Set more than 10000 number of values in data tables

Elastic Stack Kibana
,
1

Hi, I'm trying to fetch more than 10000 number of values in my kibana data table visualization.

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I get the error above, I edited index.max_result_window in all my elasticSearch indexes. But I get the same error

I can use the same query changing the size value in json format, it works, but in Kibana not.

{
    "aggs": {
      "0": {
        "terms": {
          "field": "XXXXXXXX",
          "order": {
            "_count": "desc"
          },
          "size": 100000
        }
      }
    },
    "size": 0,
    "fields": [
      {
        "field": "Date",
        "format": "date_time"
      },
      {
        "field": "insertion_time",
        "format": "date_time"
      }
    ],
    "script_fields": {},
    "stored_fields": [
      "*"
    ],
    "runtime_mappings": {},
    "_source": {
      "excludes": []
    },
    "query": {
      "bool": {
        "must": [],
        "filter": [
          {
            "bool": {
              "must_not": {
                "bool": {
                  "should": [
                    {
                      "match": {
                        "Progressive": "1"
                      }
                    }
                  ],
                  "minimum_should_match": 1
                }
              }
            }
          },
          {
            "range": {
              "Date": {
                "format": "strict_date_optional_time",
                "gte": "2025-02-25T09:28:56.413Z",
                "lte": "2025-03-12T09:28:56.413Z"
              }
            }
          }
        ],
        "should": [],
        "must_not": []
      }
    }
  }

What can I do to get it work?
Kibana version: 8.9.0
Elastic version: 8.9.0

2

in short; You can’t.

In Kibana Lens/Data Table, the “Top values → Number of values” has a hard UI cap of 10,000 per terms agg. Changing index.max_result_window (hits pagination) doesn’t affect this, and ES might accept size: 100000 via API, but Lens won’t.

Workarounds

  • Use the Elasticsearch API with a composite aggregation (paginated via after_key) to fetch >10k buckets.

  • Or materialize results with a Transform/rollup and visualize that.

  • If you truly need all distinct values in Kibana, rethink the viz—10k+ buckets is heavy and slow.

instead, use a composite aggregation in Python and page through all buckets.