# One index or multiple index for exact same mapping, but the data are clustered based on a field

**URL:** <https://discuss.elastic.co/t/one-index-or-multiple-index-for-exact-same-mapping-but-the-data-are-clustered-based-on-a-field/378311>\
**Category:** Elasticsearch\
**Created:** [May 19, 2025, 5:44pm UTC](https://discuss.elastic.co/t/one-index-or-multiple-index-for-exact-same-mapping-but-the-data-are-clustered-based-on-a-field/378311 "2025-05-19T17:44:34Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![orfeas\_filippopoulos](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/orfeas_filippopoulos/32/143210_2.png) [@orfeas\_filippopoulos](https://discuss.elastic.co/u/orfeas_filippopoulos)\
**Post date:** [May 19, 2025, 5:44pm UTC](https://discuss.elastic.co/t/one-index-or-multiple-index-for-exact-same-mapping-but-the-data-are-clustered-based-on-a-field/378311/1 "2025-05-19T17:44:34Z")

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Hi there, community!

I have a short question.  
I have around 100k documents, each ranging from a few hundred KB to a maximum of 1MB. The documents have exactly the same mapping but can be grouped into three different clusters of equal size, based on a field in each document (let's say `doc_type`). Each query will target only one cluster at a time.

Will I achieve better performance if I split the documents into three different indexes?  
My initial thought is that performance will improve, since each search would involve a smaller number of documents. However, I'm new to Elasticsearch and would like to know if there’s a flaw in this reasoning. I assume I won’t run into an oversharding problem (only three indexes/shards), right? 🙂

My setup is a single machine with 4 cores and 12 GB of RAM.

Thank you in advance!

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**Author:** ![Tortoise](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/tortoise/32/147587_2.png) [@Tortoise](https://discuss.elastic.co/u/Tortoise)\
**Post date:** [May 20, 2025, 6:14am UTC](https://discuss.elastic.co/t/one-index-or-multiple-index-for-exact-same-mapping-but-the-data-are-clustered-based-on-a-field/378311/2 "2025-05-20T06:14:42Z")

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Hello,

As per my understanding, you should be able to see some performance improvement as the document will be available in 3 different indices & query will be against required doc\_type.  
But the question is if there is any performance issue for current setup with the document count & search against this single index?

Thanks!!

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<div class="post-metadata">

**Author:** ![orfeas\_filippopoulos](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/orfeas_filippopoulos/32/143210_2.png) [@orfeas\_filippopoulos](https://discuss.elastic.co/u/orfeas_filippopoulos)\
**Post date:** [May 20, 2025, 7:10pm UTC](https://discuss.elastic.co/t/one-index-or-multiple-index-for-exact-same-mapping-but-the-data-are-clustered-based-on-a-field/378311/3 "2025-05-20T19:10:33Z")

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Thanks for your quick response!

Just to clarify: each document is stored in only one index, and I don’t filter by `doc_type` — instead, I query directly against the index that holds documents of that specific type. Is that what you meant?

To be honest, I already set things up with 3 separate indices from the start, so I don’t know if there were any performance issues with a single-index approach — that’s on me 😄. But since the document count might eventually grow to around 300k, I wanted to take a more proactive approach rather than having to migrate and reindex everything later.