[[controlling-stemming]] === Controlling Stemming

Out-of-the-box stemming solutions are never perfect.((("stemming words", "controlling stemming"))) Algorithmic stemmers, especially, will blithely apply their rules to any words they encounter, perhaps conflating words that you would prefer to keep separate. Maybe, for your use case, it is important to keep skies and skiing as distinct words rather than stemming them both down to ski (as would happen with the english analyzer).

The http://bit.ly/1IOeXZD[`keyword_marker`] and http://bit.ly/1ymcioJ[`stemmer_override`] token filters((("stemmer_override token filter")))((("keyword_marker token filter"))) allow us to customize the stemming process.

[[preventing-stemming]] ==== Preventing Stemming

The <> parameter for language analyzers (see <>) allowed ((("stemming words", "controlling stemming", "preventing stemming")))us to specify a list of words that should not be stemmed. Internally, these language analyzers use the http://bit.ly/1IOeXZD[`keyword_marker` token filter] to mark the listed words as keywords, which prevents subsequent stemming token filters from touching those words.((("keyword_marker token filter", "preventing stemming of certain words")))

For instance, we can create a simple custom analyzer that uses the http://bit.ly/17LseXy[`porter_stem`] token filter, but prevents the word skies from((("porter_stem token filter"))) being stemmed:


PUT /my_index { "settings": { "analysis": { "filter": { "no_stem": { "type": "keyword_marker", "keywords": [ "skies" ] <1> } }, "analyzer": { "my_english": { "tokenizer": "standard", "filter": [ "lowercase", "no_stem", "porter_stem" ] } } } }


<1> They keywords parameter could accept multiple words.

Testing it with the analyze API shows that just the word skies has been excluded from stemming:


GET /my_index/_analyze?analyzer=my_english

sky skies skiing skis <1>

<1> Returns: sky, skies, ski, ski



While the language analyzers allow ((("language analyzers", "stem_exclusion parameter")))us only to specify an array of words in the stem_exclusion parameter, the keyword_marker token filter also accepts a keywords_path parameter that allows us to store all of our keywords in a file. ((("keyword_marker token filter", "keywords_path parameter")))The file should contain one word per line, and must be present on every node in the cluster. See <> for tips on how to update this file.


[[customizing-stemming]] ==== Customizing Stemming

In the preceding example, we prevented skies from being stemmed, but perhaps we would prefer it to be stemmed to sky instead.((("stemming words", "controlling stemming", "customizing stemming"))) The http://bit.ly/1ymcioJ[`stemmer_override`] token filter allows us ((("stemmer_override token filter")))to specify our own custom stemming rules. At the same time, we can handle some irregular forms like stemming mice to mouse and feet to foot:


PUT /my_index { "settings": { "analysis": { "filter": { "custom_stem": { "type": "stemmer_override", "rules": [ <1> "skies=>sky", "mice=>mouse", "feet=>foot" ] } }, "analyzer": { "my_english": { "tokenizer": "standard", "filter": [ "lowercase", "custom_stem", <2> "porter_stem" ] } } } } }

GET /my_index/_analyze?analyzer=my_english

The mice came down from the skies and ran over my feet <3>

<1> Rules take the form original=>stem.

<2> The stemmer_override filter must be placed before the stemmer.

<3> Returns the, mouse, came, down, from, the, sky, and, ran, over, my, foot.

TIP: Just as for the keyword_marker token filter, rules can be stored in a file whose location should be specified with the rules_path parameter.

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