# Does eager\_global\_ordinals speed up metrics calcaulations on high cardinality keyword fields?

**URL:** <https://discuss.elastic.co/t/does-eager-global-ordinals-speed-up-metrics-calcaulations-on-high-cardinality-keyword-fields/248330>\
**Category:** Elasticsearch\
**Created:** [September 11, 2020, 1:19pm UTC](https://discuss.elastic.co/t/does-eager-global-ordinals-speed-up-metrics-calcaulations-on-high-cardinality-keyword-fields/248330 "2020-09-11T13:19:43Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![Peter\_Steenbergen](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/peter_steenbergen/32/22888_2.png) [@Peter\_Steenbergen](https://discuss.elastic.co/u/Peter_Steenbergen)\
**Post date:** [September 11, 2020, 1:19pm UTC](https://discuss.elastic.co/t/does-eager-global-ordinals-speed-up-metrics-calcaulations-on-high-cardinality-keyword-fields/248330/1 "2020-09-11T13:19:43Z")

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Hi,

I was wondering if people have tested with a dataset with around 1.5M records with 40k of unique terms in a particular field to do metric calculations on or a regex filtering. I know there is a wildcard field (does that support term aggregations btw?)..

Would the setting "eager\_global\_ordinals" for a keyword help to load the terms in ordinal tree for quick lookups to make a more speedy query?

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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 9, 2020, 1:20pm UTC](https://discuss.elastic.co/t/does-eager-global-ordinals-speed-up-metrics-calcaulations-on-high-cardinality-keyword-fields/248330/2 "2020-10-09T13:20:04Z")

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