原文链接：https://my.oschina.net/qiuzhping/blog/611692

Lucene 5.2.1 + jcseg 1.9.6中文分词索引(Lucene 学习序列2)

       jcseg是使用Java开发的一个开源的中文分词器，使用流行的mmseg算法实现。是一款独立的分词组件，不是针对lucene而开发，但是提供了最新版本的lucene和solr分词接口。

      Java Code

<span style="font-size:14px;">package com.qiuzhping.lucene;

import java.sql.Connection;
import java.sql.ResultSet;
import java.sql.Statement;

import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
import org.apache.lucene.document.StringField;
import org.apache.lucene.document.TextField;
import org.apache.lucene.index.DirectoryReader;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.IndexWriter;
import org.apache.lucene.index.IndexWriterConfig;
import org.apache.lucene.index.IndexWriterConfig.OpenMode;
import org.apache.lucene.queryparser.classic.QueryParser;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.Query;
import org.apache.lucene.search.ScoreDoc;
import org.apache.lucene.search.TopDocs;
import org.apache.lucene.store.Directory;
import org.apache.lucene.store.RAMDirectory;
import org.lionsoul.jcseg.analyzer.JcsegAnalyzer5X;
import org.lionsoul.jcseg.core.JcsegTaskConfig;

/**
 * <Description functions in a word>
 * Jcseg[dʒɛ'ke'sɛ]是使用Java开发的一个开源中文分词器，使用流行的mmseg算法实现，<BR>
 * 并且提供了最高版本的lucene, solr, elasticsearch(New)的分词接口．<BR>
 * 本程序测试的是jcseg 1.9.6,Lucene:5.2.1<BR>
 * 关于Jcseg介绍详细请参看 http://www.oschina.net/p/jcseg
 * <Detail description>
 * 
 * @author  Peter.Qiu
 * @version  [Version NO, 2015年7月31日]
 * @see  [Related classes/methods]
 * @since  [product/module version]
 */
public class LuceneChineseSplit {
	
	public static void main(String[] args) throws Exception {
		Analyzer analyzer = new JcsegAnalyzer5X(JcsegTaskConfig.COMPLEX_MODE);
		// 非必须(用于修改默认配置): 获取分词任务配置实例
		JcsegAnalyzer5X jcseg = (JcsegAnalyzer5X) analyzer;
		JcsegTaskConfig config = jcseg.getTaskConfig();
		// 追加同义词到分词结果中, 需要在 jcseg.properties 中配置 jcseg.loadsyn=1
		config.setAppendCJKSyn(true);
		// 追加拼音到分词结果中, 需要在 jcseg.properties 中配置 jcseg.loadpinyin=1
		config.setAppendCJKPinyin(true);
		// 更多配置, 请查看 com.webssky.jcseg.core.JcsegTaskConfig 类
		// ====建立索引
		// 建立内存索引对象
		Directory directory = new RAMDirectory();
		IndexWriterConfig iwConfig = new IndexWriterConfig(analyzer);
		iwConfig.setOpenMode(OpenMode.CREATE_OR_APPEND);
		IndexWriter iwriter = new IndexWriter(directory, iwConfig);
		
		Connection conn = QueryDataFromDb.getConnection();
		Statement st = conn.createStatement();
		long count = 0;
		for(int i = 0 ; i < 10; i ++){
			String query = "select * from student limit "+ i * 100000+","+ 100000;
			ResultSet result = st.executeQuery(query);
			while (result.next()) {
				Document document = new Document();
				document.add(new StringField("id", result.getString("id"),
						Field.Store.YES));
				document.add(new TextField("name", result
						.getString("name"), Field.Store.YES));
				document.add(new StringField("math", result
						.getString("math"), Field.Store.YES));
				iwriter.addDocument(document);
				count ++;
			}
		}			
		System.out.println("Total record : "+count);
		
		iwriter.commit();
		iwriter.close();

		// ==搜索
		IndexReader ireader = DirectoryReader.open(directory);
		IndexSearcher isearcher = new IndexSearcher(ireader);
		String keyword = "你好";
		// 使用QueryParser查询分析器构造Query对象
		QueryParser qp = new QueryParser("name", analyzer);
		qp.setDefaultOperator(QueryParser.AND_OPERATOR);
		Query query = qp.parse(keyword);
		System.out.println("Query = " + query);
		long start = System.currentTimeMillis();
		//搜索相似度最高的2条记录
		System.out.println("搜索相似度最高的2条记录");
		TopDocs topDocs = isearcher.search(query, 2);
		System.out.println("命中：" + topDocs.totalHits);
		for (ScoreDoc sd : topDocs.scoreDocs) {
			Document doc = isearcher.doc(sd.doc);
			System.out.println("id:" + doc.get("id"));
			System.out.println("name:" + doc.get("name"));
			System.out.println("math:" + doc.get("math"));
		}
		System.out.println("Spend time:"+(System.currentTimeMillis() - start) + " ms");
	}
}
</span>

测试结果：

Total record : 1000000
Query = name:你好
搜索相似度最高的2条记录
命中：1000000
id:1
name:你好
math:38
id:2
name:你好
math:21
Spend time:52 ms

代码片段涉及到：

lucene-analyzers-common-5.2.1.jar

lucene-core-5.2.1.jar

lucene-queryparser-5.2.1.jar

mysql-connector-java-5.1.35.jar

jcseg-analyzer-1.9.6.jar

jcseg-core-1.9.6.jar

关于数据库操作的可以参考上一篇文章：

Lucene 4.10 + Mysql 5.5 创建数据库表索引(Lucene 学习序列1)

转载于:https://my.oschina.net/qiuzhping/blog/611692