# Anyone has a performance evaluation with NGram tokenizer?

**URL:** <https://discuss.elastic.co/t/anyone-has-a-performance-evaluation-with-ngram-tokenizer/307356>\
**Category:** Elasticsearch\
**Created:** [June 16, 2022, 7:47am UTC](https://discuss.elastic.co/t/anyone-has-a-performance-evaluation-with-ngram-tokenizer/307356 "2022-06-16T07:47:16Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![fraf](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/fraf/32/107072_2.png) [@fraf](https://discuss.elastic.co/u/fraf)\
**Post date:** [June 16, 2022, 7:47am UTC](https://discuss.elastic.co/t/anyone-has-a-performance-evaluation-with-ngram-tokenizer/307356/1 "2022-06-16T07:47:16Z")

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Hello searchers,

I think, one of the best tokenizer algorithm (and maybe the most used), is the NGram tokenizer (equivalent to the SQL : `where table.column like '%search_text%`'.  
Indeed, given an input text, it can generate a lot of (very lot) token. So given an input search text, it is likely to find a matched token. But for me, it is the easy solution, without taking into account the performance other side : how long does it takes to update this kind of index ? how much weight does it represents for searching in general, because this NGram algorithm can ask for a lot of disk space , too much as long as `min_gram` is low.

Any performance feedback ? Thx.

EDIT : is it possible to have any metrics which say "given this fulltext field of this index name, we have X generated token. Among all these tokens, you can see how often, for each one, it has been candidate and so matched a given input text". ?

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**Author:** ![Christian\_Dahlqvist](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/christian_dahlqvist/32/4617_2.png) [@Christian\_Dahlqvist](https://discuss.elastic.co/u/Christian_Dahlqvist)\
**Post date:** [June 16, 2022, 8:59am UTC](https://discuss.elastic.co/t/anyone-has-a-performance-evaluation-with-ngram-tokenizer/307356/2 "2022-06-16T08:59:09Z")

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It sounds like the [the wildcard field type](https://www.elastic.co/guide/en/elasticsearch/reference/8.2/keyword.html#wildcard-field-type) might be what you are looking for.

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**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [July 14, 2022, 8:59am UTC](https://discuss.elastic.co/t/anyone-has-a-performance-evaluation-with-ngram-tokenizer/307356/3 "2022-07-14T08:59:50Z")

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