New

The executive guide to generative AI

Read more
About usPartnersSupport|Login

WARNING: Version 1.4 of Elasticsearch has passed its EOL date.

This documentation is no longer being maintained and may be removed. If you are running this version, we strongly advise you to upgrade. For the latest information, see the current release documentation.

« Date Histogram Aggregation GeoHash grid Aggregation »
Elastic Docs ›Elasticsearch Guide [1.4] ›Search APIs ›Aggregations

Geo Distance Aggregation

edit

Geo Distance Aggregation

edit

A multi-bucket aggregation that works on geo_point fields and conceptually works very similar to the range aggregation. The user can define a point of origin and a set of distance range buckets. The aggregation evaluate the distance of each document value from the origin point and determines the buckets it belongs to based on the ranges (a document belongs to a bucket if the distance between the document and the origin falls within the distance range of the bucket).

{
    "aggs" : {
        "rings_around_amsterdam" : {
            "geo_distance" : {
                "field" : "location",
                "origin" : "52.3760, 4.894",
                "ranges" : [
                    { "to" : 100 },
                    { "from" : 100, "to" : 300 },
                    { "from" : 300 }
                ]
            }
        }
    }
}

Response:

{
    "aggregations": {
        "rings" : {
            "buckets": [
                {
                    "key": "*-100.0",
                    "from": 0,
                    "to": 100.0,
                    "doc_count": 3
                },
                {
                    "key": "100.0-300.0",
                    "from": 100.0,
                    "to": 300.0,
                    "doc_count": 1
                },
                {
                    "key": "300.0-*",
                    "from": 300.0,
                    "doc_count": 7
                }
            ]
        }
    }
}

The specified field must be of type geo_point (which can only be set explicitly in the mappings). And it can also hold an array of geo_point fields, in which case all will be taken into account during aggregation. The origin point can accept all formats supported by the geo_point type:

  • Object format: { "lat" : 52.3760, "lon" : 4.894 } - this is the safest format as it is the most explicit about the lat & lon values
  • String format: "52.3760, 4.894" - where the first number is the lat and the second is the lon
  • Array format: [4.894, 52.3760] - which is based on the GeoJson standard and where the first number is the lon and the second one is the lat

By default, the distance unit is m (metres) but it can also accept: mi (miles), in (inches), yd (yards), km (kilometers), cm (centimeters), mm (millimeters).

{
    "aggs" : {
        "rings" : {
            "geo_distance" : {
                "field" : "location",
                "origin" : "52.3760, 4.894",
                "unit" : "mi", 
                "ranges" : [
                    { "to" : 100 },
                    { "from" : 100, "to" : 300 },
                    { "from" : 300 }
                ]
            }
        }
    }
}

The distances will be computed as miles

There are three distance calculation modes: sloppy_arc (the default), arc (most accurate) and plane (fastest). The arc calculation is the most accurate one but also the more expensive one in terms of performance. The sloppy_arc is faster but less accurate. The plane is the fastest but least accurate distance function. Consider using plane when your search context is "narrow" and spans smaller geographical areas (like cities or even countries). plane may return higher error mergins for searches across very large areas (e.g. cross continent search). The distance calculation type can be set using the distance_type parameter:

{
    "aggs" : {
        "rings" : {
            "geo_distance" : {
                "field" : "location",
                "origin" : "52.3760, 4.894",
                "distance_type" : "plane",
                "ranges" : [
                    { "to" : 100 },
                    { "from" : 100, "to" : 300 },
                    { "from" : 300 }
                ]
            }
        }
    }
}
« Date Histogram Aggregation GeoHash grid Aggregation »
Was this helpful?
Feedback