Word delimiter graph token filter
editWord delimiter graph token filter
editSplits tokens at non-alphanumeric characters. The word_delimiter_graph
filter
also performs optional token normalization based on a set of rules. By default,
the filter uses the following rules:
-
Split tokens at non-alphanumeric characters.
The filter uses these characters as delimiters.
For example:
Super-Duper
→Super
,Duper
-
Remove leading or trailing delimiters from each token.
For example:
XL---42+'Autocoder'
→XL
,42
,Autocoder
-
Split tokens at letter case transitions.
For example:
PowerShot
→Power
,Shot
-
Split tokens at letter-number transitions.
For example:
XL500
→XL
,500
-
Remove the English possessive (
's
) from the end of each token. For example:Neil's
→Neil
The word_delimiter_graph
filter uses Lucene’s
WordDelimiterGraphFilter.
The word_delimiter_graph
filter was designed to remove punctuation from
complex identifiers, such as product IDs or part numbers. For these use cases,
we recommend using the word_delimiter_graph
filter with the
keyword
tokenizer.
Avoid using the word_delimiter_graph
filter to split hyphenated words, such as
wi-fi
. Because users often search for these words both with and without
hyphens, we recommend using the
synonym_graph
filter instead.
Example
editThe following analyze API request uses the
word_delimiter_graph
filter to split Neil's-Super-Duper-XL500--42+AutoCoder
into normalized tokens using the filter’s default rules:
response = client.indices.analyze( body: { tokenizer: 'keyword', filter: [ 'word_delimiter_graph' ], text: "Neil's-Super-Duper-XL500--42+AutoCoder" } ) puts response
GET /_analyze { "tokenizer": "keyword", "filter": [ "word_delimiter_graph" ], "text": "Neil's-Super-Duper-XL500--42+AutoCoder" }
The filter produces the following tokens:
[ Neil, Super, Duper, XL, 500, 42, Auto, Coder ]
Add to an analyzer
editThe following create index API request uses the
word_delimiter_graph
filter to configure a new
custom analyzer.
PUT /my-index-000001 { "settings": { "analysis": { "analyzer": { "my_analyzer": { "tokenizer": "keyword", "filter": [ "word_delimiter_graph" ] } } } } }
Avoid using the word_delimiter_graph
filter with tokenizers that remove
punctuation, such as the standard
tokenizer.
This could prevent the word_delimiter_graph
filter from splitting tokens
correctly. It can also interfere with the filter’s configurable parameters, such
as catenate_all
or
preserve_original
. We
recommend using the keyword
or
whitespace
tokenizer instead.
Configurable parameters
edit-
adjust_offsets
-
(Optional, Boolean) If
true
, the filter adjusts the offsets of split or catenated tokens to better reflect their actual position in the token stream. Defaults totrue
.Set
adjust_offsets
tofalse
if your analyzer uses filters, such as thetrim
filter, that change the length of tokens without changing their offsets. Otherwise, theword_delimiter_graph
filter could produce tokens with illegal offsets.
-
catenate_all
-
(Optional, Boolean) If
true
, the filter produces catenated tokens for chains of alphanumeric characters separated by non-alphabetic delimiters. For example:super-duper-xl-500
→ [superduperxl500
,super
,duper
,xl
,500
]. Defaults tofalse
.Setting this parameter to
true
produces multi-position tokens, which are not supported by indexing.If this parameter is
true
, avoid using this filter in an index analyzer or use theflatten_graph
filter after this filter to make the token stream suitable for indexing.When used for search analysis, catenated tokens can cause problems for the
match_phrase
query and other queries that rely on token position for matching. Avoid setting this parameter totrue
if you plan to use these queries.
-
catenate_numbers
-
(Optional, Boolean) If
true
, the filter produces catenated tokens for chains of numeric characters separated by non-alphabetic delimiters. For example:01-02-03
→ [010203
,01
,02
,03
]. Defaults tofalse
.Setting this parameter to
true
produces multi-position tokens, which are not supported by indexing.If this parameter is
true
, avoid using this filter in an index analyzer or use theflatten_graph
filter after this filter to make the token stream suitable for indexing.When used for search analysis, catenated tokens can cause problems for the
match_phrase
query and other queries that rely on token position for matching. Avoid setting this parameter totrue
if you plan to use these queries.
-
catenate_words
-
(Optional, Boolean) If
true
, the filter produces catenated tokens for chains of alphabetical characters separated by non-alphabetic delimiters. For example:super-duper-xl
→ [superduperxl
,super
,duper
,xl
]. Defaults tofalse
.Setting this parameter to
true
produces multi-position tokens, which are not supported by indexing.If this parameter is
true
, avoid using this filter in an index analyzer or use theflatten_graph
filter after this filter to make the token stream suitable for indexing.When used for search analysis, catenated tokens can cause problems for the
match_phrase
query and other queries that rely on token position for matching. Avoid setting this parameter totrue
if you plan to use these queries. -
generate_number_parts
-
(Optional, Boolean)
If
true
, the filter includes tokens consisting of only numeric characters in the output. Iffalse
, the filter excludes these tokens from the output. Defaults totrue
. -
generate_word_parts
-
(Optional, Boolean)
If
true
, the filter includes tokens consisting of only alphabetical characters in the output. Iffalse
, the filter excludes these tokens from the output. Defaults totrue
. -
ignore_keywords
-
(Optional, Boolean)
If
true
, the filter skips tokens with akeyword
attribute oftrue
. Defaults tofalse
.
-
preserve_original
-
(Optional, Boolean) If
true
, the filter includes the original version of any split tokens in the output. This original version includes non-alphanumeric delimiters. For example:super-duper-xl-500
→ [super-duper-xl-500
,super
,duper
,xl
,500
]. Defaults tofalse
.Setting this parameter to
true
produces multi-position tokens, which are not supported by indexing.If this parameter is
true
, avoid using this filter in an index analyzer or use theflatten_graph
filter after this filter to make the token stream suitable for indexing. -
protected_words
- (Optional, array of strings) Array of tokens the filter won’t split.
-
protected_words_path
-
(Optional, string) Path to a file that contains a list of tokens the filter won’t split.
This path must be absolute or relative to the
config
location, and the file must be UTF-8 encoded. Each token in the file must be separated by a line break. -
split_on_case_change
-
(Optional, Boolean)
If
true
, the filter splits tokens at letter case transitions. For example:camelCase
→ [camel
,Case
]. Defaults totrue
. -
split_on_numerics
-
(Optional, Boolean)
If
true
, the filter splits tokens at letter-number transitions. For example:j2se
→ [j
,2
,se
]. Defaults totrue
. -
stem_english_possessive
-
(Optional, Boolean)
If
true
, the filter removes the English possessive ('s
) from the end of each token. For example:O'Neil's
→ [O
,Neil
]. Defaults totrue
. -
type_table
-
(Optional, array of strings) Array of custom type mappings for characters. This allows you to map non-alphanumeric characters as numeric or alphanumeric to avoid splitting on those characters.
For example, the following array maps the plus (
+
) and hyphen (-
) characters as alphanumeric, which means they won’t be treated as delimiters:[ "+ => ALPHA", "- => ALPHA" ]
Supported types include:
-
ALPHA
(Alphabetical) -
ALPHANUM
(Alphanumeric) -
DIGIT
(Numeric) -
LOWER
(Lowercase alphabetical) -
SUBWORD_DELIM
(Non-alphanumeric delimiter) -
UPPER
(Uppercase alphabetical)
-
-
type_table_path
-
(Optional, string) Path to a file that contains custom type mappings for characters. This allows you to map non-alphanumeric characters as numeric or alphanumeric to avoid splitting on those characters.
For example, the contents of this file may contain the following:
# Map the $, %, '.', and ',' characters to DIGIT # This might be useful for financial data. $ => DIGIT % => DIGIT . => DIGIT \\u002C => DIGIT # in some cases you might not want to split on ZWJ # this also tests the case where we need a bigger byte[] # see https://en.wikipedia.org/wiki/Zero-width_joiner \\u200D => ALPHANUM
Supported types include:
-
ALPHA
(Alphabetical) -
ALPHANUM
(Alphanumeric) -
DIGIT
(Numeric) -
LOWER
(Lowercase alphabetical) -
SUBWORD_DELIM
(Non-alphanumeric delimiter) -
UPPER
(Uppercase alphabetical)
This file path must be absolute or relative to the
config
location, and the file must be UTF-8 encoded. Each mapping in the file must be separated by a line break. -
Customize
editTo customize the word_delimiter_graph
filter, duplicate it to create the basis
for a new custom token filter. You can modify the filter using its configurable
parameters.
For example, the following request creates a word_delimiter_graph
filter that uses the following rules:
-
Split tokens at non-alphanumeric characters, except the hyphen (
-
) character. - Remove leading or trailing delimiters from each token.
- Do not split tokens at letter case transitions.
- Do not split tokens at letter-number transitions.
-
Remove the English possessive (
's
) from the end of each token.
PUT /my-index-000001 { "settings": { "analysis": { "analyzer": { "my_analyzer": { "tokenizer": "keyword", "filter": [ "my_custom_word_delimiter_graph_filter" ] } }, "filter": { "my_custom_word_delimiter_graph_filter": { "type": "word_delimiter_graph", "type_table": [ "- => ALPHA" ], "split_on_case_change": false, "split_on_numerics": false, "stem_english_possessive": true } } } } }
Differences between word_delimiter_graph
and word_delimiter
editBoth the word_delimiter_graph
and
word_delimiter
filters produce tokens
that span multiple positions when any of the following parameters are true
:
However, only the word_delimiter_graph
filter assigns multi-position tokens a
positionLength
attribute, which indicates the number of positions a token
spans. This ensures the word_delimiter_graph
filter always produces valid
token graphs.
The word_delimiter
filter does not assign multi-position tokens a
positionLength
attribute. This means it produces invalid graphs for streams
including these tokens.
While indexing does not support token graphs containing multi-position tokens,
queries, such as the match_phrase
query, can
use these graphs to generate multiple sub-queries from a single query string.
To see how token graphs produced by the word_delimiter
and
word_delimiter_graph
filters differ, check out the following example.
Example
Both the word_delimiter
and word_delimiter_graph
produce the following token
graph for PowerShot2000
when the following parameters are false
:
This graph does not contain multi-position tokens. All tokens span only one position.
word_delimiter_graph
graph with a multi-position token
The word_delimiter_graph
filter produces the following token graph for
PowerShot2000
when catenate_words
is true
.
This graph correctly indicates the catenated PowerShot
token spans two
positions.
word_delimiter
graph with a multi-position token
When catenate_words
is true
, the word_delimiter
filter produces
the following token graph for PowerShot2000
.
Note that the catenated PowerShot
token should span two positions but only
spans one in the token graph, making it invalid.