort);
  
   ScoreDoc[] hits3 = topDocs1.scoreDocs;
   SimpleHTMLFormatter simpleHtmlFormatter = new SimpleHTMLFormatter(
     "<span style='color:#ff0000'>", "</span>");// 设定高亮显示的格式，也就是对高亮显示的词组加上前缀后缀
   Highlighter highlighter = new Highlighter(simpleHtmlFormatter,
     new QueryScorer(query2));
   for (int i = 0; i < hits3.length; i++) {
    Document doc = is.doc(hits3[i].doc);
    String docTTT = doc.get("TTT");
    highlighter.setTextFragmenter(new SimpleFragmenter(docTTT.length()));// 设置每次返回的字符数.想必大家在使用搜索引擎的时候也没有一并把全部数据展示出来吧，当然这里也是设定只展示部分数据
    TokenStream tokenStream = analyzer.tokenStream("",
      new StringReader(docTTT));
    String str = highlighter.getBestFragment(tokenStream, docTTT);
    System.out.println(" 高亮设置: " + str );
   
    String docModified = doc.get("filename");
    highlighter.setTextFragmenter(new SimpleFragmenter(docModified.length()));
   
    TokenStream tokenStream2 = analyzer.tokenStream("",
      new StringReader(docModified));
    String str2 = highlighter.getBestFragment(tokenStream2, docModified);
    System.out.println(" 高亮设置: " + str2 );
   
    
    
    
    List<Fieldable> list = doc.getFields();
    for (int j = 0; j < list.size(); j++) {
     Fieldable fieldable = list.get(j);
     System.out.println(fieldable.name() + " : "
       + fieldable.stringValue() + "<br>");
    }
   }

   
   
   
   
   long end = new Date().getTime();// end time

   System.out.println("Found " + hits3.length
     + " document(s) (in " + (end - start)
     + " milliseconds) that matched query '" + q + "':");
}

}

　　对索引的操作类：

import java.io.File;
import java.io.IOException;
import java.sql.Connection;
import java.sql.SQLException;

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.IndexReader;
import org.apache.lucene.index.IndexWriter;
import org.apache.lucene.index.Term;
import org.apache.lucene.store.Directory;
import org.apache.lucene.store.FSDirectory;
import org.apache.lucene.util.Version;
import org.wltea.analyzer.lucene.IKAnalyzer;

public class ManageIndexFile {
private static String INDEX_DIR = "D:\\nutchwork\\LucenceTestDir\\index";// 索引存放目录



//删除索引
public static void DeleteIndex(SearchDocBean bean) throws IOException {
   Directory dir = FSDirectory.open(new File(INDEX_DIR));
   IndexReader reader = IndexReader.open(dir, false);
   Term term = new Term("modified", bean.getId());
   int count = reader.deleteDocuments(term);
   reader.close();
   System.out.println("Successful Delete " + count + " path==" + bean.getId());

}

public static void DeleteIndex(int[] posIDS) throws IOException {
   Directory dir = FSDirectory.open(new File(INDEX_DIR));
   IndexReader reader = IndexReader.open(dir, false);
   for (int i = 0; i < posIDS.length; i++) {
    Term term = new Term("posID", Integer.toString(posIDS[i]));
    reader.deleteDocuments(term);
   }
   reader.close();

}
//更新索引
public static void UpdateIndex(SearchDocBean bean) throws IOException {
   Directory dir = FSDirectory.open(new File(INDEX_DIR));
   IndexReader reader = IndexReader.open(dir, false);
   Term term = new Term("modified", bean.getId());
   reader.deleteDocuments(term);
   reader.close();

   IndexWriter writer = new IndexWriter(FSDirectory.open(new File(
     INDEX_DIR)), new StandardAnalyzer(Version.LUCENE_CURRENT),
     true, IndexWriter.MaxFieldLength.LIMITED);
   Document doc = new Document();

   doc.add(new Field("modified", bean.getId(), Field.Store.YES,
     Field.Index.NOT_ANALYZED));
   writer.addDocument(doc);
   writer.optimize();
   writer.close();

}




//增加索引
public static void AddIndex(SearchDocBean bean,
    Connection conn) throws IOException, SQLException {
   Analyzer analyzer = new IKAnalyzer();// 采用的分词器

   IndexWriter writer = new IndexWriter(FSDirectory.open(new File(
     INDEX_DIR)), analyzer, false,
     IndexWriter.MaxFieldLength.LIMITED);

   Document doc = new Document();
   doc.add(new Field("filename", bean.getFileName(), Field.Store.YES,
     Field.Index.ANALYZED));

   doc.add(new Field("path", bean.getPath(), Field.Store.YES,
     Field.Index.ANALYZED));

   doc.add(new Field("dateTime", bean.getId(), Field.Store.YES,
     Field.Index.ANALYZED));

   doc.add(new Field("TTT", bean.getContents(), Field.Store.YES, Field.Index.ANALYZED));

   writer.setUseCompoundFile(false);
   writer.addDocument(doc);
   writer.optimize();
   writer.close();
}

}

　　封装起来的查询结果：

public class SearchDocBean {
    private String id;
    private String path;
    private String contents;
    private String dateTime;
    public String getId() {
        return id;
    }
    public void setId(String id) {
        this.id = id;
    }
    public String getPath() {
        return path;
    }
    public void setPath(String path) {
        this.path = path;
    }
    public String getContents() {
        return contents;
    }
    public void setContents(String contents) {
        this.contents = contents;
    }
    public String getDateTime() {
        return dateTime;
    }
    public void setDateTime(String dateTime) {
        this.dateTime = dateTime;
    }
    public String getFileName() {
        return fileName;
    }
    public void setFileName(String fileName) {
        this.fileName = fileName;
    }
    private String fileName;

}

下面是serach 中国人的结果：

 高亮设置: <span style='color:#ff0000'>中国人</span>
 高亮设置: null
filename : D:\nutchwork\LucenceTestDir\file1\1.txt<br>
TTT : 我们是中国人<br>
path : D:\nutchwork\LucenceTestDir\file1\1.txt<br>
modified : 201107161115<br>
 高亮设置: <span style='color:#ff0000'>中国人</span>
 高亮设置: null
filename : D:\nutchwork\LucenceTestDir\file1\2.txt<br>
TTT : 我们是中国人<br>
path : D:\nutchwork\LucenceTestDir\file1\2.txt<br>
modified : 201107161115<br>
 高亮设置: <span style='color:#ff0000'>中国人</span>
 高亮设置: null
filename : D:\nutchwork\LucenceTestDir\file1\3.txt<br>
TTT : 我们是中国人<br>
path : D:\nutchwork\LucenceTestDir\file1\3.txt<br>
modified : 201107161115<br>
 高亮设置: <span style='color:#ff0000'>中国人</span>
 高亮设置: null
filename : D:\nutchwork\LucenceTestDir\file1\4.txt<br>
TTT : 我们是中国人<br>
path : D:\nutchwork\LucenceTestDir\file1\4.txt<br>
modified : 201107161115<br>
Found 4 document(s) (in 717 milliseconds) that matched query '中国人':

　　整个工程：基本上是从网上找到的代码，运行了下，算是有一个大概的了解。

posted @ 2011-07-16 21:43 wtx 阅读(4457) 评论(0) 编辑收藏举报

会员力量，点亮园子希望

刷新页面返回顶部

wtx

Lucence3.0学习（1）

公告