# Performance / memory impact by size of term aggregation?

**URL:** <https://discuss.elastic.co/t/performance-memory-impact-by-size-of-term-aggregation/82691>\
**Category:** Elasticsearch\
**Created:** [April 18, 2017, 10:26am UTC](https://discuss.elastic.co/t/performance-memory-impact-by-size-of-term-aggregation/82691 "2017-04-18T10:26:40Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![asp](https://avatars.discourse-cdn.com/v4/letter/a/9fc348/32.png) [@asp](https://discuss.elastic.co/u/asp)\
**Post date:** [April 18, 2017, 10:26am UTC](https://discuss.elastic.co/t/performance-memory-impact-by-size-of-term-aggregation/82691/1 "2017-04-18T10:26:40Z")

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Hi all,

I am using kibana, but I think this questions goes down to how elasticsearch is handling this problem.

If I am using a term aggregation on a field (e.g. company), I have to limit the term size.

Lets say in our example data, we have only 7 companies. Lets say I would like to have the calculation / aggregation on **all** unique entries for the field company.  
Is there a performance or especially a memory overhead if I I oversize the term size?  
Meaning, does it make any difference if I set it to 10 or 1000?  
Or is only the result set affecting the performance / memory usage?

I just want to understand the effect of my doing a bit deeper 😉

Thanks, Andreas

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<div class="post-metadata">

**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [May 16, 2017, 10:28am UTC](https://discuss.elastic.co/t/performance-memory-impact-by-size-of-term-aggregation/82691/2 "2017-05-16T10:28:32Z")

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