The index analysis module acts as a configurable registry of Analyzers that can be used in order to both break indexed (analyzed) fields when a document is indexed and process query strings. It maps to the Lucene Analyzer.

Analyzers are (generally) composed of a single Tokenizer and zero or more TokenFilters. A set of CharFilters can be associated with an analyzer to process the characters prior to other analysis steps. The analysis module allows one to register TokenFilters, Tokenizers and Analyzers under logical names that can then be referenced either in mapping definitions or in certain APIs. The Analysis module automatically registers (if not explicitly defined) built in analyzers, token filters, and tokenizers.

Here is a sample configuration:

index :
    analysis :
        analyzer : 
            standard : 
                type : standard
                stopwords : [stop1, stop2]
            myAnalyzer1 :
                type : standard
                stopwords : [stop1, stop2, stop3]
                max_token_length : 500
            # configure a custom analyzer which is 
            # exactly like the default standard analyzer
            myAnalyzer2 :
                tokenizer : standard
                filter : [standard, lowercase, stop]
        tokenizer :
            myTokenizer1 :
                type : standard
                max_token_length : 900
            myTokenizer2 :
                type : keyword
                buffer_size : 512
        filter :
            myTokenFilter1 :
                type : stop
                stopwords : [stop1, stop2, stop3, stop4]
            myTokenFilter2 :
                type : length
                min : 0
                max : 2000

All analyzers, tokenizers, and token filters can be configured with a version parameter to control which Lucene version behavior they should use. Possible values are: 3.0, 3.1, 3.2, 3.3 and 3.4 (the highest version number is the default option).

Types

Analyzer

Analyzers in general are broken down into a Tokenizer with zero or more TokenFilter applied to it. The analysis module allows one to register TokenFilters, Tokenizers and Analyzers under logical names which can then be referenced either in mapping definitions or in certain APIs. Here is a list of analyzer types:

Char Filter

Char filters allow one to filter out the stream of text before it gets tokenized (used within an Analyzer).

Tokenizer

Tokenizers act as the first stage of the analysis process (used within an Analyzer).

Token Filter

Token filters act as additional stages of the analysis process (used within an Analyzer).

Default Analyzers

An analyzer is registered under a logical name. It can then be referenced from mapping definitions or certain APIs. When none are defined, defaults are used. There is an option to define which analyzers will be used by default when none can be derived.

The default logical name allows one to configure an analyzer that will be used both for indexing and for searching APIs. The default_index logical name can be used to configure a default analyzer that will be used just when indexing, and the default_search can be used to configure a default analyzer that will be used just when searching.

Aliasing Analyzers

Analyzers can be aliased to have several registered lookup names associated with them. For example:

index :
  analysis :
    analyzer :
      standard :
        alias: [alias1, alias2]
        type : standard
        stopwords : [test1, test2, test3]

Will allow the standard analyzer to also be referenced with alias1 and alias2 values.