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* add keyword repeat token filter docs #8149 Signed-off-by: Anton Rubin <[email protected]> * Doc review Signed-off-by: Fanit Kolchina <[email protected]> * Apply suggestions from code review Co-authored-by: Nathan Bower <[email protected]> Signed-off-by: kolchfa-aws <[email protected]> --------- Signed-off-by: Anton Rubin <[email protected]> Signed-off-by: Fanit Kolchina <[email protected]> Signed-off-by: kolchfa-aws <[email protected]> Co-authored-by: Fanit Kolchina <[email protected]> Co-authored-by: kolchfa-aws <[email protected]> Co-authored-by: Nathan Bower <[email protected]>
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,160 @@ | ||
| --- | ||
| layout: default | ||
| title: Keyword repeat | ||
| parent: Token filters | ||
| nav_order: 210 | ||
| --- | ||
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| # Keyword repeat token filter | ||
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| The `keyword_repeat` token filter emits the keyword version of a token into a token stream. This filter is typically used when you want to retain both the original token and its modified version after further token transformations, such as stemming or synonym expansion. The duplicated tokens allow the original, unchanged version of the token to remain in the final analysis alongside the modified versions. | ||
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| The `keyword_repeat` token filter should be placed before stemming filters. Stemming is not applied to every token, thus you may have duplicate tokens in the same position after stemming. To remove duplicate tokens, use the `remove_duplicates` token filter after the stemmer. | ||
| {: .note} | ||
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| ## Example | ||
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| The following example request creates a new index named `my_index` and configures an analyzer with a `keyword_repeat` filter: | ||
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| ```json | ||
| PUT /my_index | ||
| { | ||
| "settings": { | ||
| "analysis": { | ||
| "filter": { | ||
| "my_kstem": { | ||
| "type": "kstem" | ||
| }, | ||
| "my_lowercase": { | ||
| "type": "lowercase" | ||
| } | ||
| }, | ||
| "analyzer": { | ||
| "my_custom_analyzer": { | ||
| "type": "custom", | ||
| "tokenizer": "standard", | ||
| "filter": [ | ||
| "my_lowercase", | ||
| "keyword_repeat", | ||
| "my_kstem" | ||
| ] | ||
| } | ||
| } | ||
| } | ||
| } | ||
| } | ||
| ``` | ||
| {% include copy-curl.html %} | ||
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| ## Generated tokens | ||
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| Use the following request to examine the tokens generated using the analyzer: | ||
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| ```json | ||
| POST /my_index/_analyze | ||
| { | ||
| "analyzer": "my_custom_analyzer", | ||
| "text": "Stopped quickly" | ||
| } | ||
| ``` | ||
| {% include copy-curl.html %} | ||
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| The response contains the generated tokens: | ||
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| ```json | ||
| { | ||
| "tokens": [ | ||
| { | ||
| "token": "stopped", | ||
| "start_offset": 0, | ||
| "end_offset": 7, | ||
| "type": "<ALPHANUM>", | ||
| "position": 0 | ||
| }, | ||
| { | ||
| "token": "stop", | ||
| "start_offset": 0, | ||
| "end_offset": 7, | ||
| "type": "<ALPHANUM>", | ||
| "position": 0 | ||
| }, | ||
| { | ||
| "token": "quickly", | ||
| "start_offset": 8, | ||
| "end_offset": 15, | ||
| "type": "<ALPHANUM>", | ||
| "position": 1 | ||
| }, | ||
| { | ||
| "token": "quick", | ||
| "start_offset": 8, | ||
| "end_offset": 15, | ||
| "type": "<ALPHANUM>", | ||
| "position": 1 | ||
| } | ||
| ] | ||
| } | ||
| ``` | ||
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| You can further examine the impact of the `keyword_repeat` token filter by adding the following parameters to the `_analyze` query: | ||
|
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| ```json | ||
| POST /my_index/_analyze | ||
| { | ||
| "analyzer": "my_custom_analyzer", | ||
| "text": "Stopped quickly", | ||
| "explain": true, | ||
| "attributes": "keyword" | ||
| } | ||
| ``` | ||
| {% include copy-curl.html %} | ||
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| The response includes detailed information, such as tokenization, filtering, and the application of specific token filters: | ||
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| ```json | ||
| { | ||
| "detail": { | ||
| "custom_analyzer": true, | ||
| "charfilters": [], | ||
| "tokenizer": { | ||
| "name": "standard", | ||
| "tokens": [ | ||
| {"token": "OpenSearch","start_offset": 0,"end_offset": 10,"type": "<ALPHANUM>","position": 0}, | ||
| {"token": "helped","start_offset": 11,"end_offset": 17,"type": "<ALPHANUM>","position": 1}, | ||
| {"token": "many","start_offset": 18,"end_offset": 22,"type": "<ALPHANUM>","position": 2}, | ||
| {"token": "employers","start_offset": 23,"end_offset": 32,"type": "<ALPHANUM>","position": 3} | ||
| ] | ||
| }, | ||
| "tokenfilters": [ | ||
| { | ||
| "name": "lowercase", | ||
| "tokens": [ | ||
| {"token": "opensearch","start_offset": 0,"end_offset": 10,"type": "<ALPHANUM>","position": 0}, | ||
| {"token": "helped","start_offset": 11,"end_offset": 17,"type": "<ALPHANUM>","position": 1}, | ||
| {"token": "many","start_offset": 18,"end_offset": 22,"type": "<ALPHANUM>","position": 2}, | ||
| {"token": "employers","start_offset": 23,"end_offset": 32,"type": "<ALPHANUM>","position": 3} | ||
| ] | ||
| }, | ||
| { | ||
| "name": "keyword_marker_filter", | ||
| "tokens": [ | ||
| {"token": "opensearch","start_offset": 0,"end_offset": 10,"type": "<ALPHANUM>","position": 0,"keyword": true}, | ||
| {"token": "helped","start_offset": 11,"end_offset": 17,"type": "<ALPHANUM>","position": 1,"keyword": false}, | ||
| {"token": "many","start_offset": 18,"end_offset": 22,"type": "<ALPHANUM>","position": 2,"keyword": false}, | ||
| {"token": "employers","start_offset": 23,"end_offset": 32,"type": "<ALPHANUM>","position": 3,"keyword": false} | ||
| ] | ||
| }, | ||
| { | ||
| "name": "kstem_filter", | ||
| "tokens": [ | ||
| {"token": "opensearch","start_offset": 0,"end_offset": 10,"type": "<ALPHANUM>","position": 0,"keyword": true}, | ||
| {"token": "help","start_offset": 11,"end_offset": 17,"type": "<ALPHANUM>","position": 1,"keyword": false}, | ||
| {"token": "many","start_offset": 18,"end_offset": 22,"type": "<ALPHANUM>","position": 2,"keyword": false}, | ||
| {"token": "employer","start_offset": 23,"end_offset": 32,"type": "<ALPHANUM>","position": 3,"keyword": false} | ||
| ] | ||
| } | ||
| ] | ||
| } | ||
| } | ||
| ``` |