lucene 分词器分析

lucene的Analyzer类里面主要包含这个方法：

public abstract class Analyzer{

 public abstract TokenStream tokenStream(String fieldName, Reader reader);

}

-------------------------------------------------------------------

public abstract class TokenStream {
                ......
 public Token next(final Token reusableToken) throws IOException {
    // We don't actually use inputToken, but still add this assert
    assert reusableToken != null;
    return next();
  }
               ......
}

所有要实现analyzer的类都要重写这个方法，获取自己制定的Tokenizer(Tokenizer继承于TokenStream)。而分词的主要方法就是TokenStream里面提供的next()方法，所有继承TokenStream类的方法都要重写这个next()方法，以制定自己分词器。

//下面分析一下StandAnalyzer,它继承于Analyzer，StandAnalyzer里面的tokenStream方法如下：
public class StandardAnalyzer extends Analyzer {
                 ......
  public TokenStream tokenStream(String fieldName, Reader reader) {
    StandardTokenizer tokenStream = new StandardTokenizer(reader, replaceInvalidAcronym);  //使用了StandardTokenizer
    tokenStream.setMaxTokenLength(maxTokenLength);
    TokenStream result = new StandardFilter(tokenStream);
    result = new LowerCaseFilter(result);
    result = new StopFilter(result, stopSet);
    return result;
  }

}
-----------------------------------------------------------------
//StandardTokenizer的next方法如下：
public class StandardTokenizer extends Tokenizer {
              .......
public Token next(final Token reusableToken) throws IOException {
      assert reusableToken != null;
      int posIncr = 1;

      while(true) {
	int tokenType = scanner.getNextToken();

	if (tokenType == StandardTokenizerImpl.YYEOF) {
	    return null;
	}

        if (scanner.yylength() <= maxTokenLength) {
          reusableToken.clear();
          reusableToken.setPositionIncrement(posIncr);
          scanner.getText(reusableToken);
          final int start = scanner.yychar();
          reusableToken.setStartOffset(start);
          reusableToken.setEndOffset(start+reusableToken.termLength());
          // This 'if' should be removed in the next release. For now, it converts
          // invalid acronyms to HOST. When removed, only the 'else' part should
          // remain.
          if (tokenType == StandardTokenizerImpl.ACRONYM_DEP) {
            if (replaceInvalidAcronym) {
              reusableToken.setType(StandardTokenizerImpl.TOKEN_TYPES[StandardTokenizerImpl.HOST]);
              reusableToken.setTermLength(reusableToken.termLength() - 1); // remove extra '.'
            } else {
              reusableToken.setType(StandardTokenizerImpl.TOKEN_TYPES[StandardTokenizerImpl.ACRONYM]);
            }
          } else {
            reusableToken.setType(StandardTokenizerImpl.TOKEN_TYPES[tokenType]);
          }
          return reusableToken;
        } else
          // When we skip a too-long term, we still increment the
          // position increment
          posIncr++;
      }
    }
               ......
}

测试代码：

public class TestAnalyzer {

	final static String TEXT = "hadoop is very good,xina a tooken finished!"; 

	@SuppressWarnings("deprecation")
	public void testTokenizer() throws IOException{
		Reader reader = new StringReader(TEXT);
		StandardTokenizer tokenizer = new StandardTokenizer(reader);
		for (Token t = tokenizer.next();t!=null;t = tokenizer.next()) {
			System.out.println(t.startOffset() +"--" + t.endOffset() + ": "+ t.termText());
		}
	}

	public static void main(String[] args) throws IOException {
		TestAnalyzer t = new TestAnalyzer();
		t.testTokenizer();
	}
}

//lucene2.4.1新API的测试用法：
		TokenStream ts = analyzer.tokenStream("text", new StringReader(txt));
		for(Token t= new Token(); (t=ts.next(t)) !=null;) {
			System.out.println(t);
		}