90 lines
2.0 KiB
Plaintext
90 lines
2.0 KiB
Plaintext
[[analysis-keyword-analyzer]]
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=== Keyword analyzer
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++++
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<titleabbrev>Keyword</titleabbrev>
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++++
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The `keyword` analyzer is a ``noop'' analyzer which returns the entire input
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string as a single token.
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[float]
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=== Example output
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[source,console]
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---------------------------
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POST _analyze
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{
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"analyzer": "keyword",
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"text": "The 2 QUICK Brown-Foxes jumped over the lazy dog's bone."
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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": "The 2 QUICK Brown-Foxes jumped over the lazy dog's bone.",
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"start_offset": 0,
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"end_offset": 56,
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"type": "word",
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"position": 0
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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 sentence would produce the following single term:
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[source,text]
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---------------------------
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[ The 2 QUICK Brown-Foxes jumped over the lazy dog's bone. ]
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---------------------------
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[float]
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=== Configuration
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The `keyword` analyzer is not configurable.
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[float]
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=== Definition
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The `keyword` analyzer consists of:
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Tokenizer::
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* <<analysis-keyword-tokenizer,Keyword Tokenizer>>
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If you need to customize the `keyword` analyzer then you need to
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recreate it as a `custom` analyzer and modify it, usually by adding
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token filters. Usually, you should prefer the
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<<keyword, Keyword type>> when you want strings that are not split
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into tokens, but just in case you need it, this would recreate the
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built-in `keyword` analyzer and you can use it as a starting point
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for further customization:
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[source,console]
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----------------------------------------------------
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PUT /keyword_example
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{
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"settings": {
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"analysis": {
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"analyzer": {
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"rebuilt_keyword": {
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"tokenizer": "keyword",
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"filter": [ <1>
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]
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}
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}
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}
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}
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}
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----------------------------------------------------
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// TEST[s/\n$/\nstartyaml\n - compare_analyzers: {index: keyword_example, first: keyword, second: rebuilt_keyword}\nendyaml\n/]
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<1> You'd add any token filters here.
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