---
mapped_pages:
  - https://www.elastic.co/guide/en/elasticsearch/reference/8.18/search-vector-tile-api.html#search-vector-tile-api-api-example
applies_to:
  stack: all
navigation_title: Vector tile search API
---

# Vector tile search API examples

The [vector tile search API](https://www.elastic.co/docs/api/doc/elasticsearch/operation/operation-search-mvt-1) searches for geospatial data within a specific tile coordinate (zoom/x/y) and returns the results as a binary Mapbox Vector Tile (MVT) containing hits, aggregations, and metadata. This page shows how to create an index with geospatial data and retrieve vector tile results using the API.


You can learn how to:
- [Create an index with geospatial fields](#create-an-index-with-geospatial-fields)
- [Query geospatial data using a vector tile](#query-a-vector-tile-for-geospatial-data)
- [Understand the structure of the API response](#example-response)
- [Understand how the request is internally translated](#how-elasticsearch-translates-the-request-internally)

## Create an index with geospatial fields

The following requests create the `museum` index and add several geospatial
`location` values.

```console
PUT museums
{
  "mappings": {
    "properties": {
      "location": {
        "type": "geo_point"
      },
      "name": {
        "type": "keyword"
      },
      "price": {
        "type": "long"
      },
      "included": {
        "type": "boolean"
      }
    }
  }
}

POST museums/_bulk?refresh
{ "index": { "_id": "1" } }
{ "location": "POINT (4.912350 52.374081)", "name": "NEMO Science Museum",  "price": 1750, "included": true }
{ "index": { "_id": "2" } }
{ "location": "POINT (4.901618 52.369219)", "name": "Museum Het Rembrandthuis", "price": 1500, "included": false }
{ "index": { "_id": "3" } }
{ "location": "POINT (4.914722 52.371667)", "name": "Nederlands Scheepvaartmuseum", "price":1650, "included": true }
{ "index": { "_id": "4" } }
{ "location": "POINT (4.914722 52.371667)", "name": "Amsterdam Centre for Architecture", "price":0, "included": true }
```

## Query a vector tile for geospatial data

The following request searches the index for `location` values that intersect
the `13/4207/2692` vector tile.

```console
GET museums/_mvt/location/13/4207/2692
{
  "grid_agg": "geotile",
  "grid_precision": 2,
  "fields": [
    "name",
    "price"
  ],
  "query": {
    "term": {
      "included": true
    }
  },
  "aggs": {
    "min_price": {
      "min": {
        "field": "price"
      }
    },
    "max_price": {
      "max": {
        "field": "price"
      }
    },
    "avg_price": {
      "avg": {
        "field": "price"
      }
    }
  }
}
```
% TEST[continued]

## Example response

The API returns results as a binary vector tile. When decoded into JSON, the
tile contains the following data:

```js
{
  "hits": {
    "extent": 4096,
    "version": 2,
    "features": [
      {
        "geometry": {
          "type": "Point",
          "coordinates": [
            3208,
            3864
          ]
        },
        "properties": {
          "_id": "1",
          "_index": "museums",
          "name": "NEMO Science Museum",
          "price": 1750
        },
        "type": 1
      },
      {
        "geometry": {
          "type": "Point",
          "coordinates": [
            3429,
            3496
          ]
        },
        "properties": {
          "_id": "3",
          "_index": "museums",
          "name": "Nederlands Scheepvaartmuseum",
          "price": 1650
        },
        "type": 1
      },
      {
        "geometry": {
          "type": "Point",
          "coordinates": [
            3429,
            3496
          ]
        },
        "properties": {
          "_id": "4",
          "_index": "museums",
          "name": "Amsterdam Centre for Architecture",
          "price": 0
        },
        "type": 1
      }
    ]
  },
  "aggs": {
    "extent": 4096,
    "version": 2,
    "features": [
      {
        "geometry": {
          "type": "Polygon",
          "coordinates": [
            [
              [
                3072,
                3072
              ],
              [
                4096,
                3072
              ],
              [
                4096,
                4096
              ],
              [
                3072,
                4096
              ],
              [
                3072,
                3072
              ]
            ]
          ]
        },
        "properties": {
          "_count": 3,
          "max_price.value": 1750.0,
          "min_price.value": 0.0,
          "avg_price.value": 1133.3333333333333
        },
        "type": 3
      }
    ]
  },
  "meta": {
    "extent": 4096,
    "version": 2,
    "features": [
      {
        "geometry": {
          "type": "Polygon",
          "coordinates": [
            [
              [
                0,
                0
              ],
              [
                4096,
                0
              ],
              [
                4096,
                4096
              ],
              [
                0,
                4096
              ],
              [
                0,
                0
              ]
            ]
          ]
        },
        "properties": {
          "_shards.failed": 0,
          "_shards.skipped": 0,
          "_shards.successful": 1,
          "_shards.total": 1,
          "aggregations._count.avg": 3.0,
          "aggregations._count.count": 1,
          "aggregations._count.max": 3.0,
          "aggregations._count.min": 3.0,
          "aggregations._count.sum": 3.0,
          "aggregations.avg_price.avg": 1133.3333333333333,
          "aggregations.avg_price.count": 1,
          "aggregations.avg_price.max": 1133.3333333333333,
          "aggregations.avg_price.min": 1133.3333333333333,
          "aggregations.avg_price.sum": 1133.3333333333333,
          "aggregations.max_price.avg": 1750.0,
          "aggregations.max_price.count": 1,
          "aggregations.max_price.max": 1750.0,
          "aggregations.max_price.min": 1750.0,
          "aggregations.max_price.sum": 1750.0,
          "aggregations.min_price.avg": 0.0,
          "aggregations.min_price.count": 1,
          "aggregations.min_price.max": 0.0,
          "aggregations.min_price.min": 0.0,
          "aggregations.min_price.sum": 0.0,
          "hits.max_score": 0.0,
          "hits.total.relation": "eq",
          "hits.total.value": 3,
          "timed_out": false,
          "took": 2
        },
        "type": 3
      }
    ]
  }
}
```
% NOTCONSOLE

## How Elasticsearch translates the request internally

{{es}} may translate a vector tile search API request with a
`grid_agg` argument of `geotile` and an `exact_bounds` argument of `true`
into the following search:

<!--
```console
PUT my-index
{
  "mappings": {
    "properties": {
      "my-geo-field": {
        "type": "geo_point"
      }
    }
  }
}

PUT my-index/_doc/0?refresh
{
  "my-geo-field": "POINT (-122.0863176 37.3864953)"
}
```
-->

```console
GET my-index/_search
{
  "size": 10000,
  "query": {
    "geo_bounding_box": {
      "my-geo-field": {
        "top_left": {
          "lat": -40.979898069620134,
          "lon": -45
        },
        "bottom_right": {
          "lat": -66.51326044311186,
          "lon": 0
        }
      }
    }
  },
  "aggregations": {
    "grid": {
      "geotile_grid": {
        "field": "my-geo-field",
        "precision": 11,
        "size": 65536,
        "bounds": {
          "top_left": {
            "lat": -40.979898069620134,
            "lon": -45
          },
          "bottom_right": {
            "lat": -66.51326044311186,
            "lon": 0
          }
        }
      }
    },
    "bounds": {
      "geo_bounds": {
        "field": "my-geo-field",
        "wrap_longitude": false
      }
    }
  }
}
```
% TEST[continued]