Lucene的使用 | 红颜丽人

Lucene的使用.

如果你想快速查询你磁盘上文件，或查询邮件、Web页面，甚至查询存于数据库的数据，你都可以借助于Lucene来完成。但是要完成查询就必须先建立索引。首先从Lucene API说起：
1、 Lucene API（核心操作类）
IndexWriter 创建和维护索引（向原索引中添加新Document，设置合并策略、优化等）
FSDirectory 最主要用来存储索引文件的类，表示将索引文件存储到文件系统
Document 索引和查询的原子单元，一个Document包含一系列Field
IndexReader 一个抽象类，提供了访问索引的接口，当然访问索引也可以通过它的子类来完成
Analyzer 分词类，它有一系列子类，都是用来将文本解析成TokenStream
Searcher 用于查询索引的核心类
2、创建索引
Java代码
Directory dir = FSDirectory.open(new File(“lucene.blog”));
IndexWriter writer = new IndexWriter(dir,new StandardAnalyzer(Version.LUCENE_29),true, IndexWriter.MaxFieldLength.UNLIMITED);
Document doc = new Document();
doc.add(new Field(“id”, “101″, Field.Store.YES, Field.Index.NO));
doc.add(new Field(“name”, “kobe bryant”, Field.Store.YES, Field.Index.NO));
writer.addDocument(doc);
writer.optimize();
writer.close();
Java代码复制代码收藏代码
Directory dir = FSDirectory.open(new File(“lucene.blog”));
IndexWriter writer = new IndexWriter(dir,new StandardAnalyzer(Version.LUCENE_29),true, IndexWriter.MaxFieldLength.UNLIMITED);
Document doc = new Document();
doc.add(new Field(“id”, “101″, Field.Store.YES, Field.Index.NO));
doc.add(new Field(“name”, “kobe bryant”, Field.Store.YES, Field.Index.NO));
writer.addDocument(doc);
writer.optimize();
writer.close();
[java] view plaincopyprint?
Directory dir = FSDirectory.open(new File(“lucene.blog”));
IndexWriter writer = new IndexWriter(dir,new StandardAnalyzer(Version.LUCENE_29),true, IndexWriter.MaxFieldLength.UNLIMITED);
Document doc = new Document();
doc.add(new Field(“id”, “101″, Field.Store.YES, Field.Index.NO));
doc.add(new Field(“name”, “kobe bryant”, Field.Store.YES, Field.Index.NO));
writer.addDocument(doc);
writer.optimize();
writer.close();
如上所示将索引文件存储于工作目录下lucene.blog文件夹，创建了Document，向Document里添加了两个Field id和name，然后使用IndexWriter的addDocument(Document)方法将其添加到索引目录下的索引文件中，然后使用IndexWriter的optimize()方法进行对索引文件优化，最后关闭IndexWriter;
3、通过IndexWriter删除索引中Document
Java代码
Directory dir = FSDirectory.open(new File(“lucene.blog”));
IndexWriter writer = new IndexWriter(dir, new StandardAnalyzer(Version.LUCENE_29), true, IndexWriter.MaxFieldLength.UNLIMITED);
writer.deleteDocuments(new Term(“id”, “101″));
writer.commit();
writer.close();
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Directory dir = FSDirectory.open(new File(“lucene.blog”));
IndexWriter writer = new IndexWriter(dir, new StandardAnalyzer(Version.LUCENE_29), true, IndexWriter.MaxFieldLength.UNLIMITED);
writer.deleteDocuments(new Term(“id”, “101″));
writer.commit();
writer.close();
[java] view plaincopyprint?
Directory dir = FSDirectory.open(new File(“lucene.blog”));
IndexWriter writer = new IndexWriter(dir, new StandardAnalyzer(Version.LUCENE_29), true, IndexWriter.MaxFieldLength.UNLIMITED);
writer.deleteDocuments(new Term(“id”, “101″));
writer.commit();
writer.close();
如上先打开索引位置（工作目录下lucene.blog文件夹），然后直接调运IndexWriter的deleteDocuments(Term)方法删除上面2中创建的Document，注意必须调运commit()方法，上面2中之所以没有commit()是因为optimize()方法中存在默认Commit方法；
4、通过IndexWriter更新索引中Document
Java代码
Directory dir = FSDirectory.open(new File(“lucene.blog”));
IndexWriter writer = new IndexWriter(dir, new StandardAnalyzer(Version.LUCENE_29), true, IndexWriter.MaxFieldLength.UNLIMITED);
Document doc = new Document();
doc.add(new Field(“id”, “101″, Field.Store.YES, Field.Index.ANALYZED)); // Field.Index.ANALYZED
doc.add(new Field(“name”, “kylin soong”, Field.Store.YES, Field.Index.ANALYZED));
writer.updateDocument(new Term(“id”, “101″), doc);
writer.commit();
writer.close();
Java代码复制代码收藏代码
Directory dir = FSDirectory.open(new File(“lucene.blog”));
IndexWriter writer = new IndexWriter(dir, new StandardAnalyzer(Version.LUCENE_29), true, IndexWriter.MaxFieldLength.UNLIMITED);
Document doc = new Document();
doc.add(new Field(“id”, “101″, Field.Store.YES, Field.Index.NO));
doc.add(new Field(“name”, “kylin soong”, Field.Store.YES, Field.Index.NO));
writer.updateDocument(new Term(“id”, “101″), doc);
writer.commit();
writer.close();
[java] view plaincopyprint?
Directory dir = FSDirectory.open(new File(“lucene.blog”));
IndexWriter writer = new IndexWriter(dir, new StandardAnalyzer(Version.LUCENE_29), true, IndexWriter.MaxFieldLength.UNLIMITED);
Document doc = new Document();
doc.add(new Field(“id”, “101″, Field.Store.YES, Field.Index.NO));
doc.add(new Field(“name”, “kylin soong”, Field.Store.YES, Field.Index.NO));
writer.updateDocument(new Term(“id”, “101″), doc);
writer.commit();
writer.close();
通过IndexWriter的updateDocument(Term, Document)来完成更新，具体是将包含Term(“id”, “101″)的Document删除，然后将传入的Document添加到索引文件；
5、Field选项意义
Java代码
Field field = new Field(
“101″,
“kobe bryant”,
Field.Store.YES,
Field.Index.ANALYZED,
Field.TermVector.YES);
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Field field = new Field(
“101″,
“kobe bryant”,
Field.Store.YES,
Field.Index.ANALYZED,
Field.TermVector.YES);
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Field field = new Field(
“101″,
“kobe bryant”,
Field.Store.YES,
Field.Index.ANALYZED,
Field.TermVector.YES);
如上代码显示Field各属性设置情况，下面简单说明这些属性选项的意义
Field.Store.*决定是否将Field的完全值进行存储，注意：不能将整个文本内容存储，这样导致索引文件过大
Field.Store.YES 存储，一旦存储，你可以用完整的Field的完全值作为查询条件查询（id:101）
Field.Store.NO 不存储
Field.Index.*控制Field的值是否可查询通过索引成的索引文件
Field.Index.ANALYZED 用Analyzer将Field的值分词成多个Token
Field.Index.NOT_ANALYZED 不对Field的值分词，将Field的值作为一个Token处理
Field.Index.ANALYZED_NO_NORMS 类似ANALYZED，但不存常规信息到索引文件
Field.Index.NOT_ANALYZED_NO_NORMS 类似NOT_ANALYZED，但不存常规信息到索引文件
Field.Index.NO 不进行索引，Field的值不可被搜索
如果你想要检索出唯一的terms在搜索时，或对搜索结果进行加亮处理等操作是Field.TermVector.*是必要的
Field.TermVector.YES 记录唯一的terms，当重复发生时记下重复数，在不做额外处理
Field.TermVector.WITH_POSITIONS 在上面基础上记录下位置
Field.TermVector.WITH_OFFSETS 在TermVector.YES基础上记录偏移量
Field.TermVector.WITH_POSITIONS_OFFSETS 在TermVector.YES基础上记录偏移量和位置
Field.TermVector.NO 不做任何处理
6、索引numbers
Java代码
Document doc = new Document();
NumericField field1 = new NumericField(“id”);
field1.setIntValue(101);
doc.add(field1);
NumericField field2 = new NumericField(“price”);
field1.setDoubleValue(123.50);
doc.add(field2);
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Document doc = new Document();
NumericField field1 = new NumericField(“id”);
field1.setIntValue(101);
doc.add(field1);
NumericField field2 = new NumericField(“price”);
field1.setDoubleValue(123.50);
doc.add(field2);
[java] view plaincopyprint?
Document doc = new Document();
NumericField field1 = new NumericField(“id”);
field1.setIntValue(101);
doc.add(field1);
NumericField field2 = new NumericField(“price”);
field1.setDoubleValue(123.50);
doc.add(field2);
如上所示为索引numbers方法；
7、索引Date和Time
Java代码
Document doc = new Document();
doc.add(new NumericField(“timestamp”).setLongValue(new Date().getTime()));
doc.add(new NumericField(“day”).setIntValue((int) (new Date().getTime()/24/3600)));
Calendar cal = Calendar.getInstance();
cal.setTime(new Date());
doc.add(new NumericField(“dayOfMonth”).setIntValue(cal.get(Calendar.DAY_OF_MONTH)));
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Document doc = new Document();
doc.add(new NumericField(“timestamp”).setLongValue(new Date().getTime()));
doc.add(new NumericField(“day”).setIntValue((int) (new Date().getTime()/24/3600)));
Calendar cal = Calendar.getInstance();
cal.setTime(new Date());
doc.add(new NumericField(“dayOfMonth”).setIntValue(cal.get(Calendar.DAY_OF_MONTH)));
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Document doc = new Document();
doc.add(new NumericField(“timestamp”).setLongValue(new Date().getTime()));
doc.add(new NumericField(“day”).setIntValue((int) (new Date().getTime()/24/3600)));
Calendar cal = Calendar.getInstance();
cal.setTime(new Date());
doc.add(new NumericField(“dayOfMonth”).setIntValue(cal.get(Calendar.DAY_OF_MONTH)));
实质上对Date和Time的处理是将Date和Time转化为numbers来处理，注意：当然也可以把Date和Time以及上面的numbers当做字符串来处理，不过这样影响查询；
8、IndexWriter的其他同法
Java代码
Directory dir = FSDirectory.open(new File(“lucene.blog”));
IndexWriter writer = new IndexWriter(dir, new StandardAnalyzer(Version.LUCENE_29), true, IndexWriter.MaxFieldLength.LIMITED);
writer.setMaxFieldLength(1);
MergePolicy policy = new LogByteSizeMergePolicy(writer);
writer.setMergePolicy(policy);
writer.optimize(5);
writer.close();
Java代码复制代码收藏代码
Directory dir = FSDirectory.open(new File(“lucene.blog”));
IndexWriter writer = new IndexWriter(dir, new StandardAnalyzer(Version.LUCENE_29), true, IndexWriter.MaxFieldLength.LIMITED);
writer.setMaxFieldLength(1);
MergePolicy policy = new LogByteSizeMergePolicy(writer);
writer.setMergePolicy(policy);
writer.optimize(5);
writer.close();
[java] view plaincopyprint?
Directory dir = FSDirectory.open(new File(“lucene.blog”));
IndexWriter writer = new IndexWriter(dir, new StandardAnalyzer(Version.LUCENE_29), true, IndexWriter.MaxFieldLength.LIMITED);
writer.setMaxFieldLength(1);
MergePolicy policy = new LogByteSizeMergePolicy(writer);
writer.setMergePolicy(policy);
writer.optimize(5);
writer.close();
如上IndexWriter.MaxFieldLength.LIMITED设定了Field截取功能，如果Field值相当长，而你只想索引Field值的前固定个字符，可以用Field截取功能来实现；IndexWriter的setMergePolicy(policy)，可以设定合并策略，另外optimize(int maxNumSegments)方法可以通过参数设定优化成的Segment个数；
9、根据确定的term查询
Java代码
IndexReader reader = IndexReader.open(FSDirectory.open(new File(“lucene.blog”)),true);
IndexSearcher searcher = new IndexSearcher(reader);
Term term = new Term(“id”,”101″);
Query query = new TermQuery(term);
TopDocs topDocs = searcher.search(query, 10);
System.out.println(topDocs.totalHits);
ScoreDoc[] docs = topDocs.scoreDocs;
System.out.println(docs[0].doc + ” ” + docs[0].score);
Document doc = searcher.doc(docs[0].doc);
System.out.println(doc.get(“id”));
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IndexReader reader = IndexReader.open(FSDirectory.open(new File(“lucene.blog”)),true);
IndexSearcher searcher = new IndexSearcher(reader);
Term term = new Term(“id”,”101″);
Query query = new TermQuery(term);
TopDocs topDocs = searcher.search(query, 10);
System.out.println(topDocs.totalHits);
ScoreDoc[] docs = topDocs.scoreDocs;
System.out.println(docs[0].doc + ” ” + docs[0].score);
Document doc = searcher.doc(docs[0].doc);
System.out.println(doc.get(“id”));
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IndexReader reader = IndexReader.open(FSDirectory.open(new File(“lucene.blog”)),true);
IndexSearcher searcher = new IndexSearcher(reader);
Term term = new Term(“id”,”101″);
Query query = new TermQuery(term);
TopDocs topDocs = searcher.search(query, 10);
System.out.println(topDocs.totalHits);
ScoreDoc[] docs = topDocs.scoreDocs;
System.out.println(docs[0].doc + ” ” + docs[0].score);
Document doc = searcher.doc(docs[0].doc);
System.out.println(doc.get(“id”));
如上示例显示了一个Lucene查询的基本方法，IndexSearcher是核心的查询类，IndexReader 可以读取索引文件，IndexSearcher有一系列重载的Search（）方法，可以根据传入不同参数进行不同查询处理，ScoreDoc数组保存查询结果，和相关得分；
10、根据QueryParser查询，并收集查询结果
Java代码
IndexReader reader = IndexReader.open(FSDirectory.open(new File(“lucene.blog”)),true);
IndexSearcher searcher = new IndexSearcher(reader);
Analyzer analyzer = new StandardAnalyzer(Version.LUCENE_29);
QueryParser parser = new QueryParser(Version.LUCENE_29,”name”,analyzer);
String queryString = “kobe”;
Query query = parser.parse(queryString);
TopScoreDocCollector collector = TopScoreDocCollector.create(10, false);
searcher.search(query, collector);
ScoreDoc[] hits = collector.topDocs().scoreDocs;
for(int i = 0 ; i < hits.length ; i ++) {
Document doc = searcher.doc(hits[i].doc);
String name = doc.get(“name”);
if (name != null) {
System.out.println(name);
}
}
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IndexReader reader = IndexReader.open(FSDirectory.open(new File(“lucene.blog”)),true);
IndexSearcher searcher = new IndexSearcher(reader);
Analyzer analyzer = new StandardAnalyzer(Version.LUCENE_29);
QueryParser parser = new QueryParser(Version.LUCENE_29,”name”,analyzer);
String queryString = “kobe”;
Query query = parser.parse(queryString);
TopScoreDocCollector collector = TopScoreDocCollector.create(10, false);
searcher.search(query, collector);
ScoreDoc[] hits = collector.topDocs().scoreDocs;
for(int i = 0 ; i < hits.length ; i ++) {
Document doc = searcher.doc(hits[i].doc);
String name = doc.get(“name”);
if (name != null) {
System.out.println(name);
}
}
[java] view plaincopyprint?
IndexReader reader = IndexReader.open(FSDirectory.open(new File(“lucene.blog”)),true);
IndexSearcher searcher = new IndexSearcher(reader);
Analyzer analyzer = new StandardAnalyzer(Version.LUCENE_29);
QueryParser parser = new QueryParser(Version.LUCENE_29,”name”,analyzer);
String queryString = “kobe”;
Query query = parser.parse(queryString);
TopScoreDocCollector collector = TopScoreDocCollector.create(10, false);
searcher.search(query, collector);
ScoreDoc[] hits = collector.topDocs().scoreDocs;
for(int i = 0 ; i < hits.length ; i ++) {
Document doc = searcher.doc(hits[i].doc);
String name = doc.get(“name”);
if (name != null) {
System.out.println(name);
}
}
如上为一个使用QueryParser查询关键字“kobe”的实例，另外还对查询结果进行了收集
11、使用Lucene图形化工具Luke来操作索引
Luke使用非常简单：
下载：http://code.google.com/p/luke/ 点击下载最新版本，下载完成直接点击下载的jar包，就可以进入图形化操作界面，选择索引的目录就可以对索引进行图形化操作

本文链接地址: Lucene的使用http://www.hongyanliren.com/2014m12/26597.html

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