Search a vector tile

POST also GET /{index}/_mvt/{field}/{zoom}/{x}/{y}

Search a vector tile for geospatial values. Before using this API, you should be familiar with the Mapbox vector tile specification. The API returns results as a binary mapbox vector tile.

Internally, Elasticsearch translates a vector tile search API request into a search containing:

A geo_bounding_box query on the <field>. The query uses the <zoom>/<x>/<y> tile as a bounding box.
A geotile_grid or geohex_grid aggregation on the <field>. The grid_agg parameter determines the aggregation type. The aggregation uses the <zoom>/<x>/<y> tile as a bounding box.
Optionally, a geo_bounds aggregation on the <field>. The search only includes this aggregation if the exact_bounds parameter is true.
If the optional parameter with_labels is true, the internal search will include a dynamic runtime field that calls the getLabelPosition function of the geometry doc value. This enables the generation of new point features containing suggested geometry labels, so that, for example, multi-polygons will have only one label.

The API returns results as a binary Mapbox vector tile. Mapbox vector tiles are encoded as Google Protobufs (PBF). By default, the tile contains three layers:

A hits layer containing a feature for each <field> value matching the geo_bounding_box query.
An aggs layer containing a feature for each cell of the geotile_grid or geohex_grid. The layer only contains features for cells with matching data.
A meta layer containing:
- A feature containing a bounding box. By default, this is the bounding box of the tile.
- Value ranges for any sub-aggregations on the geotile_grid or geohex_grid.
- Metadata for the search.

The API only returns features that can display at its zoom level. For example, if a polygon feature has no area at its zoom level, the API omits it. The API returns errors as UTF-8 encoded JSON.

IMPORTANT: You can specify several options for this API as either a query parameter or request body parameter. If you specify both parameters, the query parameter takes precedence.

Grid precision for geotile

For a grid_agg of geotile, you can use cells in the aggs layer as tiles for lower zoom levels. grid_precision represents the additional zoom levels available through these cells. The final precision is computed by as follows: <zoom> + grid_precision. For example, if <zoom> is 7 and grid_precision is 8, then the geotile_grid aggregation will use a precision of 15. The maximum final precision is 29. The grid_precision also determines the number of cells for the grid as follows: (2^grid_precision) x (2^grid_precision). For example, a value of 8 divides the tile into a grid of 256 x 256 cells. The aggs layer only contains features for cells with matching data.

Grid precision for geohex

For a grid_agg of geohex, Elasticsearch uses <zoom> and grid_precision to calculate a final precision as follows: <zoom> + grid_precision.

This precision determines the H3 resolution of the hexagonal cells produced by the geohex aggregation. The following table maps the H3 resolution for each precision. For example, if <zoom> is 3 and grid_precision is 3, the precision is 6. At a precision of 6, hexagonal cells have an H3 resolution of 2. If <zoom> is 3 and grid_precision is 4, the precision is 7. At a precision of 7, hexagonal cells have an H3 resolution of 3.

Precision	Unique tile bins	H3 resolution	Unique hex bins	Ratio
1	4	0	122	30.5
2	16	0	122	7.625
3	64	1	842	13.15625
4	256	1	842	3.2890625
5	1024	2	5882	5.744140625
6	4096	2	5882	1.436035156
7	16384	3	41162	2.512329102
8	65536	3	41162	0.6280822754
9	262144	4	288122	1.099098206
10	1048576	4	288122	0.2747745514
11	4194304	5	2016842	0.4808526039
12	16777216	6	14117882	0.8414913416
13	67108864	6	14117882	0.2103728354
14	268435456	7	98825162	0.3681524172
15	1073741824	8	691776122	0.644266719
16	4294967296	8	691776122	0.1610666797
17	17179869184	9	4842432842	0.2818666889
18	68719476736	10	33897029882	0.4932667053
19	274877906944	11	237279209162	0.8632167343
20	1099511627776	11	237279209162	0.2158041836
21	4398046511104	12	1660954464122	0.3776573213
22	17592186044416	13	11626681248842	0.6609003122
23	70368744177664	13	11626681248842	0.165225078
24	281474976710656	14	81386768741882	0.2891438866
25	1125899906842620	15	569707381193162	0.5060018015
26	4503599627370500	15	569707381193162	0.1265004504
27	18014398509482000	15	569707381193162	0.03162511259
28	72057594037927900	15	569707381193162	0.007906278149
29	288230376151712000	15	569707381193162	0.001976569537

Hexagonal cells don't align perfectly on a vector tile. Some cells may intersect more than one vector tile. To compute the H3 resolution for each precision, Elasticsearch compares the average density of hexagonal bins at each resolution with the average density of tile bins at each zoom level. Elasticsearch uses the H3 resolution that is closest to the corresponding geotile density.

Learn how to use the vector tile search API with practical examples in the Vector tile search examples guide.

Required authorization

Index privileges: read

More about mapbox vector tiles

Path Parameters

Query Parameters

exact_bounds boolean · default: false

If false, the meta layer's feature is the bounding box of the tile. If true, the meta layer's feature is a bounding box resulting from a geo_bounds aggregation. The aggregation runs on

extent number · default: 4096

The size, in pixels, of a side of the tile. Vector tiles are square with equal sides.

grid_agg enum GridAggregationType · default: geotile

Aggregation used to create a grid for field.

Values: geotile geohex

grid_precision number · default: 8

Additional zoom levels available through the aggs layer. For example, if

grid_type enum GridType · default: grid

Determines the geometry type for features in the aggs layer. In the aggs layer, each feature represents a geotile_grid cell. If 'grid' each feature is a Polygon of the cells bounding box. If 'point' each feature is a Point that is the centroid of the cell.

Values: grid point centroid

size number · default: 10000

Maximum number of features to return in the hits layer. Accepts 0-10000. If 0, results don't include the hits layer.

track_total_hits boolean | number · default: 10000

The number of hits matching the query to count accurately. If true, the exact number of hits is returned at the cost of some performance. If false, the response does not include the total number of hits matching the query.

with_labels boolean · default: false

If true, the hits and aggs layers will contain additional point features representing suggested label positions for the original features.

Point and MultiPoint features will have one of the points selected.
Polygon and MultiPolygon features will have a single point generated, either the centroid, if it is within the polygon, or another point within the polygon selected from the sorted triangle-tree.
LineString features will likewise provide a roughly central point selected from the triangle-tree.
The aggregation results will provide one central point for each aggregation bucket.

All attributes from the original features will also be copied to the new label features. In addition, the new features will be distinguishable using the tag _mvt_label_position.

Request

aggs map string to {} AggregationContainer

Sub-aggregations for the geotile_grid.

It supports the following aggregation types:

avg
boxplot
cardinality
extended stats
max
median absolute deviation
min
percentile
percentile-rank
stats
sum
value count

The aggregation names can't start with _mvt_. The _mvt_ prefix is reserved for internal aggregations.

buffer number · default: 5

The size, in pixels, of a clipping buffer outside the tile. This allows renderers to avoid outline artifacts from geometries that extend past the extent of the tile.

exact_bounds boolean · default: false

If false, the meta layer's feature is the bounding box of the tile. If true, the meta layer's feature is a bounding box resulting from a geo_bounds aggregation. The aggregation runs on

extent number · default: 4096

The size, in pixels, of a side of the tile. Vector tiles are square with equal sides.

fields string Fields

The fields to return in the hits layer. It supports wildcards (*). This parameter does not support fields with array values. Fields with array values may return inconsistent results.

grid_agg enum GridAggregationType

The aggregation used to create a grid for the field.

Values: geotile geohex

grid_precision number · default: 8

Additional zoom levels available through the aggs layer. For example, if <zoom> is 7 and grid_precision is 8, you can zoom in up to level 15. Accepts 0-8. If 0, results don't include the aggs layer.

grid_type enum GridType · default: grid

Determines the geometry type for features in the aggs layer. In the aggs layer, each feature represents a geotile_grid cell. If grid, each feature is a polygon of the cells bounding box. If point`, each feature is a Point that is the centroid of the cell.

Values: grid point centroid

query {} QueryContainer

The query DSL used to filter documents for the search.

runtime_mappings RuntimeFields

Defines one or more runtime fields in the search request. These fields take precedence over mapped fields with the same name.

size number · default: 10000

The maximum number of features to return in the hits layer. Accepts 0-10000. If 0, results don't include the hits layer.

sort Sort

Sort the features in the hits layer. By default, the API calculates a bounding box for each feature. It sorts features based on this box's diagonal length, from longest to shortest.

track_total_hits boolean | number · default: 10000

with_labels boolean

If true, the hits and aggs layers will contain additional point features representing suggested label positions for the original features.

Point and MultiPoint features will have one of the points selected.
Polygon and MultiPolygon features will have a single point generated, either the centroid, if it is within the polygon, or another point within the polygon selected from the sorted triangle-tree.
LineString features will likewise provide a roughly central point selected from the triangle-tree.
The aggregation results will provide one central point for each aggregation bucket.

All attributes from the original features will also be copied to the new label features. In addition, the new features will be distinguishable using the tag _mvt_label_position.

Response

application/json

Examples

Run POST museums/_mvt/location/13/4207/2692 to search an index for location values that intersect the 13/4207/2692 vector tile.

Request Console 1 / 8 languages

Console Kibana Dev Tools

POST 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"
      }
    }
  }
}

JavaScript Elasticsearch JavaScript Client

const response = await client.searchMvt({
  index: "museums",
  field: "location",
  zoom: 13,
  x: 4207,
  y: 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",
      },
    },
  },
});

Python Elasticsearch Python Client

resp = client.search_mvt(
    index="museums",
    field="location",
    zoom="13",
    x="4207",
    y="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"
            }
        }
    },
)

curl Shell

curl -X POST "$ELASTICSEARCH_URL/museums/_mvt/location/13/4207/2692" \
  -H "Authorization: ApiKey $ELASTIC_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "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"
        }
      }
    }
  }'

Java Elasticsearch Java Client

client.searchMvt(s -> s
    .aggs(Map.of("max_price", Aggregation.of(a -> a
            .max(m -> m
                .field("price")
            )
        ),"min_price", Aggregation.of(ag -> ag
            .min(m -> m
                .field("price")
            )
        ),"avg_price", Aggregation.of(agg -> agg
            .avg(av -> av
                .field("price")
            )
        )))
    .field("location")
    .fields(List.of("name","price"))
    .gridAgg(GridAggregationType.Geotile)
    .gridPrecision(2)
    .index("museums")
    .query(q -> q
        .term(t -> t
            .field("included")
            .value(FieldValue.of(true))
        )
    )
    .x(4207)
    .y(2692)
    .zoom(13)
);

C# Elasticsearch .NET Client

var response = await client
    .SearchMvtAsync(indices: new[] { "museums" }, field: global::Elastic.Clients.Elasticsearch.Infer.Field<MyDocument>(x => x.Location), zoom: 13, x: 4207, y: 2692, d1 => d1
        .Aggs(d2 => d2
            .Add("min_price", d3 => d3
                .Min(d4 => d4
                    .Field(x => x.Price)
                )
            )
            .Add("max_price", d3 => d3
                .Max(d4 => d4
                    .Field(x => x.Price)
                )
            )
            .Add("avg_price", d3 => d3
                .Avg(d4 => d4
                    .Field(x => x.Price)
                )
            )
        )
        .Fields(x => x.Name, x => x.Price)
        .GridAgg(GridAggregationType.Geotile)
        .GridPrecision(2)
        .Query(d2 => d2
            .Term(d3 => d3
                .Field(x => x.Included)
                .Value(true)
            )
        )
    );

PHP Elasticsearch PHP Client

$resp = $client->searchMvt([
    "index" => "museums",
    "field" => "location",
    "zoom" => "13",
    "x" => "4207",
    "y" => "2692",
    "body" => [
        "grid_agg" => "geotile",
        "grid_precision" => 2,
        "fields" => array(
            "name",
            "price",
        ),
        "query" => [
            "term" => [
                "included" => true,
            ],
        ],
        "aggs" => [
            "min_price" => [
                "min" => [
                    "field" => "price",
                ],
            ],
            "max_price" => [
                "max" => [
                    "field" => "price",
                ],
            ],
            "avg_price" => [
                "avg" => [
                    "field" => "price",
                ],
            ],
        ],
    ],
]);

Ruby Elasticsearch Ruby Client

response = client.search_mvt(
  index: "museums",
  field: "location",
  zoom: "13",
  x: "4207",
  y: "2692",
  body: {
    "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"
        }
      }
    }
  }
)

Response

{
  "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
      }
    ]
  }
}

Required authorization

Path Parameters { index , field , zoom , x , y , }

Query Parameters { exact_bounds , extent , grid_agg , grid_precision , grid_type , size , track_total_hits , with_labels , }

Request { aggs , buffer , exact_bounds , extent , fields , grid_agg , grid_precision , grid_type , query , runtime_mappings , size , sort , track_total_hits , with_labels , }

Response

Path Parameters

Query Parameters

Request