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Elastic Docs ›Elasticsearch Guide [8.2] ›Aggregations ›Bucket aggregations

Geohex grid aggregation

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Geohex grid aggregation

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A multi-bucket aggregation that groups geo_point values into buckets that represent a grid. The resulting grid can be sparse and only contains cells that have matching data. Each cell corresponds to a H3 cell index and is labeled using the H3Index representation.

See the table of cell areas for H3 resolutions on how precision (zoom) correlates to size on the ground. Precision for this aggregation can be between 0 and 15, inclusive.

High-precision requests can be very expensive in terms of RAM and result sizes. For example, the highest-precision geohex with a precision of 15 produces cells that cover less than 10cm by 10cm. We recommend you use a filter to limit high-precision requests to a smaller geographic area. For an example, refer to High-precision requests.

Simple low-precision request

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PUT /museums
{
  "mappings": {
    "properties": {
      "location": {
        "type": "geo_point"
      }
    }
  }
}

POST /museums/_bulk?refresh
{"index":{"_id":1}}
{"location": "52.374081,4.912350", "name": "NEMO Science Museum"}
{"index":{"_id":2}}
{"location": "52.369219,4.901618", "name": "Museum Het Rembrandthuis"}
{"index":{"_id":3}}
{"location": "52.371667,4.914722", "name": "Nederlands Scheepvaartmuseum"}
{"index":{"_id":4}}
{"location": "51.222900,4.405200", "name": "Letterenhuis"}
{"index":{"_id":5}}
{"location": "48.861111,2.336389", "name": "Musée du Louvre"}
{"index":{"_id":6}}
{"location": "48.860000,2.327000", "name": "Musée d'Orsay"}

POST /museums/_search?size=0
{
  "aggregations": {
    "large-grid": {
      "geohex_grid": {
        "field": "location",
        "precision": 4
      }
    }
  }
}

Response:

{
  ...
  "aggregations": {
    "large-grid": {
      "buckets": [
        {
          "key": "841969dffffffff",
          "doc_count": 3
        },
        {
          "key": "841fb47ffffffff",
          "doc_count": 2
        },
        {
          "key": "841fa4dffffffff",
          "doc_count": 1
        }
      ]
    }
  }
}

High-precision requests

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When requesting detailed buckets (typically for displaying a "zoomed in" map), a filter like geo_bounding_box should be applied to narrow the subject area. Otherwise, potentially millions of buckets will be created and returned.

POST /museums/_search?size=0
{
  "aggregations": {
    "zoomed-in": {
      "filter": {
        "geo_bounding_box": {
          "location": {
            "top_left": "52.4, 4.9",
            "bottom_right": "52.3, 5.0"
          }
        }
      },
      "aggregations": {
        "zoom1": {
          "geohex_grid": {
            "field": "location",
            "precision": 12
          }
        }
      }
    }
  }
}

Response:

{
  ...
  "aggregations": {
    "zoomed-in": {
      "doc_count": 3,
      "zoom1": {
        "buckets": [
          {
            "key": "8c1969c9b2617ff",
            "doc_count": 1
          },
          {
            "key": "8c1969526d753ff",
            "doc_count": 1
          },
          {
            "key": "8c1969526d26dff",
            "doc_count": 1
          }
        ]
      }
    }
  }
}

Requests with additional bounding box filtering

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The geohex_grid aggregation supports an optional bounds parameter that restricts the cells considered to those that intersect the provided bounds. The bounds parameter accepts the same bounding box formats as the geo-bounding box query. This bounding box can be used with or without an additional geo_bounding_box query for filtering the points prior to aggregating. It is an independent bounding box that can intersect with, be equal to, or be disjoint to any additional geo_bounding_box queries defined in the context of the aggregation.

POST /museums/_search?size=0
{
  "aggregations": {
    "tiles-in-bounds": {
      "geohex_grid": {
        "field": "location",
        "precision": 12,
        "bounds": {
          "top_left": "52.4, 4.9",
          "bottom_right": "52.3, 5.0"
        }
      }
    }
  }
}

Response:

{
  ...
  "aggregations": {
    "tiles-in-bounds": {
      "buckets": [
        {
          "key": "8c1969c9b2617ff",
          "doc_count": 1
        },
        {
          "key": "8c1969526d753ff",
          "doc_count": 1
        },
        {
          "key": "8c1969526d26dff",
          "doc_count": 1
        }
      ]
    }
  }
}

Options

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field

(Required, string) Field containing indexed geo-point values. Must be explicitly mapped as a geo_point field. If the field contains an array, geohex_grid aggregates all array values.

precision

(Optional, integer) Integer zoom of the key used to define cells/buckets in the results. Defaults to 6. Values outside of [0,15] will be rejected.

bounds

(Optional, object) Bounding box used to filter the geo-points in each bucket. Accepts the same bounding box formats as the geo-bounding box query.

size

(Optional, integer) Maximum number of buckets to return. Defaults to 10,000. When results are trimmed, buckets are prioritized based on the volume of documents they contain.

shard_size

(Optional, integer) Number of buckets returned from each shard. Defaults to max(10,(size x number-of-shards)) to allow for more a accurate count of the top cells in the final result.

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