## org.apache.lucene.search.highlight
Class Highlighter

    java.lang.Object
      org.apache.lucene.search.highlight.Highlighter

    public class Highlighter

extends Object

Class used to markup highlighted terms found in the best sections of a text, using configurable `Fragmenter`, `Scorer`, `Formatter`, `Encoder` and tokenizers.

Field Summary
`static int` `DEFAULT_MAX_CHARS_TO_ANALYZE`

Constructor Summary
`Highlighter(Formatter formatter, Encoder encoder, Scorer fragmentScorer)`
`Highlighter(Formatter formatter, Scorer fragmentScorer)`
`Highlighter(Scorer fragmentScorer)`

Method Summary
`String` `getBestFragment(Analyzer analyzer, String fieldName, String text)` Highlights chosen terms in a text, extracting the most relevant section.
`String` `getBestFragment(TokenStream tokenStream, String text)` Highlights chosen terms in a text, extracting the most relevant section.
`String[]` `getBestFragments(Analyzer analyzer, String fieldName, String text, int maxNumFragments)` Highlights chosen terms in a text, extracting the most relevant sections.
`String[]` `getBestFragments(TokenStream tokenStream, String text, int maxNumFragments)` Highlights chosen terms in a text, extracting the most relevant sections.
`String` `getBestFragments(TokenStream tokenStream, String text, int maxNumFragments, String separator)` Highlights terms in the text , extracting the most relevant sections and concatenating the chosen fragments with a separator (typically "...").
`TextFragment[]` `getBestTextFragments(TokenStream tokenStream, String text, boolean mergeContiguousFragments, int maxNumFragments)` Low level api to get the most relevant (formatted) sections of the document.
`Encoder` `getEncoder()`
`Scorer` `getFragmentScorer()`
`int` `getMaxDocCharsToAnalyze()`
`Fragmenter` `getTextFragmenter()`
`void` `setEncoder(Encoder encoder)`
`void` `setFragmentScorer(Scorer scorer)`
`void` `setMaxDocCharsToAnalyze(int maxDocCharsToAnalyze)`
`void` `setTextFragmenter(Fragmenter fragmenter)`

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Field Detail

### DEFAULT_MAX_CHARS_TO_ANALYZE

    public static final int DEFAULT_MAX_CHARS_TO_ANALYZE

See Also:
  Constant Field Values

Constructor Detail

### Highlighter

    public Highlighter(Scorer fragmentScorer)

### Highlighter

    public Highlighter(Formatter formatter,
                       Scorer fragmentScorer)

### Highlighter

    public Highlighter(Formatter formatter,
                       Encoder encoder,
                       Scorer fragmentScorer)

Method Detail

### getBestFragment

    public final String getBestFragment(Analyzer analyzer,
                                        String fieldName,
                                        String text)
                                 throws IOException,
                                        InvalidTokenOffsetsException

  Highlights chosen terms in a text, extracting the most relevant section. This is a convenience method that calls `getBestFragment(TokenStream, String)`

  Parameters:
    `analyzer` - the analyzer that will be used to split `text` into chunks
    `text` - text to highlight terms in
    `fieldName` - Name of field used to influence analyzer's tokenization policy
  Returns:
    highlighted text fragment or null if no terms found
  Throws:
    `InvalidTokenOffsetsException` - thrown if any token's endOffset exceeds the provided text's length
    `IOException`

### getBestFragment

    public final String getBestFragment(TokenStream tokenStream,
                                        String text)
                                 throws IOException,
                                        InvalidTokenOffsetsException

  Highlights chosen terms in a text, extracting the most relevant section. The document text is analysed in chunks to record hit statistics across the document. After accumulating stats, the fragment with the highest score is returned

  Parameters:
    `tokenStream` - a stream of tokens identified in the text parameter, including offset information. This is typically produced by an analyzer re-parsing a document's text. Some work may be done on retrieving TokenStreams more efficiently by adding support for storing original text position data in the Lucene index but this support is not currently available (as of Lucene 1.4 rc2).
    `text` - text to highlight terms in
  Returns:
    highlighted text fragment or null if no terms found
  Throws:
    `InvalidTokenOffsetsException` - thrown if any token's endOffset exceeds the provided text's length
    `IOException`

### getBestFragments

    public final String[] getBestFragments(Analyzer analyzer,
                                           String fieldName,
                                           String text,
                                           int maxNumFragments)
                                    throws IOException,
                                           InvalidTokenOffsetsException

  Highlights chosen terms in a text, extracting the most relevant sections. This is a convenience method that calls `getBestFragments(TokenStream, String, int)`

  Parameters:
    `analyzer` - the analyzer that will be used to split `text` into chunks
    `fieldName` - the name of the field being highlighted (used by analyzer)
    `text` - text to highlight terms in
    `maxNumFragments` - the maximum number of fragments.
  Returns:
    highlighted text fragments (between 0 and maxNumFragments number of fragments)
  Throws:
    `InvalidTokenOffsetsException` - thrown if any token's endOffset exceeds the provided text's length
    `IOException`

### getBestFragments

    public final String[] getBestFragments(TokenStream tokenStream,
                                           String text,
                                           int maxNumFragments)
                                    throws IOException,
                                           InvalidTokenOffsetsException

  Highlights chosen terms in a text, extracting the most relevant sections. The document text is analysed in chunks to record hit statistics across the document. After accumulating stats, the fragments with the highest scores are returned as an array of strings in order of score (contiguous fragments are merged into one in their original order to improve readability)

  Parameters:
    `text` - text to highlight terms in
    `maxNumFragments` - the maximum number of fragments.
  Returns:
    highlighted text fragments (between 0 and maxNumFragments number of fragments)
  Throws:
    `InvalidTokenOffsetsException` - thrown if any token's endOffset exceeds the provided text's length
    `IOException`

### getBestTextFragments

    public final TextFragment[] getBestTextFragments(TokenStream tokenStream,
                                                     String text,
                                                     boolean mergeContiguousFragments,
                                                     int maxNumFragments)
                                              throws IOException,
                                                     InvalidTokenOffsetsException

  Low level api to get the most relevant (formatted) sections of the document. This method has been made public to allow visibility of score information held in TextFragment objects. Thanks to Jason Calabrese for help in redefining the interface.

  Throws:
    `IOException` - If there is a low-level I/O error
    `InvalidTokenOffsetsException` - thrown if any token's endOffset exceeds the provided text's length

### getBestFragments

    public final String getBestFragments(TokenStream tokenStream,
                                         String text,
                                         int maxNumFragments,
                                         String separator)
                                  throws IOException,
                                         InvalidTokenOffsetsException

  Highlights terms in the text , extracting the most relevant sections and concatenating the chosen fragments with a separator (typically "..."). The document text is analysed in chunks to record hit statistics across the document. After accumulating stats, the fragments with the highest scores are returned in order as "separator" delimited strings.

  Parameters:
    `text` - text to highlight terms in
    `maxNumFragments` - the maximum number of fragments.
    `separator` - the separator used to intersperse the document fragments (typically "...")
  Returns:
    highlighted text
  Throws:
    `InvalidTokenOffsetsException` - thrown if any token's endOffset exceeds the provided text's length
    `IOException`

### getMaxDocCharsToAnalyze

    public int getMaxDocCharsToAnalyze()

### setMaxDocCharsToAnalyze

    public void setMaxDocCharsToAnalyze(int maxDocCharsToAnalyze)

### getTextFragmenter

    public Fragmenter getTextFragmenter()

### setTextFragmenter

    public void setTextFragmenter(Fragmenter fragmenter)

### getFragmentScorer

    public Scorer getFragmentScorer()

  Returns:
    Object used to score each text fragment

### setFragmentScorer

    public void setFragmentScorer(Scorer scorer)

### getEncoder

    public Encoder getEncoder()

### setEncoder

    public void setEncoder(Encoder encoder)

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