# Indexing large amount of data due to Autosuggestion and Highlighting

**URL:** <https://discuss.elastic.co/t/indexing-large-amount-of-data-due-to-autosuggestion-and-highlighting/149942>\
**Category:** Elasticsearch\
**Created:** [September 26, 2018, 7:26am UTC](https://discuss.elastic.co/t/indexing-large-amount-of-data-due-to-autosuggestion-and-highlighting/149942 "2018-09-26T07:26:20Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![pranav24](https://avatars.discourse-cdn.com/v4/letter/p/b19c9b/32.png) [@pranav24](https://discuss.elastic.co/u/pranav24)\
**Post date:** [September 26, 2018, 7:26am UTC](https://discuss.elastic.co/t/indexing-large-amount-of-data-due-to-autosuggestion-and-highlighting/149942/1 "2018-09-26T07:26:20Z")

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Hi all,  
I am indexing thousands of documents which contains hundreds of metadata with one field containing over 5000 words and rest of the fields containing 3-5 words each. I am using Edge Tokenizer to perform autosuggestion and term\_vectors to use fast vector highlighting. I have noticed my index size has increased over 50% by using these two features. Will this affect my future search performances since I have to index many more documents and is it a bad procedure to have large index data?  
Is there any disadvantage of using large sized indices?

Elasticsearch version -6.3.2

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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:** [October 24, 2018, 7:26am UTC](https://discuss.elastic.co/t/indexing-large-amount-of-data-due-to-autosuggestion-and-highlighting/149942/2 "2018-10-24T07:26:26Z")

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Closed on October 24, 2018, 7:26am UTC

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