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Elastic Docs ›Elasticsearch: The Definitive Guide [1.x] ›Geolocation ›Geo Points

Geo Distance Filter

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Geo Distance Filter

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The geo_distance filter draws a circle around the specified location and finds all documents that have a geo-point within that circle:

GET /attractions/restaurant/_search
{
  "query": {
    "filtered": {
      "filter": {
        "geo_distance": {
          "distance": "1km", 
          "location": { 
            "lat":  40.715,
            "lon": -73.988
          }
        }
      }
    }
  }
}

Find all location fields within 1km of the specified point. See Distance Units for a list of the accepted units.

The central point can be specified as a string, an array, or (as in this example) an object. See Lat/Lon Formats.

A geo-distance calculation is expensive. To optimize performance, Elasticsearch draws a box around the circle and first uses the less expensive bounding-box calculation to exclude as many documents as it can. It runs the geo-distance calculation on only those points that fall within the bounding box.

Do your users really require an accurate circular filter to be applied to their results? Using a rectangular bounding box is much more efficient than geo-distance and will usually serve their purposes just as well.

Faster Geo-Distance Calculations

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The distance between two points can be calculated using algorithms, which trade performance for accuracy:

arc
The slowest but most accurate is the arc calculation, which treats the world as a sphere. Accuracy is still limited because the world isn’t really a sphere.
plane
The plane calculation, which treats the world as if it were flat, is faster but less accurate. It is most accurate at the equator and becomes less accurate toward the poles.
sloppy_arc
So called because it uses the SloppyMath Lucene class to trade accuracy for speed, the sloppy_arc calculation uses the Haversine formula to calculate distance. It is four to five times as fast as arc, and distances are 99.9% accurate. This is the default calculation.

You can specify a different calculation as follows:

GET /attractions/restaurant/_search
{
  "query": {
    "filtered": {
      "filter": {
        "geo_distance": {
          "distance":      "1km",
          "distance_type": "plane", 
          "location": {
            "lat":  40.715,
            "lon": -73.988
          }
        }
      }
    }
  }
}

Use the faster but less accurate plane calculation.

Will your users really care if a restaurant is a few meters outside their specified radius? While some geo applications require great accuracy, less-accurate but faster calculations will suit the majority of use cases just fine.

geo_distance_range Filter

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The only difference between the geo_distance and geo_distance_range filters is that the latter has a doughnut shape and excludes documents within the central hole.

Instead of specifying a single distance from the center, you specify a minimum distance (with gt or gte) and maximum distance (with lt or lte), just like a range filter:

GET /attractions/restaurant/_search
{
  "query": {
    "filtered": {
      "filter": {
        "geo_distance_range": {
          "gte":    "1km", 
          "lt":     "2km", 
          "location": {
            "lat":  40.715,
            "lon": -73.988
          }
        }
      }
    }
  }
}

Matches locations that are at least 1km from the center, and less than 2km from the center.
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