public static Analyzer getLoggingAnalyzer(Analyzer child,
    PrintStream log,
    String logName) 
{
    
    if (child == null) 
      throw new IllegalArgumentException("child analyzer must not be null");
    if (log == null) 
      throw new IllegalArgumentException("logStream must not be null");
    return new Analyzer() {
      public TokenStream tokenStream(final String fieldName, Reader reader) {
        return new TokenFilter(child.tokenStream(fieldName, reader)) {
          private int position = -1;
          public Token next() throws IOException {
            Token token = input.next(); // from filter super class
            log.println(toString(token));
            return token;
          }
          private String toString(Token token) {
            if (token == null) return "[" + logName + ":EOS:" + fieldName + "]\n";
            position += token.getPositionIncrement();
            return "[" + logName + ":" + position + ":" + fieldName + ":"
                + token.termText() + ":" + token.startOffset()
                + "-" + token.endOffset() + ":" + token.type()
                + "]";
          }         
        };
      }
    };
}

Returns a simple analyzer wrapper that logs all tokens produced by the underlying child analyzer to the given log stream (typically System.err); Otherwise behaves exactly like the child analyzer, delivering the very same tokens; useful for debugging purposes on custom indexing and/or querying.

 public static Analyzer getMaxTokenAnalyzer(Analyzer child,
    int maxTokens) 
{
    
    if (child == null) 
      throw new IllegalArgumentException("child analyzer must not be null");
    if (maxTokens <  0) 
      throw new IllegalArgumentException("maxTokens must not be negative");
    if (maxTokens == Integer.MAX_VALUE) 
      return child; // no need to wrap
    return new Analyzer() {
      public TokenStream tokenStream(String fieldName, Reader reader) {
        return new TokenFilter(child.tokenStream(fieldName, reader)) {
          private int todo = maxTokens;
          public Token next() throws IOException {
            return --todo  >= 0 ? input.next() : null;
          }
        };
      }
    };
}

Returns an analyzer wrapper that returns at most the first maxTokens tokens from the underlying child analyzer, ignoring all remaining tokens.

 public static String[] getMostFrequentTerms(Analyzer analyzer,
    String text,
    int limit) 
{
    if (analyzer == null) 
      throw new IllegalArgumentException("analyzer must not be null");
    if (text == null) 
      throw new IllegalArgumentException("text must not be null");
    if (limit < = 0) limit = Integer.MAX_VALUE;
    // compute frequencies of distinct terms
    HashMap map = new HashMap();
    TokenStream stream = analyzer.tokenStream("", new StringReader(text));
    try {
      Token token;
      while ((token = stream.next()) != null) {
        MutableInteger freq = (MutableInteger) map.get(token.termText());
        if (freq == null) {
          freq = new MutableInteger(1);
          map.put(token.termText(), freq);
        } else {
          freq.setValue(freq.intValue() + 1);
        }
      }
    } catch (IOException e) {
      throw new RuntimeException(e);
    } finally {
      try {
        stream.close();
      } catch (IOException e2) {
        throw new RuntimeException(e2);
      }
    }
    // sort by frequency, text
    Map.Entry[] entries = new Map.Entry[map.size()];
    map.entrySet().toArray(entries);
    Arrays.sort(entries, new Comparator() {
      public int compare(Object o1, Object o2) {
        Map.Entry e1 = (Map.Entry) o1;
        Map.Entry e2 = (Map.Entry) o2;
        int f1 = ((MutableInteger) e1.getValue()).intValue();
        int f2 = ((MutableInteger) e2.getValue()).intValue();
        if (f2 - f1 != 0) return f2 - f1;
        String s1 = (String) e1.getKey();
        String s2 = (String) e2.getKey();
        return s1.compareTo(s2);
      }
    });
    // return top N entries
    int size = Math.min(limit, entries.length);
    String[] pairs = new String[size];
    for (int i=0; i <  size; i++) {
      pairs[i] = entries[i].getValue() + ":" + entries[i].getKey();
    }
    return pairs;
}

Returns (frequency:term) pairs for the top N distinct terms (aka words), sorted descending by frequency (and ascending by term, if tied).

Example XQuery:

declare namespace util = "java:org.apache.lucene.index.memory.AnalyzerUtil";
declare namespace analyzer = "java:org.apache.lucene.index.memory.PatternAnalyzer";

for $pair in util:get-most-frequent-terms(
analyzer:EXTENDED_ANALYZER(), doc("samples/shakespeare/othello.xml"), 10)
return <word word="{substring-after($pair, ':')}" frequency="{substring-before($pair, ':')}"/>

 public static String[] getParagraphs(String text,
    int limit) 
{
  
    return tokenize(PARAGRAPHS, text, limit);
}

Returns at most the first N paragraphs of the given text. Delimiting characters are excluded from the results. Each returned paragraph is whitespace-trimmed via String.trim(), potentially an empty string.

 public static Analyzer getPorterStemmerAnalyzer(Analyzer child) 
{
    
    if (child == null) 
      throw new IllegalArgumentException("child analyzer must not be null");
    return new Analyzer() {
      public TokenStream tokenStream(String fieldName, Reader reader) {
        return new PorterStemFilter(
            child.tokenStream(fieldName, reader));
//        /* PorterStemFilter and SnowballFilter have the same behaviour, 
//        but PorterStemFilter is much faster. */
//        return new org.apache.lucene.analysis.snowball.SnowballFilter(
//            child.tokenStream(fieldName, reader), "English");
      }
    };
}

Returns an English stemming analyzer that stems tokens from the underlying child analyzer according to the Porter stemming algorithm. The child analyzer must deliver tokens in lower case for the stemmer to work properly.

Background: Stemming reduces token terms to their linguistic root form e.g. reduces "fishing" and "fishes" to "fish", "family" and "families" to "famili", as well as "complete" and "completion" to "complet". Note that the root form is not necessarily a meaningful word in itself, and that this is not a bug but rather a feature, if you lean back and think about fuzzy word matching for a bit.

See the Lucene contrib packages for stemmers (and stop words) for German, Russian and many more languages.

 public static String[] getSentences(String text,
    int limit) 
{
                                                                                                
//    return tokenize(SENTENCES, text, limit); // equivalent but slower
    int len = text.length();
    if (len == 0) return new String[] { text };
    if (limit < = 0) limit = Integer.MAX_VALUE;
    // average sentence length heuristic
    String[] tokens = new String[Math.min(limit, 1 + len/40)];
    int size = 0;
    int i = 0;
    while (i <  len && size <  limit) {
      // scan to end of current sentence
      int start = i;
      while (i <  len && !isSentenceSeparator(text.charAt(i))) i++;
      if (size == tokens.length) { // grow array
        String[] tmp = new String[tokens.length < <  1];
        System.arraycopy(tokens, 0, tmp, 0, size);
        tokens = tmp;
      }
      // add sentence (potentially empty)
      tokens[size++] = text.substring(start, i).trim();
      // scan to beginning of next sentence
      while (i <  len && isSentenceSeparator(text.charAt(i))) i++;
    }
    if (size == tokens.length) return tokens;
    String[] results = new String[size];
    System.arraycopy(tokens, 0, results, 0, size);
    return results;
}

Returns at most the first N sentences of the given text. Delimiting characters are excluded from the results. Each returned sentence is whitespace-trimmed via String.trim(), potentially an empty string.

 public static Analyzer getSynonymAnalyzer(Analyzer child,
    SynonymMap synonyms,
    int maxSynonyms) 
{
    
    if (child == null) 
      throw new IllegalArgumentException("child analyzer must not be null");
    if (synonyms == null)
      throw new IllegalArgumentException("synonyms must not be null");
    if (maxSynonyms <  0) 
      throw new IllegalArgumentException("maxSynonyms must not be negative");
    if (maxSynonyms == 0)
      return child; // no need to wrap
    return new Analyzer() {
      public TokenStream tokenStream(String fieldName, Reader reader) {
        return new SynonymTokenFilter(
          child.tokenStream(fieldName, reader), synonyms, maxSynonyms);
      }
    };
}

Returns an analyzer wrapper that wraps the underlying child analyzer's token stream into a SynonymTokenFilter .

 public static Analyzer getTokenCachingAnalyzer(Analyzer child) 
{
    if (child == null)
      throw new IllegalArgumentException("child analyzer must not be null");
    return new Analyzer() {
      private final HashMap cache = new HashMap();
      public TokenStream tokenStream(String fieldName, Reader reader) {
        final ArrayList tokens = (ArrayList) cache.get(fieldName);
        if (tokens == null) { // not yet cached
          final ArrayList tokens2 = new ArrayList();
          TokenStream tokenStream = new TokenFilter(child.tokenStream(fieldName, reader)) {
            public Token next() throws IOException {
              Token token = input.next(); // from filter super class
              if (token != null) tokens2.add(token);
              return token;
            }
          };
          cache.put(fieldName, tokens2);
          return tokenStream;
        } else { // already cached
          return new TokenStream() {
            private Iterator iter = tokens.iterator();
            public Token next() {
              if (!iter.hasNext()) return null;
              return (Token) iter.next();
            }
          };
        }
      }
    };
}

Returns an analyzer wrapper that caches all tokens generated by the underlying child analyzer's token streams, and delivers those cached tokens on subsequent calls to tokenStream(String fieldName, Reader reader) if the fieldName has been seen before, altogether ignoring the Reader parameter on cache lookup.

If Analyzer / TokenFilter chains are expensive in terms of I/O or CPU, such caching can help improve performance if the same document is added to multiple Lucene indexes, because the text analysis phase need not be performed more than once.

Caveats:

• Caching the tokens of large Lucene documents can lead to out of memory exceptions.
• The Token instances delivered by the underlying child analyzer must be immutable.
• The same caching analyzer instance must not be used for more than one document because the cache is not keyed on the Reader parameter.