103 lines
2.5 KiB
Plaintext
103 lines
2.5 KiB
Plaintext
[[analysis-simplepatternsplit-tokenizer]]
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=== Simple Pattern Split Tokenizer
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The `simple_pattern_split` tokenizer uses a regular expression to split the
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input into terms at pattern matches. The set of regular expression features it
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supports is more limited than the <<analysis-pattern-tokenizer,`pattern`>>
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tokenizer, but the tokenization is generally faster.
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This tokenizer does not produce terms from the matches themselves. To produce
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terms from matches using patterns in the same restricted regular expression
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subset, see the <<analysis-simplepattern-tokenizer,`simple_pattern`>>
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tokenizer.
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This tokenizer uses {lucene-core-javadoc}/org/apache/lucene/util/automaton/RegExp.html[Lucene regular expressions].
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For an explanation of the supported features and syntax, see <<regexp-syntax,Regular Expression Syntax>>.
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The default pattern is the empty string, which produces one term containing the
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full input. This tokenizer should always be configured with a non-default
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pattern.
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[float]
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=== Configuration
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The `simple_pattern_split` tokenizer accepts the following parameters:
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[horizontal]
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`pattern`::
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A {lucene-core-javadoc}/org/apache/lucene/util/automaton/RegExp.html[Lucene regular expression], defaults to the empty string.
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[float]
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=== Example configuration
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This example configures the `simple_pattern_split` tokenizer to split the input
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text on underscores.
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[source,console]
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----------------------------
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PUT my_index
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{
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"settings": {
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"analysis": {
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"analyzer": {
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"my_analyzer": {
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"tokenizer": "my_tokenizer"
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}
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},
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"tokenizer": {
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"my_tokenizer": {
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"type": "simple_pattern_split",
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"pattern": "_"
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}
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}
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}
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}
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}
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POST my_index/_analyze
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{
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"analyzer": "my_analyzer",
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"text": "an_underscored_phrase"
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}
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----------------------------
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/////////////////////
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[source,console-result]
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----------------------------
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{
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"tokens" : [
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{
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"token" : "an",
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"start_offset" : 0,
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"end_offset" : 2,
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"type" : "word",
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"position" : 0
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},
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{
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"token" : "underscored",
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"start_offset" : 3,
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"end_offset" : 14,
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"type" : "word",
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"position" : 1
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},
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{
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"token" : "phrase",
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"start_offset" : 15,
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"end_offset" : 21,
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"type" : "word",
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"position" : 2
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}
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]
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}
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----------------------------
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/////////////////////
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The above example produces these terms:
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[source,text]
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---------------------------
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[ an, underscored, phrase ]
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---------------------------
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