lucene&IKAnalyzer入门实例

最近研究了下IKAnalyzer，发现果然很强大，而且说明文档很齐全，上手简单，随便写了个例子。留念。

Ikanalyzer是一个分词工具，lucene是全文检索。

IKAnalyzer 和 IKSimilarity 目前都是直接继承了 Lucene，IKQueryParser是一个新的实现类，如果需要修改可以查看IK的源代码(IK源码)。

用户可以指定数据集使用lucene建立索引，再对这些索引进行查询，lucene可以自动对相似度高的进行排序。

在更新索引时，在实例化IndexWriter是可以提供boolean型的参数，判断是否需要覆盖，还是增加。在更新索引时，找到需要更新的索引，删除之，再添加修改后的索引。

在使用扩展词典的时候，按照说明文档上的说法就是UTF-8的无BOM文档，还有个新手提示说要空一行。其实没那么负责的，打开EditPlus，新建一个无BOM的UTF-8文档，直接一行一个词组添加即可，什么都不用加，也不用空行。

package com.ik;

import java.io.File;
import java.io.IOException;
import java.io.Reader;
import java.io.StringReader;
import java.sql.ResultSet;
import java.sql.SQLException;
import java.util.ArrayList;
import java.util.List;

import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
import org.apache.lucene.index.CorruptIndexException;
import org.apache.lucene.index.IndexWriter;
import org.apache.lucene.index.Term;
import org.apache.lucene.search.BooleanQuery;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.Query;
import org.apache.lucene.search.ScoreDoc;
import org.apache.lucene.search.TermQuery;
import org.apache.lucene.search.TopDocs;
import org.apache.lucene.search.Weight;
import org.apache.lucene.search.BooleanClause.Occur;
import org.apache.lucene.store.FSDirectory;
import org.apache.lucene.store.LockObtainFailedException;
import org.wltea.analyzer.IKSegmentation;
import org.wltea.analyzer.Lexeme;
import org.wltea.analyzer.lucene.IKAnalyzer;
import org.wltea.analyzer.lucene.IKQueryParser;
import org.wltea.analyzer.lucene.IKSimilarity;

public class IndexUtil {

// 索引存储路径
private final static String INDEX_PATH = "./myindex";

public void createIndex() {

// 实例化IKAnalyzer分词器
Analyzer analyzer = new IKAnalyzer(true);

IndexWriter iwriter = null;

try {
// 创建索引实例
iwriter = new IndexWriter(FSDirectory.open(new File(INDEX_PATH)),
analyzer, true, IndexWriter.MaxFieldLength.LIMITED);

DB db = DB.getInstance();
db.setDbName("youtee");
db.open();
ResultSet rs = db.select("select * from stadium");

while (rs.next()) {

// 创建Document
Document doc = new Document();

// 添加 field
doc.add(new Field("sid", rs.getString("sid"), Field.Store.YES,
Field.Index.ANALYZED));

doc.add(new Field("name", rs.getString("name"),
Field.Store.YES, Field.Index.ANALYZED));

doc.add(new Field("address", rs.getString("address"),
Field.Store.YES, Field.Index.ANALYZED));

doc.add(new Field("description", rs.getString("description"),
Field.Store.YES, Field.Index.ANALYZED));

iwriter.addDocument(doc);
}

// 执行优化
iwriter.optimize();

// 关闭indexWriter
iwriter.close();

} catch (CorruptIndexException e) {
e.printStackTrace();
} catch (LockObtainFailedException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
} catch (SQLException e) {
e.printStackTrace();
}
}

public List search(String keyword, String field, int returnNum) {
IndexSearcher isearcher = null;
List resultList = new ArrayList();

try {
// 实例化搜索器
isearcher = new IndexSearcher(FSDirectory
.open(new File(INDEX_PATH)), true);

// 在索引器中使用IKSimilarity相似度评估器
isearcher.setSimilarity(new IKSimilarity());

// 使用IKQueryParser查询分析器构造Query对象,fileName->需要搜索的域
// Query query = IKQueryParser.parse(type, keyword);

// 不需要使用分词，只对输入的关键字进行查询
BooleanQuery aBooleanQuery = new BooleanQuery();

String qParts[] = keyword.split("\\s");
for (String q : qParts) {
Query query = new TermQuery(new Term(field, q));
if (query != null
&& (!(query instanceof BooleanQuery) || ((BooleanQuery) query)
.getClauses().length > 0)) {
aBooleanQuery.add(query, Occur.SHOULD);
}
}

// 搜索相似度最高的n条记录
TopDocs topDocs = isearcher.search(aBooleanQuery, returnNum);

returnNum = returnNum <= topDocs.totalHits ? returnNum
: topDocs.totalHits;

System.out.println("命中：" + topDocs.totalHits);

// 输出结果
ScoreDoc[] scoreDocs = topDocs.scoreDocs;

for (int i = 0; i < returnNum; i++) {
Document targetDoc = isearcher.doc(scoreDocs[i].doc);
resultList.add(targetDoc.get(field));

// System.out.println("内容：" + targetDoc.toString());
}

} catch (CorruptIndexException e) {
e.printStackTrace();
} catch (LockObtainFailedException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
} finally {
if (isearcher != null) {
try {
isearcher.close();
} catch (IOException e) {
e.printStackTrace();
}
}
}

return resultList;
}

public static void main(String[] args) {
IndexUtil indexUtil = new IndexUtil();
//		 indexUtil.createIndex();

ArrayList list = (ArrayList) indexUtil.search("体育 中秋", "address", 100);
for (int i = 0; i < list.size(); i++) {
System.out.println(list.get(i));
}

}

public void getSplitWord(String keyword) {
Reader reader = new StringReader(keyword);
IKSegmentation iks = new IKSegmentation(reader, false);

try {
Lexeme lexeme = null;
do {
lexeme = iks.next();
System.out.println(lexeme != null ? lexeme.getLexemeText()
: "++结束++");
} while (lexeme != null);

} catch (IOException e) {
// TODO: handle exception
System.out.println(e.getMessage());
}
}
}