Fulltext Analyzers

Fulltext Analyzers

Table of Contents

Overview
Built-in Analyzers
Built-in Tokenizers
Built-in Token Filters
Builtin Char Filter

Overview

Analyzers are used for creating fulltext-indexes. They take the content of a field and split it into tokens, which are then searched. Analyzers filter, reorder and/or transform the content of a field before it becomes the final stream of tokens.

An analyzer consists of one tokenizer, zero or more token-filters, and zero or more char-filters.

When a field-content is analyzed to become a stream of tokens, the char-filter is applied at first. It is used to filter some special chars from the stream of characters that make up the content.

Tokenizers take a possibly filtered stream of characters and split it into a stream of tokens.

Token-filters can add tokens, delete tokens or transform them.

With these elements in place, analyzer provide fine-grained control over building a token stream used for fulltext search. For example you can use language specific analyzers, tokenizers and token-filters to get proper search results for data provided in a certain language.

Below the builtin analyzers, tokenizers, token-filters and char-filters are listed. They can be used as is or can be extended.

Built-in Analyzers

`standard`

type='standard'

An analyzer of type standard is built using the Standard Tokenizer Tokenizer with the standard Token Filter, lowercase Token Filter, and stop Token Filter.

Lowercase all Tokens, uses NO stopwords and excludes tokens longer than 255 characters. This analyzer uses unicode text segmentation, which is defined by UAX#29.

For example, the standard analyzer converts the sentence

The quick brown fox jumps Over the lAzY DOG.

into the following tokens

quick, brown, fox, jumps, lazy, dog

Parameters

stopwords

A list of stopwords to initialize the stop filter with. Defaults to the english stop words.

max_token_length

The maximum token length. If a token exceeds this length it is split in max_token_length chunks. Defaults to 255.

`default`

type='default'

This is the same as the standard-analyzer analyzer.

`simple`

type='simple'

Uses the Lowercase Tokenizer tokenizer.

`whitespace`

type='whitespace'

Uses a Witespace Tokenizer tokenizer

`stop`

type='stop'

Uses a Lowercase Tokenizer Tokenizer, with stop Token Filter.

Parameters

stopwords

A list of stopwords to initialize the :ref:’stop-tokenfilter` filter with. Defaults to the english stop words.

stopwords_path

A path (either relative to config location, or absolute) to a stopwords file configuration.

`keyword`

type=keyword

Creates one single token from the field-contents.

`pattern`

type='pattern'

An analyzer of type pattern that can flexibly separate text into terms via a regular expression.

Parameters

lowercase

Should terms be lowercased or not. Defaults to true.

pattern

The regular expression pattern, defaults to W+.

flags

The regular expression flags.

Note

The regular expression should match the token separators, not the tokens themselves.

Flags should be pipe-separated, eg CASE_INSENSITIVE|COMMENTS. Check Java Pattern API for more details about flags options.

`language`

type='<language-name>'

The following types are supported:

arabic, armenian, basque, brazilian, bengali, bulgarian, catalan, chinese, cjk, czech, danish, dutch, english, finnish, french, galician, german, greek, hindi, hungarian, indonesian, italian, latvian, lithuanian, norwegian, persian, portuguese, romanian, russian, sorani, spanish, swedish, turkish, thai.

Parameters

stopwords

A list of stopwords to initialize the stop filter with. Defaults to the english stop words.

stopwords_path

A path (either relative to config location, or absolute) to a stopwords file configuration.

stem_exclusion

The stem_exclusion parameter allows you to specify an array of lowercase words that should not be stemmed. The following analyzers support setting stem_exclusion: arabic, armenian, basque, brazilian, bengali, bulgarian, catalan, czech, danish, dutch, english, finnish, french, galician, german, hindi, hungarian, indonesian, italian, latvian, lithuanian, norwegian, portuguese, romanian, russian, spanish, swedish, turkish.

`snowball`

type='snowball'

Uses the Standard Tokenizer Tokenizer, with standard filter, lowercase filter, stop filter, and snowball filter.

Parameters

stopwords

A list of stopwords to initialize the stop filter with. Defaults to the english stop words.

language

See the language-parameter of snowball.

`fingerprint`

type='fingerprint'

The fingerprint analyzer implements a fingerprinting algorithm which is used by the OpenRefine project to assist in clustering. Input text is lowercased, normalized to remove extended characters, sorted, deduplicated and concatenated into a single token. If a stopword list is configured, stop words will also be removed. It uses the Standard Tokenizer Tokenizer and the following filters: lowercase, asciifolding, fingerprint and ref:stop-tokenfilter.

Parameters

separator

The character to use to concatenate the terms. Defaults to a space.

max_output_size

The maximum token size to emit, tokens larger than this size will be discarded. Defaults to 255.

stopwords

A pre-defined stop words list like _english_ or an array containing a list of stop words. Defaults to \_none_.

stopwords_path

The path to a file containing stop words.

Built-in Tokenizers

Standard Tokenizer

type='standard'

The tokenizer of type standard is providing a grammar based tokenizer, which is a good tokenizer for most European language documents. The tokenizer implements the Unicode Text Segmentation algorithm, as specified in Unicode Standard Annex #29.

Parameters

max_token_length

The maximum token length. If a token exceeds this length it is split in max_token_length chunks. Defaults to 255.

Classic Tokenizer

type='classic'

The classic tokenizer is a grammar based tokenizer that is good for English language documents. This tokenizer has heuristics for special treatment of acronyms, company names, email addresses, and internet host names. However, these rules don’t always work, and the tokenizer doesn’t work well for most languages other than English.

Parameters

max_token_length

The maximum token length. If a token exceeds this length it is split in max_token_length chunks. Defaults to 255.

Thai Tokenizer

type='thai'

The thai tokenizer splits Thai text correctly, treats all other languages like the standard-tokenizer does.

Letter Tokenizer

type='letter'

The letter tokenzier splits text at non-letters.

Lowercase Tokenizer

type='lowercase'

The lowercase tokenizer performs the function of Letter Tokenizer and lowercase together. It divides text at non-letters and converts them to lower case.

Witespace Tokenizer

type='whitespace'

The whitespace tokenizer splits text at whitespace.

Parameters

max_token_length

The maximum token length. If a token exceeds this length it is split in max_token_length chunks. Defaults to 255.

UAX URL Email Tokenizer

type='uax_url_email'

The uax_url_email tokenizer behaves like the Standard Tokenizer, but tokenizes emails and urls as single tokens.

Parameters

max_token_length

The maximum token length. If a token exceeds this length it is split in max_token_length chunks. Defaults to 255.

N-Gram Tokenizer

type='ngram'

Parameters

min_gram

Minimum length of characters in a gram. default: 1.

max_gram

Maximum length of characters in a gram. default: 2.

token_chars

Characters classes to keep in the tokens, will split on characters that don’t belong to any of these classes. default: [] (Keep all characters).

Classes: letter, digit, whitespace, punctuation, symbol

Edge N-Gram Tokenizer

type='edge_ngram'

The edge_ngram tokenizer is very similar to N-Gram Tokenizer but only keeps n-grams which start at the beginning of a token.

Parameters

min_gram

Minimum length of characters in a gram. default: 1

max_gram

Maximum length of characters in a gram. default: 2

token_chars

Characters classes to keep in the tokens, will split on characters that don’t belong to any of these classes. default: [] (Keep all characters).

Classes: letter, digit, whitespace, punctuation, symbol

Keywork Tokenizer

type='keyword'

The keyworkd tokenizer emits the entire input as a single token.

Parameters

buffer_size

The term buffer size. Defaults to 256.

Pattern Tokenizer

type='pattern'

The pattern tokenizer separates text into terms via a regular expression.

Parameters

pattern

The regular expression pattern, defaults to \W+.

flags

The regular expression flags.

group

Which group to extract into tokens. Defaults to -1 (split).

Note

The regular expression should match the token separators, not the tokens themselves.

Flags should be pipe-separated, eg CASE_INSENSITIVE|COMMENTS. Check Java Pattern API for more details about flags options.

Simple Pattern Tokenizer

type='simple_pattern'

Similar to the pattern tokenizer, this tokenizer uses a regular expression to split matching text into terms, however with a limited, more restrictive subset of expressions. This is in general faster than the normal pattern tokenizer, but does not support splitting on pattern.

Parameters

pattern

A Lucene regular expression, defaults to empty string.

Simple Pattern Split Tokenizer

type='simple_patten_split'

The simple_pattern_split tokenizer operates with the same restricted subset of regular expressions as the simple_pattern tokenizer, but it splits the input on the pattern, rather than the matching pattern.

Parameters

pattern

A Lucene regular expression, defaults to empty string.

Path Hierarchy Tokenizer

type='path_hierarchy'

Takes something like this:

/something/something/else

And produces tokens:

/something
/something/something
/something/something/else

Parameters

delimiter

The character delimiter to use, defaults to /.

replacement

An optional replacement character to use. Defaults to the delimiter.

buffer_size

The buffer size to use, defaults to 1024.

reverse

Generates tokens in reverse order, defaults to false.

skip

Controls initial tokens to skip, defaults to 0.

Char Group Tokenizer

type=char_group

Breaks text into terms whenever it encounters a character that is part of a predefined set.

Parameters

tokenize_on_chars

A list containing characters to tokenize on.

Built-in Token Filters

`standard`

type='standard'

Normalizes tokens extracted with the Standard Tokenizer Tokenizer.

`classic`

type='classic'

Does optional post-processing of terms that are generated by the classic tokenizer. It removes the english possessive from the end of words, and it removes dots from acronyms.

`apostrophe`

type='apostrophe'

Strips all characters after an apostrophe, and the apostrophe itself.

`asciifolding`

type='asciifolding'

Converts alphabetic, numeric, and symbolic Unicode characters which are not in the first 127 ASCII characters (the “Basic Latin” Unicode block) into their ASCII equivalents, if one exists.

`length`

type='length'

Removes words that are too long or too short for the stream.

Parameters

min

The minimum number. Defaults to 0.

max

The maximum number. Defaults to Integer.MAX_VALUE.

`lowercase`

type='lowercase'

Normalizes token text to lower case.

Parameters

language

For options, see language Analyzer.

`ngram`

type='ngram'

Parameters

min_gram

Defaults to 1.

max_gram

Defaults to 2.

`edge_ngram`

type='edge_ngram'

Parameters

min_gram

Defaults to 1.

max_gram

Defaults to 2.

side

Either front or back. Defaults to front.

`porter_stem`

type='porter_stem'

Transforms the token stream as per the Porter stemming algorithm.

Note

The input to the stemming filter must already be in lower case, so you will need to use Lower Case Token Filter or Lower Case Tokenizer farther down the Tokenizer chain in order for this to work properly! For example, when using custom analyzer, make sure the lowercase filter comes before the porterStem filter in the list of filters.

`shingle`

type='shingle'

Constructs shingles (token n-grams), combinations of tokens as a single token, from a token stream.

Parameters

max_shingle_size

The maximum shingle size. Defaults to 2.

min_shingle_sizes

The minimum shingle size. Defaults to 2.

output_unigrams

If true the output will contain the input tokens (unigrams) as well as the shingles. Defaults to true.

output_unigrams_if_no_shingles

If output_unigrams is false the output will contain the input tokens (unigrams) if no shingles are available. Note if output_unigrams is set to true this setting has no effect. Defaults to false.

token_separator

The string to use when joining adjacent tokens to form a shingle. Defaults to ” “.

`stop`

type='stop'

Removes stop words from token streams.

Parameters

stopwords

A list of stop words to use. Defaults to english stop words.

stopwords_path

A path (either relative to config location, or absolute) to a stopwords file configuration. Each stop word should be in its own “line” (separated by a line break). The file must be UTF-8 encoded.

ignore_case

Set to true to lower case all words first. Defaults to false.

remove_trailing

Set to false in order to not ignore the last term of a search if it is a stop word. Defaults to true

`word_delimiter`

type='word_delimiter'

Splits words into subwords and performs optional transformations on subword groups.

Parameters

generate_word_parts

If true causes parts of words to be generated: “PowerShot” ⇒ “Power” “Shot”. Defaults to true.

generate_number_parts

If true causes number subwords to be generated: “500-42” ⇒ “500” “42”. Defaults to true.

catenate_words

If true causes maximum runs of word parts to be catenated: “wi-fi” ⇒ “wifi”. Defaults to false.

catenate_numbers

If true causes maximum runs of number parts to be catenated: “500-42” ⇒ “50042”. Defaults to false.

catenate_all

If true causes all subword parts to be catenated: “wi-fi-4000” ⇒ “wifi4000”. Defaults to false.

split_on_case_change

If true causes “PowerShot” to be two tokens; (“Power-Shot” remains two parts regards). Defaults to true.

preserve_original

If true includes original words in subwords: “500-42” ⇒ “500-42” “500” “42”. Defaults to false.

split_on_numerics

If true causes “j2se” to be three tokens; “j” “2” “se”. Defaults to true.

stem_english_possessive

If true causes trailing “‘s” to be removed for each subword: “O’Neil’s” ⇒ “O”, “Neil”. Defaults to true.

protected_words

A list of words protected from being delimiter.

protected_words_path

A relative or absolute path to a file configured with protected words (one on each line). If relative, automatically resolves to config/ based location if exists.

type_table

A custom type mapping table

`stemmer`

type='stemmer'

A filter that stems words (similar to snowball, but with more options).

Parameters

language/name

arabic, armenian, basque, brazilian, bulgarian, catalan, czech, danish, dutch, english, finnish, french, german, german2, greek, hungarian, italian, kp, kstem, lovins, latvian, norwegian, minimal_norwegian, porter, portuguese, romanian, russian, spanish, swedish, turkish, minimal_english, possessive_english, light_finnish, light_french, minimal_french, light_german, minimal_german, hindi, light_hungarian, indonesian, light_italian, light_portuguese, minimal_portuguese, portuguese, light_russian, light_spanish, light_swedish.

`keyword_marker`

type='keyword_marker'

Protects words from being modified by stemmers. Must be placed before any stemming filters.

Parameters

keywords

A list of words to use.

keywords_path

A path (either relative to config location, or absolute) to a list of words.

ignore_case

Set to true to lower case all words first. Defaults to false.

`kstem`

type='kstem'

High performance filter for english.

All terms must already be lowercased (use lowercase filter) for this filter to work correctly.

`snowball`

type='snowball'

A filter that stems words using a Snowball-generated stemmer.

Parameters

language

Possible values: Armenian, Basque, Catalan, Danish, Dutch, English, Finnish, French, German, German2, Hungarian, Italian, Kp, Lovins, Norwegian, Porter, Portuguese, Romanian, Russian, Spanish, Swedish, Turkish.

`synonym`

type='synonym'

Allows to easily handle synonyms during the analysis process. Synonyms are configured using a configuration file.

Parameters

synonyms_path

Path to synonyms configuration file

ignore_case

Defaults to false

expand

Defaults to true

`*_decompounder`

type='dictionary_decompounder' or type='hyphenation_decompounder'

Decomposes compound words.

Parameters

word_list

A list of words to use.

word_list_path

A path (either relative to config location, or absolute) to a list of words.

min_word_size

Minimum word size(Integer). Defaults to 5.

min_subword_size

Minimum subword size(Integer). Defaults to 2.

max_subword_size

Maximum subword size(Integer). Defaults to 15.

only_longest_match

Only matching the longest(Boolean). Defaults to false

`reverse`

type='reverse'

Reverses each token.

`elision`

type='elision'

Removes elisions.

Parameters

articles

A set of stop words articles, for example ['j', 'l'] for content like J'aime l'odeur.

`truncate`

type='truncate'

Truncates tokens to a specific length.

Parameters

length

Number of characters to truncate to. default 10

`unique`

type='unique'

Used to only index unique tokens during analysis. By default it is applied on all the token stream.

Parameters

only_on_same_position

If set to true, it will only remove duplicate tokens on the same position.

`pattern_capture`

type='pattern_capture'

Emits a token for every capture group in the regular expression

Parameters

preserve_original

If set to true (the default) then it would also emit the original token

`pattern_replace`

type='pattern_replace'

Handle string replacements based on a regular expression.

Parameters

pattern

Regular expression whose matches will be replaced.

replacement

The replacement, can reference the original text with $1-like (the first matched group) references.

`trim`

type='trim'

Trims the whitespace surrounding a token.

`limit`

type='limit'

Limits the number of tokens that are indexed per document and field.

Parameters

max_token_count

The maximum number of tokens that should be indexed per document and field. The default is 1

consume_all_tokens

If set to true the filter exhaust the stream even if max_token_count tokens have been consumed already. The default is false.

`hunspell`

type='hunspell'

Basic support for Hunspell stemming. Hunspell dictionaries will be picked up from the dedicated directory <path.conf>/hunspell. Each dictionary is expected to have its own directory named after its associated locale (language). This dictionary directory is expected to hold both the *.aff and *.dic files (all of which will automatically be picked up).

Parameters

ignore_case

If true, dictionary matching will be case insensitive (defaults to false)

strict_affix_parsing

Determines whether errors while reading a affix rules file will cause exception or simply be ignored (defaults to true)

locale

A locale for this filter. If this is unset, the lang or language are used instead - so one of these has to be set.

dictionary

The name of a dictionary contained in <path.conf>/hunspell.

dedup

If only unique terms should be returned, this needs to be set to true. Defaults to true.

recursion_level

Configures the recursion level a stemmer can go into. Defaults to 2. Some languages (for example czech) give better results when set to 1 or 0, so you should test it out.

`common_grams`

type='common_grams'

Generates bigrams for frequently occuring terms. Single terms are still indexed. It can be used as an alternative to the stop Token filter when we don’t want to completely ignore common terms.

Parameters

common_words

A list of common words to use.

common_words_path

A path (either relative to config location, or absolute) to a list of common words. Each word should be in its own “line” (separated by a line break). The file must be UTF-8 encoded.

ignore_case

If true, common words matching will be case insensitive (defaults to false).

query_mode

Generates bigrams then removes common words and single terms followed by a common word (defaults to false).

Note

Either common_words or common_words_path must be given.

`*_normalization`

type='<language>_normalization'

Normalizes special characters of several languages.

Available languages:

arabic
bengali
german
hindi
indic
persian
scandinavian
serbian
sorani

`scandinavian_folding`

type='scandinavian_folding'

Folds scandinavian characters like ø to o or å to a.

Though this might result in different words, it is easier to match different scandinavian languages using this folding algorithm.

`delimited_payload`

type='delimited_payload'

Split tokens up by delimiter (default |) into the real token being indexed and the payload stored additionally into the index. For example Trillian|65535 will be indexed as Trillian with 65535 as payload.

Parameters

encoding

How the payload should be interpreted, possible values are float for float values, int for integer values and identity for keeping the payload as byte array (string).

delimiter

The string used to separate the token and its payload.

`keep`

type='keep'

Only keep tokens defined within the settings of this filter keep_words and variations.

All other tokens will be filtered. This filter works like an inverse stop-tokenfilter filter.

Parameters

keep_words

A list of words to keep and index as tokens.

keep_words_path

A path (either relative to config location, or absolute) to a list of words to keep and index.

Each word should be in its own “line” (separated by a line break). The file must be UTF-8 encoded.

`stemmer_override`

type='stemmer_override'

Override any previous stemmer that recognizes keywords with a custom mapping, defined by rules or rules_path. One of these settings has to be set.

Parameters

rules

A list of rules for overriding, in the form of [<source>=><replacement>] e.g. "foo=>bar"

rules_path

A path to a file with one rule per line, like above.

`cjk_bigram`

type='cjk_bigram'

Handle Chinese, Japanese and Korean (CJK) bigrams.

Parameters

output_bigrams

Boolean flag to enable a combined unigram+bigram approach.

Default is false, so single CJK characters that do not form a bigram are passed as unigrams.

All non CJK characters are output unmodified.

ignored_scripts

Scripts to ignore. possible values: han, hiragana, katakana, hangul

`cjk_width`

type='cjk_width'

A filter that normalizes CJK.

`*_stem`

type='arabic_stem' or

type='brazilian_stem' or

type='czech_stem' or

type='dutch_stem' or

type='french_stem' or

type='german_stem' or

type='russian_stem'

A group of filters that applies language specific stemmers to the token stream. To prevent terms from being stemmed put a keywordmarker-tokenfilter before this filter into the token_filter chain.

`decimal_digit`

A token filter that folds unicode digits to 0-9

`remove_duplicates`

A token filter that drops identical tokens at the same position.

Builtin Char Filter

`mapping`

type='mapping'

Parameters

mappings

A list of mappings as strings of the form [<source>=><replacement>] e.g. "ph=>f"

mappings_path

A path to a file with one mapping per line, like above.

`html_strip`

type='html_strip'

Strips out HTML elements from an analyzed text.

`pattern_replace`

type='pattern_replace'

Manipulates the characters in a string before analysis with a regex.

Parameters

pattern

Regex whose matches will be replaced

replacement

Replacement string, can reference replaced text by $1 like references (first matched element)

`keep_types`

type='keep_types'

Keeps only the tokens with a token type contained in a predefined set.

Parameters

types

A list of token types to keep.

`min_hash`

type='min_hash'

Hashes each token of the token stream and divides the resulting hashes into buckets, keeping the lowest-valued hashes per bucket. It then returns these hashes as tokens.

Parameters

hash_count

The number of hashes to hash the token stream with. Defaults to 1.

bucket_count

The number of buckets to divide the minhashes into. Defaults to 512.

hash_set_size

The number of minhashes to keep per bucket. Defaults to 1.

with_rotation

Whether or not to fill empty buckets with the value of the first non-empty bucket to its circular right. Only takes effect if hash_set_size is equal to one. Defaults to true if bucket_count is greater than 1, else false.

`fingerprint`

type='fingerprint'

Emits a single token which is useful for fingerprinting a body of text, and/or providing a token that can be clustered on. It does this by sorting the tokens, deduplicating and then concatenating them back into a single token.

Parameters

separator

Separator which is used for concatenating the tokens. Defaults to a space.

max_output_size

If the concatenated fingerprint grows larger than max_output_size, the token filter will exit and will not emit a token. Defaults to 255.