說lucene是Java界的檢索之王,當之無愧。近年來elasticsearch的火爆登場,包括以前的solr及solr cloud,其底層都是lucene。簡單瞭解lucene,對使用elasticsearch仍是有點幫助的。本文就簡單過一下其簡單的api使用。html
<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>
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); }
@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(); }
對於搜索來講,分詞出如今兩個地方,一個是對用戶輸入的關鍵詞進行分詞,另外一個是在索引文檔時對文檔內容的分詞。兩個分詞最好同樣,這樣才能夠更好地匹配出來。java
@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是當前最流行的開源大數據內存計算框架,採用Scala語言實現,由UC伯克利大學AMPLab實驗室開發並於2010年開源。"; 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(); } }
輸出git
spark 是 當前 最 流行 的 開源 大數 據 內存 計算 框架 採用 scala 語言 實現 由 uc 伯克利 大學 amplab 實驗室 開發 並於 2010 年 開源
本工程githubgithub
lucenetutorialapache
helloLuceneapi