首先介紹一個jdbc工具類,用於得到Connection對象:
- import java.sql.Connection;
- import java.sql.DriverManager;
- import java.sql.SQLException;
- /**
- * JdbcUtil.java
- * @version 1.0
- * @createTime JDBC獲取Connection工具類
- */
- public class JdbcUtil {
- private static Connection conn = null;
- private static final String URL = "jdbc:mysql://127.0.0.1/project?autoReconnect=true&characterEncoding=utf8";
- private static final String JDBC_DRIVER = "com.mysql.jdbc.Driver";
- private static final String USER_NAME = "root";
- private static final String PASSWORD = "";
- public static Connection getConnection() {
- try {
- Class.forName(JDBC_DRIVER);
- conn = DriverManager.getConnection(URL, USER_NAME, PASSWORD);
- } catch (ClassNotFoundException e) {
- e.printStackTrace();
- } catch (SQLException e) {
- e.printStackTrace();
- }
- return conn;
- }
- }
然後就是本文的主要內容了,對數據庫信息進行索引與對索引進行搜索:
- import java.io.File;
- import java.sql.Connection;
- import java.sql.ResultSet;
- import java.sql.Statement;
- 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.document.Field.TermVector;
- import org.apache.lucene.index.IndexWriter;
- import org.apache.lucene.queryParser.QueryParser;
- import org.apache.lucene.search.*;
- import org.apache.lucene.store.Directory;
- import org.apache.lucene.store.FSDirectory;
- import org.apache.lucene.util.Version;
- import org.wltea.analyzer.lucene.IKAnalyzer;
- import org.wltea.analyzer.lucene.IKSimilarity;
- /**
- * SearchLogic.java
- * @version 1.0
- * @createTime Lucene數據庫檢索
- */
- public class SearchLogic {
- private static Connection conn = null;
- private static Statement stmt = null;
- private static ResultSet rs = null;
- private String searchDir = "E:\\Test\\Index";
- private static File indexFile = null;
- private static Searcher searcher = null;
- private static Analyzer analyzer = null;
- /** 索引頁面緩衝 */
- private int maxBufferedDocs = 500;
- /**
- * 獲取數據庫數據
- * @return ResultSet
- * @throws Exception
- */
- public List<SearchBean> getResult(String queryStr) throws Exception {
- List<SearchBean> result = null;
- conn = JdbcUtil.getConnection();
- if(conn == null) {
- throw new Exception("數據庫連接失敗!");
- }
- String sql = "select id, username, password, type from account";
- try {
- stmt = conn.createStatement();
- rs = stmt.executeQuery(sql);
- this.createIndex(rs); //給數據庫創建索引,此處執行一次,不要每次運行都創建索引,以後數據有更新可以後臺調用更新索引
- TopDocs topDocs = this.search(queryStr);
- ScoreDoc[] scoreDocs = topDocs.scoreDocs;
- result = this.addHits2List(scoreDocs);
- } catch(Exception e) {
- e.printStackTrace();
- throw new Exception("數據庫查詢sql出錯! sql : " + sql);
- } finally {
- if(rs != null) rs.close();
- if(stmt != null) stmt.close();
- if(conn != null) conn.close();
- }
- return result;
- }
- /**
- * 爲數據庫檢索數據創建索引
- * @param rs
- * @throws Exception
- */
- private void createIndex(ResultSet rs) throws Exception {
- Directory directory = null;
- IndexWriter indexWriter = null;
- try {
- indexFile = new File(searchDir);
- if(!indexFile.exists()) {
- indexFile.mkdir();
- }
- directory = FSDirectory.open(indexFile);
- analyzer = new IKAnalyzer();
- indexWriter = new IndexWriter(directory, analyzer, true, IndexWriter.MaxFieldLength.UNLIMITED);
- indexWriter.setMaxBufferedDocs(maxBufferedDocs);
- Document doc = null;
- while(rs.next()) {
- doc = new Document();
- Field id = new Field("id", String.valueOf(rs.getInt("id")), Field.Store.YES, Field.Index.NOT_ANALYZED, TermVector.NO);
- Field username = new Field("username", rs.getString("username") == null ? "" : rs.getString("username"), Field.Store.YES,Field.Index.ANALYZED, TermVector.NO);
- doc.add(id);
- doc.add(username);
- indexWriter.addDocument(doc);
- }
- indexWriter.optimize();
- indexWriter.close();
- } catch(Exception e) {
- e.printStackTrace();
- }
- }
- /**
- * 搜索索引
- * @param queryStr
- * @return
- * @throws Exception
- */
- private TopDocs search(String queryStr) throws Exception {
- if(searcher == null) {
- indexFile = new File(searchDir);
- searcher = new IndexSearcher(FSDirectory.open(indexFile));
- }
- searcher.setSimilarity(new IKSimilarity());
- QueryParser parser = new QueryParser(Version.LUCENE_30,"username",new IKAnalyzer());
- Query query = parser.parse(queryStr);
- TopDocs topDocs = searcher.search(query, searcher.maxDoc());
- return topDocs;
- }
- /**
- * 返回結果並添加到List中
- * @param scoreDocs
- * @return
- * @throws Exception
- */
- private List<SearchBean> addHits2List(ScoreDoc[] scoreDocs ) throws Exception {
- List<SearchBean> listBean = new ArrayList<SearchBean>();
- SearchBean bean = null;
- for(int i=0 ; i<scoreDocs.length; i++) {
- int docId = scoreDocs[i].doc;
- Document doc = searcher.doc(docId);
- bean = new SearchBean();
- bean.setId(doc.get("id"));
- bean.setUsername(doc.get("username"));
- listBean.add(bean);
- }
- return listBean;
- }
- public static void main(String[] args) {
- SearchLogic logic = new SearchLogic();
- try {
- Long startTime = System.currentTimeMillis();
- List<SearchBean> result = logic.getResult("商家");
- int i = 0;
- for(SearchBean bean : result) {
- if(i == 10)
- break;
- System.out.println("bean.name " + bean.getClass().getName() + " : bean.id " + bean.getId()+ " : bean.username " + bean.getUsername());
- i++;
- }
- System.out.println("searchBean.result.size : " + result.size());
- Long endTime = System.currentTimeMillis();
- System.out.println("查詢所花費的時間爲:" + (endTime-startTime)/1000);
- } catch (Exception e) {
- e.printStackTrace();
- System.out.println(e.getMessage());
- }
- }
- }
對了上面的類還用到了一個javabean類,如下:
- public class SearchBean {
- private String id;
- private String username;
- public String getId() {
- return id;
- }
- public void setId(String id) {
- this.id = id;
- }
- public String getUsername() {
- return username;
- }
- public void setUsername(String username) {
- this.username = username;
- }
- }
這些代碼大部分都是我在網上找到的doc文檔中複製粘貼而來,本着“拿來主義”,我對這些代碼修改不大,經測試,這些代碼能夠正常運行。
寫了幾篇博客,對lucene的使用方式也越來越清楚,在這裏也很有必要總結一下:
使用lucene包括兩個步驟,分別是索引和搜索。
•索引過程如下:
◦ 創建一個IndexWriter用來寫索引文件,它有幾個參數,INDEX_DIR就是索引文件所存放的位置,Analyzer便是用來對文檔進行詞法分析和語言處理的。
◦ 創建一個Document代表我們要索引的文檔。
◦ 將不同的Field加入到文檔中。我們知道,一篇文檔有多種信息,如題目,作者,修改時間,內容等。不同類型的信息用不同的Field來表示。
◦ IndexWriter調用函數addDocument將索引寫到索引文件夾中。
•搜索過程如下:
◦ IndexReader將磁盤上的索引信息讀入到內存,INDEX_DIR就是索引文件存放的位置。
◦ 創建IndexSearcher準備進行搜索。
◦ 創建Analyer用來對查詢語句進行詞法分析和語言處理。
◦ 創建QueryParser用來對查詢語句進行語法分析。
◦ QueryParser調用parser進行語法分析,形成查詢語法樹,放到Query中。
◦ IndexSearcher調用search對查詢語法樹Query進行搜索,得到結果TopScoreDocCollector。
對了,必須說一下,上面的例子還用到了一個新的jar包IKAnalyzer.jar包,它是一個開源的中文分詞器,如果不使用這個分詞器,那麼將無法解析中文,比如說我的第一篇關於Lucene的博客就無法解析中文字符串!