Lucene 3.6.2入门:针对索引文件的CRUD

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    * @see =============================================================================================================
    * @see Lucene官网:http://lucene.apache.org
    * @see Lucene下载:http://archive.apache.org/dist/lucene/java/
    * @see Lucene文档:http://wiki.apache.org/lucene-java/
    * @see =============================================================================================================
    * @see 使用Luke查看分词信息(http://code.google.com/p/luke/)
    * @see 1)引言:每一个Lucene版本都会有一个相应的Luke文件
    * @see 2)打开:双击或java -jar lukeall-3.5.0.jar
    * @see 3)选择索引的存放目录后点击OK即可
    * @see 7)如果我们的索引有改变,可以点击右侧的Re-open按钮重新载入索引
    * @see 4)Luke界面右下角的Top ranking terms窗口中显示的就是分词信息。其中Rank列表示出现频率
    * @see 5)Luke菜单下的Documents选项卡中显示的就是文档信息,我们可以根据文档序号来浏览(点击向左和向右的方向箭头)
    * @see 6)Luke菜单下的Search选项卡中可以根据我们输入的表达式来查文档内容
    * @see 比如在Enter search expression here:输入content:my,再在右侧点击一个黑色粗体字的Search大按钮即可
    * @see =============================================================================================================
    * @create Jun 30, 2012 4:34:09 PM
    *
    */
public class HelloIndex {    /*    * 定义一组数据,用来演示搜索(这里有一封邮件为例)    * 假设每一个变量代表一个Document,这里就定义了6个Document    */    //邮件编号    private String[] ids = {"1", "2", "3", "4", "5", "6"};    //邮件主题    private String[] names = {"Michael", "Scofield", "Tbag", "Jack", "Jade", "Jadyer"};    //邮件地址    private String[] emails = {"aa@jadyer.us", "bb@jadyer.cn", "cc@jadyer.cc", "dd@jadyer.tw", "ee@jadyer.hk", "ff@jadyer.me"};    //邮件内容    private String[] contents = {"my blog", "my website", "my name", "I am JavaDeveloper", "I am from Haerbin", "I like Lucene"};    //邮件附件(为数字和日期加索引,与,字符串加索引的方式不同)    private int[] attachs = {9,3,5,4,1,2};    //邮件日期    private Date[] dates = new Date[ids.length];    //它的创建是比较耗时耗资源的,所以这里只让它创建一次,此时reader处于整个生命周期中,实际应用中也可能直接放到ApplicationContext里面    private static IndexReader reader = null;    private Directory directory = null;    public HelloIndex(){    SimpleDateFormat sdf = new SimpleDateFormat("yyyyMMdd");    try {    dates[0] = sdf.parse("20120601");    dates[1] = sdf.parse("20120603");    dates[2] = sdf.parse("20120605");    dates[3] = sdf.parse("20120607");    dates[4] = sdf.parse("20120609");    dates[5] = sdf.parse("20120611");    directory = FSDirectory.open(new File("myExample/02_index/"));    } catch (Exception e) {    e.printStackTrace();    }    }    /**    * 获取IndexReader实例    */    private IndexReader getIndexReader(){    try {    if(reader == null){    reader = IndexReader.open(directory);    }else{    //if the index was changed since the provided reader was opened, open and return a new reader; else,return null    //如果当前reader在打开期间index发生改变,则打开并返回一个新的IndexReader,否则返回null    IndexReader ir = IndexReader.openIfChanged(reader);    if(ir != null){    reader.close(); //关闭原reader    reader = ir; //赋予新reader    }    }    return reader;    }catch(Exception e) {    e.printStackTrace();    }    return null; //发生异常则返回null    }    /**    * 通过IndexReader获取文档数量    */    public void getDocsCount(){    System.out.println("maxDocs:" + this.getIndexReader()。maxDoc());    System.out.println("numDocs:" + this.getIndexReader()。numDocs());    System.out.println("deletedDocs:" + this.getIndexReader()。numDeletedDocs());    }    /**    * 创建索引    */    public void createIndex(){    IndexWriter writer = null;    Document doc = null;    try{    writer = new IndexWriter(directory, new IndexWriterConfig(Version.LUCENE_36, new StandardAnalyzer(Version.LUCENE_36)));    writer.deleteAll(); //创建索引之前,先把文档清空掉    for(int i=0; i    doc = new Document();    doc.add(new Field("id", ids[i], Field.Store.YES, Field.Index.NOT_ANALYZED_NO_NORMS));    doc.add(new Field("name", names[i], Field.Store.YES, Field.Index.NOT_ANALYZED_NO_NORMS));    doc.add(new Field("email", emails[i], Field.Store.YES, Field.Index.NOT_ANALYZED));    doc.add(new Field("content", contents[i], Field.Store.NO, Field.Index.ANALYZED));    doc.add(new NumericField("attach", Field.Store.YES, true)。setIntValue(attachs[i])); //为数字加索引(第三个参数指定是否索引)    doc.add(new NumericField("date", Field.Store.YES, true)。setLongValue(dates[i].getTime())); //为日期加索引    /*    * 建立索引时加权    * 定义排名规则,即加权,这里是为指定邮件名结尾的emails加权    */    if(emails[i].endsWith("jadyer.cn")){    doc.setBoost(2.0f);    }else if(emails[i].endsWith("jadyer.me")){    doc.setBoost(1.5f); //为文档加权…默认为1.0,权值越高则排名越高,显示得就越靠前    }else{    doc.setBoost(0.5f); //注意它的参数类型是Float    }    writer.addDocument(doc);    }    }catch(Exception e) {    e.printStackTrace();    }finally{    if(null != writer){    try {    writer.close();    } catch (IOException ce) {    ce.printStackTrace();    }    }    }    }    /**    * 搜索文件    */    public void searchFile(){    IndexSearcher searcher = new IndexSearcher(this.getIndexReader());    Query query = new TermQuery(new Term("content", "my")); //精确搜索:搜索"content"中包含"my"的文档    try{    TopDocs tds = searcher.search(query, 10);    for(ScoreDoc sd : tds.scoreDocs){    Document doc = searcher.doc(sd.doc); //sd.doc得到的是文档的序号    //doc.getBoost()得到的权值与创建索引时设置的权值之间是不相搭的,创建索引时的权值的查看需要使用Luke工具    // 之所以这样,是因为这里的Document对象(是获取到的)与创建索引时的Document对象,不是同一个对象    //sd.score得到的是该文档的评分,该评分规则的公式是比较复杂的,它主要与文档的权值和出现次数成正比    System.out.print("(" + sd.doc + "|" + doc.getBoost() + "|" + sd.score + ")" + doc.get("name") + "[" + doc.get("email") + "]-->");    System.out.println(doc.get("id") + "," + doc.get("attach") + "," + new SimpleDateFormat("yyyyMMdd")。format(new Date(Long.parseLong(doc.get("date")))));    }    }catch(Exception e){    e.printStackTrace();    }finally{    if(null != searcher){    try {    searcher.close();    } catch (IOException e) {    e.printStackTrace();    }    }    }    } /**    * 更新索引    * @see Lucene其实并未提供更新索引的方法,这里的更新操作内部是先删除再添加的方式    * @see 因为Lucene认为更新索引的代价,与删除后重建索引的代价,二者是差不多的    */    public void updateIndex(){    IndexWriter writer = null;    Document doc = new Document();    try{    writer = new IndexWriter(directory, new IndexWriterConfig(Version.LUCENE_36, new StandardAnalyzer(Version.LUCENE_36)));    doc.add(new Field("id", "1111", Field.Store.YES, Field.Index.NOT_ANALYZED_NO_NORMS));    doc.add(new Field("name", names[0], Field.Store.YES, Field.Index.NOT_ANALYZED_NO_NORMS));    doc.add(new Field("email", emails[0], Field.Store.YES, Field.Index.NOT_ANALYZED));    doc.add(new Field("content", contents[0], Field.Store.NO, Field.Index.ANALYZED));    doc.add(new NumericField("attach", Field.Store.YES, true)。setIntValue(attachs[0]));    doc.add(new NumericField("date", Field.Store.YES, true)。setLongValue(dates[0].getTime()));    //其实它会先删除索引文档中id为1的文档,然后再将这里的doc对象重新索引,所以即便这里的1!=1111,但它并不会报错    //所以在执行完该方法后:maxDocs=7,numDocs=6,deletedDocs=1,就是因为Lucene会先删除再添加    writer.updateDocument(new Term("id","1"), doc);    }catch(Exception e) {    e.printStackTrace();    }finally{    if(null != writer){    try {    writer.close();    } catch (IOException ce) {    ce.printStackTrace();    }    }    }    }    /**    * 删除索引    * @see -----------------------------------------------------------------------------------------------------    * @see 在执行完该方法后,再执行本类的searchFile()方法,得知numDocs=5,maxDocs=6,deletedDocs=1    * @see 这说明此时删除的文档并没有被完全删除,而是存储在一个回收站中,它是可以恢复的    * @see -----------------------------------------------------------------------------------------------------    * @see 从回收站中清空索引IndexWriter    * @see 对于清空索引,Lucene3.5之前叫做优化,调用的是IndexWriter.optimize()方法,但该方法已被禁用    * @see 因为optimize时它会全部更新索引,这一过程所涉及到的负载是很大的,于是弃用了该方法,使用forceMerge代替    * @see 使用IndexWriter.forceMergeDeletes()方法可以强制清空回收站中的内容    * @see 另外IndexWriter.forceMerge(3)方法会将索引合并为3段,这3段中的被删除的数据也会被清空    * @see 但其在Lucene3.5之后不建议使用,因为其会消耗大量的开销,而Lucene会根据情况自动处理的    * @see -----------------------------------------------------------------------------------------------------    */    public void deleteIndex(){    IndexWriter writer = null;    try{    writer = new IndexWriter(directory, new IndexWriterConfig(Version.LUCENE_36, new StandardAnalyzer(Version.LUCENE_36)));    //其参数可以传Query或Term…Query指的是可以查询出一系列的结果并将其全部删掉,而Term属于精确查找    writer.deleteDocuments(new Term("id", "1")); //删除索引文档中id为1的文档    }catch(Exception e) {    e.printStackTrace();    }finally{    if(null != writer){    try {    writer.close();    } catch (IOException ce) {    ce.printStackTrace();    }    }    }    }    /**    * 恢复索引    * @see 建议弃用    */    @Deprecated    public void unDeleteIndex(){    IndexReader reader = null;    try {    //IndexReader.open(directory)此时该IndexReader默认的readOnly=true,而在恢复索引时应该指定其为非只读的    reader = IndexReader.open(directory, false);    //Deprecated. Write support will be removed in Lucene 4.0. There will be no replacement for this method.    reader.undeleteAll();    } catch (Exception e) {    e.printStackTrace();    }finally{    if(null != reader){    try {    reader.close();    } catch (IOException e) {    e.printStackTrace();    }    }    }    }    }
 下面是用JUnit4.x写的一个小测试
    双击代码全选
    package com.jadyer.test;    import org.junit.After;    import org.junit.Before;    import org.junit.Test;    import com.jadyer.lucene.HelloIndex;    public class HelloIndexTest {    private HelloIndex hello;    @Before    public void init(){    hello = new HelloIndex();    }    @After    public void destroy(){    hello.getDocsCount();    }    @Test    public void createIndex(){    hello.createIndex();    }    @Test    public void searchFile(){    hello.searchFile();    }    @Test    public void updateIndex(){    hello.updateIndex();    }    @Test    public void deleteIndex(){    hello.deleteIndex();    }    @Test    @SuppressWarnings("deprecation")    public void unDeleteIndex(){    hello.unDeleteIndex();    }    }

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