lucene简单入门
序
说lucene是Java界的检索之王，当之无愧。近年来elasticsearch的火爆登场，包括之前的solr及solr cloud，其底层都是lucene。简单了解lucene，对使用elasticsearch还是有点帮助的。本文就简单过一下其简单的api使用。
添加依赖
<dependency> <groupId>org.apache.lucene</groupId> <artifactId>lucene-core</artifactId> <version>4.6.1</version> </dependency> <dependency> <groupId>org.apache.lucene</groupId> <artifactId>lucene-analyzers-common</artifactId> <version>4.6.1</version> </dependency> <dependency> <groupId>org.apache.lucene</groupId> <artifactId>lucene-queryparser</artifactId> <version>4.6.1</version> </dependency> <dependency> <groupId>org.apache.lucene</groupId> <artifactId>lucene-codecs</artifactId> <version>4.6.1</version> </dependency>索引与检索
创建索引
File indexDir = new File(this.getClass().getClassLoader().getResource("").getFile()); @Test public void createIndex() throws IOException { // Directory index = new RAMDirectory(); Directory index = FSDirectory.open(indexDir); // 0. Specify the analyzer for tokenizing text. // The same analyzer should be used for indexing and searching StandardAnalyzer analyzer = new StandardAnalyzer(Version.LUCENE_46); IndexWriterConfig config = new IndexWriterConfig(Version.LUCENE_46, analyzer); // 1. create the index IndexWriter w = new IndexWriter(index, config); addDoc(w, "Lucene in Action", "193398817"); addDoc(w, "Lucene for Dummies", "55320055Z"); addDoc(w, "Managing Gigabytes", "55063554A"); addDoc(w, "The Art of Computer Science", "9900333X"); w.close(); } private void addDoc(IndexWriter w, String title, String isbn) throws IOException { Document doc = new Document(); doc.add(new TextField("title", title, Field.Store.YES)); // use a string field for isbn because we don't want it tokenized doc.add(new StringField("isbn", isbn, Field.Store.YES)); w.addDocument(doc); }检索
@Test public void search() throws IOException { // 2. query String querystr = "lucene"; // the "title" arg specifies the default field to use // when no field is explicitly specified in the query. Query q = null; try { StandardAnalyzer analyzer = new StandardAnalyzer(Version.LUCENE_46); q = new QueryParser(Version.LUCENE_46,"title", analyzer).parse(querystr); } catch (Exception e) { e.printStackTrace(); } // 3. search int hitsPerPage = 10; Directory index = FSDirectory.open(indexDir); IndexReader reader = DirectoryReader.open(index); IndexSearcher searcher = new IndexSearcher(reader); TopScoreDocCollector collector = TopScoreDocCollector.create(hitsPerPage, true); searcher.search(q, collector); ScoreDoc[] hits = collector.topDocs().scoreDocs; // 4. display results System.out.println("Found " + hits.length + " hits."); for (int i = 0; i < hits.length; ++i) { int docId = hits[i].doc; Document d = searcher.doc(docId); System.out.println((i + 1) + ". " + d.get("isbn") + "/t" + d.get("title")); } // reader can only be closed when there // is no need to access the documents any more. reader.close(); }分词
对于搜索来说，分词出现在两个地方，一个是对用户输入的关键词进行分词，另一个是在索引文档时对文档内容的分词。两个分词最好一样，这样才可以更好地匹配出来。
@Test public void cutWords() throws IOException { // StandardAnalyzer analyzer = new StandardAnalyzer(Version.LUCENE_46); // CJKAnalyzer analyzer = new CJKAnalyzer(Version.LUCENE_46); SimpleAnalyzer analyzer = new SimpleAnalyzer(); String text = "Spark是当前最流行的开源大数据内存计算框架，采用Scala语言实现，由UC伯克利大学AMPLab实验室开发并于2010年开源。"; TokenStream tokenStream = analyzer.tokenStream("content", new StringReader(text)); CharTermAttribute charTermAttribute = tokenStream.addAttribute(CharTermAttribute.class); try { tokenStream.reset(); while (tokenStream.incrementToken()) { System.out.println(charTermAttribute.toString()); } tokenStream.end(); } finally { tokenStream.close(); analyzer.close(); } }输出
spark 是 当前 最 流行 的 开源 大数 据 内存 计算 框架 采用 scala 语言 实现 由 uc 伯克利 大学 amplab 实验室 开发 并于 2010 年 开源本工程 github
参考
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lucenetutorial
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helloLucene
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