# Subject query data of restaurants by given location topic that we desire for a year

**URL:** <https://discuss.elastic.co/t/subject-query-data-of-restaurants-by-given-location-topic-that-we-desire-for-a-year/330167>\
**Category:** Elasticsearch\
**Created:** [April 17, 2023, 9:01pm UTC](https://discuss.elastic.co/t/subject-query-data-of-restaurants-by-given-location-topic-that-we-desire-for-a-year/330167 "2023-04-17T21:01:45Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![Nonchaianon](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/nonchaianon/32/119933_2.png) [@Nonchaianon](https://discuss.elastic.co/u/Nonchaianon)\
**Post date:** [April 17, 2023, 9:01pm UTC](https://discuss.elastic.co/t/subject-query-data-of-restaurants-by-given-location-topic-that-we-desire-for-a-year/330167/1 "2023-04-17T21:01:45Z")

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Dear elasticsearch technical

I’am developer Food delivery platform

We desire to improve performance query data of restaurants by given location

Condition

-50,000 restaurant

-200 km^2

-queries 200,000 times per day

Solution 1

We geospatial restaurants 500 restaurants/index/cluster by using H3 totally 100 index.

When user query by given location we pull the specification index relevant index.

Solution 2

We store 50,000 restaurant in 1 index but we using geo query by Elasticsearch which claim efficiency query large data

Please suggestion which solution are improve high performance and using low resources of sever

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**Author:** ![warkolm](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/warkolm/32/39224_2.png) [@warkolm](https://discuss.elastic.co/u/warkolm)\
**Post date:** [April 17, 2023, 10:15pm UTC](https://discuss.elastic.co/t/subject-query-data-of-restaurants-by-given-location-topic-that-we-desire-for-a-year/330167/2 "2023-04-17T22:15:42Z")

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Welcome to our community! 😃

> [@Nonchaianon](#):
>
> Please suggestion which solution are improve high performance and using low resources of sever

Your best option is to test both solutions on your dataset, your queries and your cluster and see which is faster.

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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:** [May 15, 2023, 10:16pm UTC](https://discuss.elastic.co/t/subject-query-data-of-restaurants-by-given-location-topic-that-we-desire-for-a-year/330167/3 "2023-05-15T22:16:31Z")

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