# Multiple search criteria across different documents sharing a common key

**URL:** <https://forum.opensearch.org/t/multiple-search-criteria-across-different-documents-sharing-a-common-key/28186>\
**Category:** OpenSearch\
**Tags:** discuss\
**Created:** [July 3, 2026, 9:06am UTC](https://forum.opensearch.org/t/multiple-search-criteria-across-different-documents-sharing-a-common-key/28186 "2026-07-03T09:06:33Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![danilopiazza](https://sea1.discourse-cdn.com/flex019/user_avatar/forum.opensearch.org/danilopiazza/32/9971_2.png) [@danilopiazza](https://forum.opensearch.org/u/danilopiazza)\
**Post date:** [July 3, 2026, 9:06am UTC](https://forum.opensearch.org/t/multiple-search-criteria-across-different-documents-sharing-a-common-key/28186/1 "2026-07-03T09:06:33Z")

</div>

**Versions** : (relevant - OpenSearch/Dashboard/Server OS/Browser): OpenSearch 3.7.0.

**Describe the issue** : I have multiple documents which share the same «business ID». Using multiple search criteria, which can be satisfied by distinct documents, how can I find all the matching «business ID»s?

Given this index mapping:

```auto
PUT myindex
{
  "mappings": {
    "properties": {
      "business_id": {
        "type": "keyword"
      },
      "color": {
        "type": "keyword"
      }
    }
  }
}

```

and the following data:

```auto
POST myindex/_doc
{
  "business_id": "123",
  "color": "red"
}

POST myindex/_doc
{
  "business_id": "123",
  "color": "cerise"
}

POST myindex/_doc
{
  "business_id": "456",
  "color": "cerulean"
}

POST myindex/_doc
{
  "business_id": "789",
  "color": "red"
}

```

I tried this query:

```auto
GET myindex/_search
{
  "query": {
    
    "bool": {
      "should": [
        {
          "term": {
            "color": {
              "value": "red"
            }
          }
        },
        {
          "term": {
            "color": {
              "value": "cerise"
            }
          }
        }
      ],
      "minimum_should_match": 1
    }
  },
  "size": 0, 
  "aggs": {
    "business_ids": {
      "terms": {
        "field": "business_id",
        "size": 10,
        "min_doc_count": 2
      }
    }
  }
}

```

It works, but:

1. This feels overly complicated. Is there a more concise way to express the same query?
2. Should I be worried about the aggregation performance?

**Configuration** : OpenSearch and OpenSearch Dashboards started locally as Docker containers with `docker run -d --name opensearch -p 9200:9200 -e 'DISABLE_SECURITY_PLUGIN=true' -e 'discovery.type=single-node' opensearchproject/opensearch` and `docker run -d --name dashboards -p 5601:5601 -e 'DISABLE_SECURITY_DASHBOARDS_PLUGIN=true' -e 'OPENSEARCH_HOSTS=["http://<my local IP address>:9200"]' opensearchproject/opensearch-dashboards`, respectively.

---

<div class="post-metadata">

**Author:** ![Yanlin](https://sea1.discourse-cdn.com/flex019/user_avatar/forum.opensearch.org/yanlin/32/10286_2.png) [@Yanlin](https://forum.opensearch.org/u/Yanlin)\
**Post date:** [July 3, 2026, 12:54pm UTC](https://forum.opensearch.org/t/multiple-search-criteria-across-different-documents-sharing-a-common-key/28186/2 "2026-07-03T12:54:59Z")

</div>

Hi @danilopiazza,

Thanks for providing a clear example.

Yes. Since both conditions are exact matches on the same `keyword` field, you can replace the two `term` clauses with a single `terms` query:

```auto
GET myindex/_search
{
  "size": 0,
  "query": {
    "terms": {
      "color": ["red", "cerise"]
    }
  },
  "aggs": {
    "business_ids": {
      "terms": {
        "field": "business_id",
        "size": 10,
        "min_doc_count": 2
      }
    }
  }
}

```

For the sample shown, aggregation performance should not be a concern. At a larger scale, the main factors are the number of matching documents, the number of unique `business_id` values, and the number of buckets requested.

One thing to note: this approach assumes that each color appears at most once for a given `business_id`. If duplicate color values are possible, `min_doc_count: 2` only guarantees that two documents matched either `red` or `cerise`; it does not guarantee that both colors are present.

Also, `"size": 10` returns at most 10 business ID buckets, not all matching business IDs. If you need to retrieve every matching business ID from a large result set, consider using a paginated `composite` aggregation rather than setting a very large `terms.size`.