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This guide walks you through indexing documents with geographic coordinates, then filtering and sorting results by location.

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Add _geo to your documents

Documents must contain a _geo field with lat and lng values: 
[
  {
    "id": 1,
    "name": "Nàpiz' Milano",
    "address": "Viale Vittorio Veneto, 30, 20124, Milan, Italy",
    "type": "pizza",
    "rating": 9,
    "_geo": {
      "lat": 45.4777599,
      "lng": 9.1967508
    }
  },
  {
    "id": 2,
    "name": "Bouillon Pigalle",
    "address": "22 Bd de Clichy, 75018 Paris, France",
    "type": "french",
    "rating": 8,
    "_geo": {
      "lat": 48.8826517,
      "lng": 2.3352748
    }
  },
  {
    "id": 3,
    "name": "Artico Gelateria Tradizionale",
    "address": "Via Dogana, 1, 20123 Milan, Italy",
    "type": "ice cream",
    "rating": 10,
    "_geo": {
      "lat": 45.4632046,
      "lng": 9.1719421
    }
  }
]
Trying to index a dataset with one or more documents containing badly formatted _geo values will cause Meilisearch to throw an invalid_document_geo_field error. In this case, the update will fail and no documents will be added or modified.
Meilisearch also supports GeoJSON for complex geometries like polygons and multi-polygons.

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Configure filterable and sortable attributes

To filter results by location, add _geo to filterableAttributes: 
curl \
  -X PUT 'MEILISEARCH_URL/indexes/restaurants/settings/filterable-attributes' \
  -H 'Content-type:application/json' \
  --data-binary '["_geo"]'
To sort results by distance, add _geo to sortableAttributes: 
curl \
  -X PUT 'MEILISEARCH_URL/indexes/restaurants/settings/sortable-attributes' \
  -H 'Content-type:application/json' \
  --data-binary '["_geo"]'
Meilisearch will rebuild your index whenever you update these settings. Depending on the size of your dataset, this might take a considerable amount of time.

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Filter results by location

Use the filter search parameter with _geoRadius to find results within a given distance from a point. The following example searches for restaurants within 2km of central Milan: 
curl \
  -X POST 'MEILISEARCH_URL/indexes/restaurants/search' \
  -H 'Content-type:application/json' \
  --data-binary '{ "filter": "_geoRadius(45.472735, 9.184019, 2000)" }'

[
  {
    "id": 1,
    "name": "Nàpiz' Milano",
    "address": "Viale Vittorio Veneto, 30, 20124, Milan, Italy",
    "type": "pizza",
    "rating": 9,
    "_geo": {
      "lat": 45.4777599,
      "lng": 9.1967508
    }
  },
  {
    "id": 3,
    "name": "Artico Gelateria Tradizionale",
    "address": "Via Dogana, 1, 20123 Milan, Italy",
    "type": "ice cream",
    "rating": 10,
    "_geo": {
      "lat": 45.4632046,
      "lng": 9.1719421
    }
  }
]

​
Sort results by distance

Use _geoPoint in the sort search parameter to order results by proximity. The following example sorts restaurants by distance from the Eiffel Tower: 
curl \
  -X POST 'MEILISEARCH_URL/indexes/restaurants/search' \
  -H 'Content-type:application/json' \
  --data-binary '{ "sort": ["_geoPoint(48.8561446,2.2978204):asc"] }'

[
  {
    "id": 2,
    "name": "Bouillon Pigalle",
    "address": "22 Bd de Clichy, 75018 Paris, France",
    "type": "french",
    "rating": 8,
    "_geo": {
      "lat": 48.8826517,
      "lng": 2.3352748
    }
  },
  …
]

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Next steps

Filter by radius

Find results within a circular area around a point

Filter by bounding box

Find results within a rectangular area

Filter by polygon

Find results within a custom polygon shape

Sort by distance

Rank results by proximity to a location

Use GeoJSON format

Index complex geometries with the GeoJSON standard