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

• lucenetutorial

• helloLucene