Package org.apache.lucene.analysis

# Class Analyzer

java.lang.Object
org.apache.lucene.analysis.Analyzer

All Implemented Interfaces:
  `Closeable`, `AutoCloseable`

Direct Known Subclasses:
  `AnalyzerWrapper`, `StopwordAnalyzerBase`

public abstract class Analyzer extends Object implements Closeable
An Analyzer builds TokenStreams, which analyze text. It thus represents a policy for extracting index terms from text.

In order to define what analysis is done, subclasses must define their `TokenStreamComponents` in `createComponents(String)`. The components are then reused in each call to `tokenStream(String, Reader)`.

Simple example:

     Analyzer analyzer = new Analyzer() {
      @Override
       protected TokenStreamComponents createComponents(String fieldName) {
         Tokenizer source = new FooTokenizer(reader);
         TokenStream filter = new FooFilter(source);
         filter = new BarFilter(filter);
         return new TokenStreamComponents(source, filter);
       }
       @Override
       protected TokenStream normalize(String fieldName, TokenStream in) {
         // Assuming FooFilter is about normalization and BarFilter is about
         // stemming, only FooFilter should be applied
         return new FooFilter(in);
       }
     };

For more examples, see the `Analysis package documentation`.

For some concrete implementations bundled with Lucene, look in the analysis modules:

- Common: Analyzers for indexing content in different languages and domains.
- ICU: Exposes functionality from ICU to Apache Lucene.
- Kuromoji: Morphological analyzer for Japanese text.
- Morfologik: Dictionary-driven lemmatization for the Polish language.
- Phonetic: Analysis for indexing phonetic signatures (for sounds-alike search).
- Smart Chinese: Analyzer for Simplified Chinese, which indexes words.
- Stempel: Algorithmic Stemmer for the Polish Language.

Since:
  3.1

## Nested Class Summary

Nested Classes
Modifier and Type
Class
Description
`static class`
`Analyzer.ReuseStrategy`
Strategy defining how TokenStreamComponents are reused per call to `tokenStream(String, java.io.Reader)`.
`static final class`
`Analyzer.TokenStreamComponents`
This class encapsulates the outer components of a token stream.

## Field Summary

Fields
Modifier and Type
Field
Description
`static final Analyzer.ReuseStrategy`
`GLOBAL_REUSE_STRATEGY`
A predefined `Analyzer.ReuseStrategy` that reuses the same components for every field.
`static final Analyzer.ReuseStrategy`
`PER_FIELD_REUSE_STRATEGY`
A predefined `Analyzer.ReuseStrategy` that reuses components per-field by maintaining a Map of TokenStreamComponent per field name.

## Constructor Summary

Constructors
Modifier
Constructor
Description
`protected`
`Analyzer()`
Create a new Analyzer, reusing the same set of components per-thread across calls to `tokenStream(String, Reader)`.
`protected`
`Analyzer(Analyzer.ReuseStrategy reuseStrategy)`
Expert: create a new Analyzer with a custom `Analyzer.ReuseStrategy`.

## Method Summary

Modifier and Type
Method
Description
`protected AttributeFactory`
`attributeFactory(String fieldName)`
Return the `AttributeFactory` to be used for `analysis` and `normalization` on the given `FieldName`.
`void`
`close()`
Frees persistent resources used by this Analyzer
`protected abstract Analyzer.TokenStreamComponents`
`createComponents(String fieldName)`
Creates a new `Analyzer.TokenStreamComponents` instance for this analyzer.
`int`
`getOffsetGap(String fieldName)`
Just like `getPositionIncrementGap(java.lang.String)`, except for Token offsets instead.
`int`
`getPositionIncrementGap(String fieldName)`
Invoked before indexing a IndexableField instance if terms have already been added to that field.
`final Analyzer.ReuseStrategy`
`getReuseStrategy()`
Returns the used `Analyzer.ReuseStrategy`.
`protected Reader`
`initReader(String fieldName, Reader reader)`
Override this if you want to add a CharFilter chain.
`protected Reader`
`initReaderForNormalization(String fieldName, Reader reader)`
Wrap the given `Reader` with `CharFilter`s that make sense for normalization.
`final BytesRef`
`normalize(String fieldName, String text)`
Normalize a string down to the representation that it would have in the index.
`protected TokenStream`
`normalize(String fieldName, TokenStream in)`
Wrap the given `TokenStream` in order to apply normalization filters.
`final TokenStream`
`tokenStream(String fieldName, Reader reader)`
Returns a TokenStream suitable for `fieldName`, tokenizing the contents of `reader`.
`final TokenStream`
`tokenStream(String fieldName, String text)`
Returns a TokenStream suitable for `fieldName`, tokenizing the contents of `text`.

### Methods inherited from class java.lang.Object

`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

## Field Details

### GLOBAL_REUSE_STRATEGY

public static final Analyzer.ReuseStrategy GLOBAL_REUSE_STRATEGY
A predefined `Analyzer.ReuseStrategy` that reuses the same components for every field.

### PER_FIELD_REUSE_STRATEGY

public static final Analyzer.ReuseStrategy PER_FIELD_REUSE_STRATEGY
A predefined `Analyzer.ReuseStrategy` that reuses components per-field by maintaining a Map of TokenStreamComponent per field name.

## Constructor Details

### Analyzer

protected Analyzer()
Create a new Analyzer, reusing the same set of components per-thread across calls to `tokenStream(String, Reader)`.

### Analyzer

protected Analyzer(Analyzer.ReuseStrategy reuseStrategy)
Expert: create a new Analyzer with a custom `Analyzer.ReuseStrategy`.

NOTE: if you just want to reuse on a per-field basis, it's easier to use a subclass of `AnalyzerWrapper` such as PerFieldAnalyzerWrapper instead.

## Method Details

### createComponents

protected abstract Analyzer.TokenStreamComponents createComponents(String fieldName)
Creates a new `Analyzer.TokenStreamComponents` instance for this analyzer.

Parameters:
  `fieldName` - the name of the fields content passed to the `Analyzer.TokenStreamComponents` sink as a reader
Returns:
  the `Analyzer.TokenStreamComponents` for this analyzer.

### normalize

protected TokenStream normalize(String fieldName, TokenStream in)
Wrap the given `TokenStream` in order to apply normalization filters. The default implementation returns the `TokenStream` as-is. This is used by `normalize(String, String)`.

### tokenStream

public final TokenStream tokenStream(String fieldName, Reader reader)
Returns a TokenStream suitable for `fieldName`, tokenizing the contents of `reader`.

This method uses `createComponents(String)` to obtain an instance of `Analyzer.TokenStreamComponents`. It returns the sink of the components and stores the components internally. Subsequent calls to this method will reuse the previously stored components after resetting them through `Analyzer.TokenStreamComponents.setReader(Reader)`.

NOTE: After calling this method, the consumer must follow the workflow described in `TokenStream` to properly consume its contents. See the `Analysis package documentation` for some examples demonstrating this.

NOTE: If your data is available as a `String`, use `tokenStream(String, String)` which reuses a `StringReader`-like instance internally.

Parameters:
  `fieldName` - the name of the field the created TokenStream is used for
  `reader` - the reader the streams source reads from
Returns:
  TokenStream for iterating the analyzed content of `reader`
Throws:
  `AlreadyClosedException` - if the Analyzer is closed.
See Also:
  - `tokenStream(String, String)`

### tokenStream

public final TokenStream tokenStream(String fieldName, String text)
Returns a TokenStream suitable for `fieldName`, tokenizing the contents of `text`.

This method uses `createComponents(String)` to obtain an instance of `Analyzer.TokenStreamComponents`. It returns the sink of the components and stores the components internally. Subsequent calls to this method will reuse the previously stored components after resetting them through `Analyzer.TokenStreamComponents.setReader(Reader)`.

NOTE: After calling this method, the consumer must follow the workflow described in `TokenStream` to properly consume its contents. See the `Analysis package documentation` for some examples demonstrating this.

Parameters:
  `fieldName` - the name of the field the created TokenStream is used for
  `text` - the String the streams source reads from
Returns:
  TokenStream for iterating the analyzed content of `reader`
Throws:
  `AlreadyClosedException` - if the Analyzer is closed.
See Also:
  - `tokenStream(String, Reader)`

### normalize

public final BytesRef normalize(String fieldName, String text)
Normalize a string down to the representation that it would have in the index.

This is typically used by query parsers in order to generate a query on a given term, without tokenizing or stemming, which are undesirable if the string to analyze is a partial word (eg. in case of a wildcard or fuzzy query).

This method uses `initReaderForNormalization(String, Reader)` in order to apply necessary character-level normalization and then `normalize(String, TokenStream)` in order to apply the normalizing token filters.

### initReader

protected Reader initReader(String fieldName, Reader reader)
Override this if you want to add a CharFilter chain.

The default implementation returns `reader` unchanged.

Parameters:
  `fieldName` - IndexableField name being indexed
  `reader` - original Reader
Returns:
  reader, optionally decorated with CharFilter(s)

### initReaderForNormalization

protected Reader initReaderForNormalization(String fieldName, Reader reader)
Wrap the given `Reader` with `CharFilter`s that make sense for normalization. This is typically a subset of the `CharFilter`s that are applied in `initReader(String, Reader)`. This is used by `normalize(String, String)`.

### attributeFactory

protected AttributeFactory attributeFactory(String fieldName)
Return the `AttributeFactory` to be used for `analysis` and `normalization` on the given `FieldName`. The default implementation returns `TokenStream.DEFAULT_TOKEN_ATTRIBUTE_FACTORY`.

### getPositionIncrementGap

public int getPositionIncrementGap(String fieldName)
Invoked before indexing a IndexableField instance if terms have already been added to that field. This allows custom analyzers to place an automatic position increment gap between IndexbleField instances using the same field name. The default value position increment gap is 0. With a 0 position increment gap and the typical default token position increment of 1, all terms in a field, including across IndexableField instances, are in successive positions, allowing exact PhraseQuery matches, for instance, across IndexableField instance boundaries.

Parameters:
  `fieldName` - IndexableField name being indexed.
Returns:
  position increment gap, added to the next token emitted from `tokenStream(String,Reader)`. This value must be `>= 0`.

### getOffsetGap

public int getOffsetGap(String fieldName)
Just like `getPositionIncrementGap(java.lang.String)`, except for Token offsets instead. By default this returns 1. This method is only called if the field produced at least one token for indexing.

Parameters:
  `fieldName` - the field just indexed
Returns:
  offset gap, added to the next token emitted from `tokenStream(String,Reader)`. This value must be `>= 0`.

### getReuseStrategy

public final Analyzer.ReuseStrategy getReuseStrategy()
Returns the used `Analyzer.ReuseStrategy`.

### close

public void close()
Frees persistent resources used by this Analyzer

Specified by:
  `close` in interface `AutoCloseable`
Specified by:
  `close` in interface `Closeable`